Template-Type: ReDIF-Article 1.0
Author-Name: Feyisayo Akinwande
Author-X-Name-First: Feyisayo
Author-X-Name-Last: Akinwande
Author-Name: Olusegun Akanbi
Author-X-Name-First: Olusegun
Author-X-Name-Last: Akanbi
Author-Name: Samson Akindele
Author-X-Name-First: Samson
Author-X-Name-Last: Akindele
Title: Computer-aided ergonomics design and comparative analysis of waiting chairs at a health centre
Abstract:
This study explains the ergonomics design and comparative analysis of chairs (waiting) at a health centre using anthropometric data and CATIA V5R20 software to perform finite element analysis (FEA) and determine the most efficient ergonomic design. From the collected data, the analysis was conducted based on percentiles; with the use of Excel. The modelling of the chairs was performed using its materials. FEA was also conducted for the designed waiting chairs to check, for stress, deformation and displacement. The human builder part of CATIA V5R20 was used to test, for the efficiency and the physical interaction across the user and the designed chair. The results obtained showed that computer-aided ergonomics design is not limited to anthropometric data collection, and designing of products. It is also a means of determining the quality of the designed product.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 338-359
Issue: 3
Volume: 42
Year: 2022
Keywords: ergonomics design; computer-aided design; CATIA V5R20; FEA analysis; anthropometrics; chairs.
File-URL: http://www.inderscience.com/link.php?id=126980
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:3:p:338-359
Template-Type: ReDIF-Article 1.0
Author-Name: Athakorn Kengpol
Author-X-Name-First: Athakorn
Author-X-Name-Last: Kengpol
Author-Name: Jakkarin Klunngien
Author-X-Name-First: Jakkarin
Author-X-Name-Last: Klunngien
Title: Design of a machine learning to classify health beverages preferences for elderly people: an empirical study during COVID-19 in Thailand
Abstract:
This research designed a decision support system based upon a machine learning (DSS-ML) model for classifying health beverage preferences for elderly people. A neural network was designed involving training using particle swarm optimisation (PSO) in comparison with two ML models: logistic regression (LR) and a neural network (NN). The DSS-ML model was able to classify accurately and autonomously the preference complexities associated with the health beverage preferences for elderly people in accordance with the WHO's recommendation. In terms of contribution, the results demonstrated that NN training with PSO resulted in a higher ability to classify the preferences for health beverages than for the two ML models. Furthermore, NN training with PSO achieved faster convergence than NN. The benefits of this research can be separated into two parts. First, manufacturers can introduce beverages that satisfy elderly people's preferences. Second, elderly people can be made aware of appropriate health beverages.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 319-337
Issue: 3
Volume: 42
Year: 2022
Keywords: decision support system; DSS; machine learning; elderly people; neural network; particle swarm optimisation; PSO; logistic regression; backpropagation; COVID-19; Thailand.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:3:p:319-337
Template-Type: ReDIF-Article 1.0
Author-Name: Renan Eduardo Pereira Barros
Author-X-Name-First: Renan Eduardo Pereira
Author-X-Name-Last: Barros
Author-Name: João Pedro Coelho Figueiredo Simas
Author-X-Name-First: João Pedro Coelho Figueiredo
Author-X-Name-Last: Simas
Author-Name: Rogério Frauendorf de Faria Coimbra
Author-X-Name-First: Rogério Frauendorf de Faria
Author-X-Name-Last: Coimbra
Author-Name: Marcelo Santiago de Sousa
Author-X-Name-First: Marcelo Santiago de
Author-X-Name-Last: Sousa
Title: Application of systems engineering to design the architecture of an enterprise of wind turbines inspection
Abstract:
The use of systems engineering techniques is presented in this work to design the architecture of an enterprise of wind turbines inspection. The motivation for this research is the possibility to acquire detailed data in order to make one improved technical and financial feasibility analysis. This way, it is considered that there will be lower risks and higher return of investment. The use of systems engineering included the problem definition, requirements specification, requirements validation, and definition of physical and logical architecture descriptions. All this information offered more data to perform more detailed calculus of investment needed to create this enterprise, and the price of the offered service.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 277-298
Issue: 3
Volume: 42
Year: 2022
Keywords: systems engineering; enterprise architecture; wind turbines inspection; renewable energy; enterprise systems engineering; ESE.
File-URL: http://www.inderscience.com/link.php?id=126985
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:3:p:277-298
Template-Type: ReDIF-Article 1.0
Author-Name: Román Felipe Bastidas Santacruz
Author-X-Name-First: Román Felipe Bastidas
Author-X-Name-Last: Santacruz
Author-Name: Roberto Rocca
Author-X-Name-First: Roberto
Author-X-Name-Last: Rocca
Author-Name: Elisa Negri
Author-X-Name-First: Elisa
Author-X-Name-Last: Negri
Author-Name: Luca Fumagalli
Author-X-Name-First: Luca
Author-X-Name-Last: Fumagalli
Title: A review of features and applications of distributed ledger technologies for smart manufacturing
Abstract:
Among the different smart technologies with the highest digitalisation capacity for manufacturing environments, distributed ledger technologies (DLT) has the potential to support one of the main challenges to be faced in the new environment created by the Industry 4.0 paradigm, i.e., the interchange of data through the supply chain. DLT enhances data immutability and transparency and offers new possibilities of interactions and business models to the new industrial networks, allowing a trustable horizontal and vertical data flow between different organisations. Although these possible improvements are in sight, the approach and characteristics that can make the technology suitable with the I4.0 paradigm, are not yet well-defined, and in some cases puzzling for industry managers. In this paper, possible applications, features of DLTs and its available types are reviewed and analysed, giving a clear definition of the most relevant characteristics that these technologies can offer to manufacturing industry.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 360-407
Issue: 3
Volume: 42
Year: 2022
Keywords: distributed ledger technologies; DLT; blockchains; Industry 4.0; manufacturing applications; direct acyclic graph; smart manufacturing; networks.
File-URL: http://www.inderscience.com/link.php?id=126987
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:3:p:360-407
Template-Type: ReDIF-Article 1.0
Author-Name: Cynthia Renea Lovelace
Author-X-Name-First: Cynthia Renea
Author-X-Name-Last: Lovelace
Title: Assessing logistics process performance using the perfect order index: confidence intervals and process capability analysis
Abstract:
Perfect order fulfilment, as measured by the perfect order index (<i>POI</i>), has become the leading key performance indicator (KPI) for logistics service quality and overall supply chain reliability. Little research has appeared in the literature to evaluate the properties of this index and the impacts of sampling variability upon its confidence bounds. The purpose of this research is to develop confidence limits for the <i>POI</i>, evaluate the sensitivity of the <i>POI</i> point estimate to proportion component variability, and propose a new process capability index, <i>C</i><SUB align="right"><SMALL><i>pl</i>(<i>POI</i>)</SMALL></SUB>, to measure fulfilment process capability to produce a perfect order. The delta distribution was utilised to develop confidence intervals for the <i>POI</i> and the process capability index, <i>C</i><SUB align="right"><SMALL><i>pl</i>(<i>POI</i>)</SMALL></SUB>. Simulation was then used to develop approximate 95% and 99% lower confidence bounds for <i>C</i><SUB align="right"><SMALL><i>pl</i>(<i>POI</i>)</SMALL></SUB>, for select combinations of component proportions.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 299-318
Issue: 3
Volume: 42
Year: 2022
Keywords: order fulfilment; perfect order fulfilment; perfect order index; POI; process capability; supply chain; logistics; performance measure; key performance indicator; KPI; supply chain metrics; delta distribution; supply chain simulation.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:3:p:299-318
Template-Type: ReDIF-Article 1.0
Author-Name: Gnanasekaran Sasikumar
Author-X-Name-First: Gnanasekaran
Author-X-Name-Last: Sasikumar
Author-Name: A. Sivasangari
Author-X-Name-First: A.
Author-X-Name-Last: Sivasangari
Title: Solar panel selection using an integrated analytical hierarchy process and multi-objective optimisation by ratio analysis: an empirical study
Abstract:
A solar panel is a vital element of a photovoltaic (PV) system. Hence, it is essential to study the reduction of material costs of a solar panel without compromising the efficiency of it. Selection of solar panel is a complex problem due to the presence of various quantitative and qualitative parameters. This paper deals with the development of a mathematical model by combining analytical hierarchy process (AHP) and multi-objective optimisation by ratio analysis (MOORA) for the evaluation and ranking of solar panels. The AHP method is utilised to fix compromise solution with incommensurable and contradictory criteria, consisting of five potential solar panels and eight selection parameters. The AHP technique is adopted for calculating the criteria weights based on the relative importance. Consequently, MOORA method is used for ranking and selecting the solar panel alternatives. The proposed AHP and MOORA approach is found to be effective for the evaluation and ranking of solar panels as it produces comparable results with VIKOR method. In the VIKOR method, alternatives are ranked based on closeness to positive ideal solution.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 64-79
Issue: 1
Volume: 42
Year: 2022
Keywords: solar panel; analytical hierarchy process; AHP; multi-objective optimisation; multi-criteria decision-making; MCDM; ratio analysis; VIKOR.
File-URL: http://www.inderscience.com/link.php?id=126018
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:64-79
Template-Type: ReDIF-Article 1.0
Author-Name: Seyed-Hadi Mirghaderi
Author-X-Name-First: Seyed-Hadi
Author-X-Name-Last: Mirghaderi
Author-Name: Behnam Hassanizadeh
Author-X-Name-First: Behnam
Author-X-Name-Last: Hassanizadeh
Title: k-most suitable locations problem: greedy search approach
Abstract:
Facility location problems have been highly considered in the literature and employed in various real-world situations. The <i>k</i>-most suitable locations (<i>k</i>-MSL) problem is a type of site-selection problem, a direction of facility location problems. It can be applied in several areas like disaster management, urban development, telecommunication and franchising corporations. This paper aims to develop heuristics for the problem. It proposes four greedy search algorithms to find solutions for the <i>k</i>-MSL problem and provide a baseline for comparing future solutions. The proposed greedy algorithms solve the problem for all values of <i>k</i>. The computational experiments using real-world datasets reveal that one of the developed algorithms is superior in consuming CPU time, and the other three algorithms provide accurate solutions in low <i>k</i> and good solutions in all values of <i>k</i> in a reasonable time.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 80-95
Issue: 1
Volume: 42
Year: 2022
Keywords: location science; k-most suitable locations; k-MSL; heuristics; facility location; greedy search.
File-URL: http://www.inderscience.com/link.php?id=126019
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:80-95
Template-Type: ReDIF-Article 1.0
Author-Name: Raviteja Buddala
Author-X-Name-First: Raviteja
Author-X-Name-Last: Buddala
Author-Name: Siba Sankar Mahapatra
Author-X-Name-First: Siba Sankar
Author-X-Name-Last: Mahapatra
Author-Name: Manas Ranjan Singh
Author-X-Name-First: Manas Ranjan
Author-X-Name-Last: Singh
Title: Solving multi-objective flexible flow-shop scheduling problem using teaching-learning-based optimisation embedded with maximum deviation theory
Abstract:
Flexible flow-shop scheduling problem (FFSP) is an extended special case of basic flow-shop scheduling problem (FSP). FFSP is treated as complex NP-hard scheduling problem. A good scheduling practice enables the manufacturer to compete effectively in the marketplace. An efficient schedule should address multiple conflicting objectives so that customer satisfaction can be improved. In this work, a novel approach based on teaching-learning-based optimisation (TLBO) technique incorporated with maximum deviation theory (MDT) is applied to generate schedules that simultaneously optimise conflicting objective measures like makespan and flowtime. Results indicate that the proposed multi-objective TLBO (MOTLBO) outperforms non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimisation (MOPSO) in majority of the problem instances.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 39-63
Issue: 1
Volume: 42
Year: 2022
Keywords: flexible flow-shop scheduling problem; FFSP; flowtime; makespan; maximum deviation theory; MDT; non-dominated solutions; multi-objective optimisation; teaching-learning-based optimisation; TLBO; flow-shop scheduling problem; FSP; multi-objective particle swarm optimisation; MOPSO.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:39-63
Template-Type: ReDIF-Article 1.0
Author-Name: Muhammad Waseem
Author-X-Name-First: Muhammad
Author-X-Name-Last: Waseem
Author-Name: Tufail Habib
Author-X-Name-First: Tufail
Author-X-Name-Last: Habib
Author-Name: Usman Ghani
Author-X-Name-First: Usman
Author-X-Name-Last: Ghani
Author-Name: Muhammad Abas
Author-X-Name-First: Muhammad
Author-X-Name-Last: Abas
Author-Name: Qazi Muhammad Usman Jan
Author-X-Name-First: Qazi Muhammad Usman
Author-X-Name-Last: Jan
Author-Name: Muhammad Alam Zaib Khan
Author-X-Name-First: Muhammad Alam Zaib
Author-X-Name-Last: Khan
Title: Optimisation of tensile and compressive behaviour of PLA 3D printed parts using categorical response surface methodology
Abstract:
The present study aims to optimise process parameters of 3-D printed polylactic acid (PLA) part using response surface methodology (RSM). The input printing process parameters considered are layer height (<i>L</i>), infill percentage (<i>I</i>), raster width (<i>R</i>) and infill patterns (<i>P</i>) (i.e., linear, hexagonal and diamond), while the responses are tensile and compressive strengths. Box Behnken array design is applied for experimental runs and also to fit quadratic regression models. The results revealed that significant parameters affecting compression strength performance are <i>I</i>, <i>I</i><SUP align="right"><SMALL>2</SMALL></SUP>, <i>R</i>, and interaction of <i>I</i> and <i>R</i>, for tensile strength, are <i>L</i>, <i>I</i>, <i>I</i><SUP align="right"><SMALL>2</SMALL></SUP>, <i>R</i>, <i>P</i>, and interaction of <i>P</i> with <i>L</i> and <i>I</i>. The simultaneously optimised parameters obtained based on composite desirability function for compression and tensile strength are <i>L</i> = 0.1 mm, <i>I</i> = 100%, <i>R</i> = 0.4 mm, and <i>P</i> = hexagonal, while the obtained maximum compression and tensile strength are 9.06 kN and 1.67 kN.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 417-437
Issue: 4
Volume: 41
Year: 2022
Keywords: additive manufacturing; fused deposition modelling; FDM; polylactic acid; PLA; tensile strength; compression strength; response surface methodology; RSM.
File-URL: http://www.inderscience.com/link.php?id=124997
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:4:p:417-437
Template-Type: ReDIF-Article 1.0
Author-Name: Wen Wang
Author-X-Name-First: Wen
Author-X-Name-Last: Wang
Author-Name: Xiang Liu
Author-X-Name-First: Xiang
Author-X-Name-Last: Liu
Author-Name: Hao Cai
Author-X-Name-First: Hao
Author-X-Name-Last: Cai
Author-Name: Shanghong He
Author-X-Name-First: Shanghong
Author-X-Name-Last: He
Author-Name: Yuelin Li
Author-X-Name-First: Yuelin
Author-X-Name-Last: Li
Title: Optimisation study on the drain mode of cycloidal rotor oil pump
Abstract:
In order to optimise the internal flow field pulsation characteristics of a cycloidal rotor oil pump, the internal oil drain structure of the pressure limiting valve was changed to an external oil drain structure. The numerical simulation method is used to calculate the internal flow field of the cycloidal oil pump with different drain structures. The outlet pressure pulsation, pressure pulsation at the pressure limiting valve, displacement of the pressure limiting valve spool and cavitation are compared and analysed. The results show that, relative to internal drain structure, the pressure amplitude of the external drain structure at the pressure limiting valve is reduced by 30%, the pressure amplitude at the outlet is reduced by 25%, and the cavitation phenomenon at the interface between the pressure limiting valve and the inlet cavity is eliminated. The bench test is carried out to verify the sample pump, and the test results are in good agreement with the simulation results, with the volume efficiency improved by up to 4%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 118-129
Issue: 1
Volume: 42
Year: 2022
Keywords: cycloidal rotor oil pump; pressure pulsation; pressure limiting valve; oil drain structure.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:118-129
Template-Type: ReDIF-Article 1.0
Author-Name: Shima Shirvani
Author-X-Name-First: Shima
Author-X-Name-Last: Shirvani
Author-Name: Mohammad Reza Shahraki
Author-X-Name-First: Mohammad Reza
Author-X-Name-Last: Shahraki
Title: A multi-level green reverse logistics network design for single manufacturer and integration of return distribution warehouses in supply chain management
Abstract:
This study develops a linear programming model in a closed loop supply chain network including supply, production, distribution, collection, recycling and disposal centres taking into account variables of route, vehicle and volume of the vehicle. Multilevel and multi-product modes are also considered for single manufacturer and integration of return distribution warehouses and processing costs are also taken into account in locations. All modifiable returned goods are shipped to production and distribution centres to be provided to the consumer directly in the logistics process. The purpose of the model is to reduce costs of the green reverse logistics network. The proposed model reduces the cost of transportation according to the vehicle, route and vehicle size; ultimately reduces the costs of reverse logistics network distribution. An example is reviewed for validation of the proposed model and finally general conclusions are presented. The results show that the proposed model is able to determine the best route, type of vehicle and shipping volume and in the reverse logistics network.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 438-454
Issue: 4
Volume: 41
Year: 2022
Keywords: reverse logistics; supply chain; return distribution cost; returned products.
File-URL: http://www.inderscience.com/link.php?id=124998
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:4:p:438-454
Template-Type: ReDIF-Article 1.0
Author-Name: Huynh Trung Luong
Author-X-Name-First: Huynh Trung
Author-X-Name-Last: Luong
Author-Name: Ashish Devkota
Author-X-Name-First: Ashish
Author-X-Name-Last: Devkota
Author-Name: Sidharath Joshi
Author-X-Name-First: Sidharath
Author-X-Name-Last: Joshi
Title: Supply chain network design under distribution centre disruption
Abstract:
In the 21st century, with the rise of increasing competition and highly volatile customer demands, managing and designing supply chain networks have become critical in most industries. While designing the supply chain, disruption must be taken into consideration. However, when dealing with supply chain disruptions, most of past research works focused only on uncertainties/disruptions at supply side or demand side. In fact, disruptions should also be considered at distribution centres. This research aims at deriving a mathematical model for a three-stage logistics network consisting of a single manufacturing plant, multiple potential locations for opening distribution centres with associated risk of disruption, and multiple customer zones. A scenario-based mathematical modelling approach is used to determine the locations at which a fixed number of distribution centres should be opened. The key challenge in developing the combined total cost function which incorporated all disruption scenarios is how to develop a general expression for the probabilities of occurrence of various disruption scenarios. This is the unique contribution of this research in terms of mathematical model development. Numerical experiments were then performed to illustrate the applicability of the proposed model. Sensitivity analyses have also been conducted to examine the robustness of the solution.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 20-38
Issue: 1
Volume: 42
Year: 2022
Keywords: supply chain network design; SCND; location-allocation problem; mixed integer linear programming; disruption; risk; uncertainty.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:20-38
Template-Type: ReDIF-Article 1.0
Author-Name: Xiaofei Liu
Author-X-Name-First: Xiaofei
Author-X-Name-Last: Liu
Title: Personalised resource recommendation method for collaborative tagging system based on machine learning
Abstract:
In order to overcome the low feasibility of traditional resource recommendation methods, this paper proposes a personalised resource recommendation method based on machine learning. Firstly, the user-based collaborative filtering algorithm is used to calculate user personalised similarity, and then content-based collaborative filtering algorithm is used to calculate resource content similarity through cosine similarity. Combined with user similarity and resource content similarity, a hybrid computing model of resource similarity is established, and personalised recommendation is realised through statistical machine learning. The experimental results show that: the F-measure value of the method can reach 0.97, the coverage rate is maintained above 50%, the popularity is above 0.8, and the MAE value is always the minimum, and its precision is always higher than that of the contrast method. It shows that the proposed method can effectively improve the precision and feasibility of personalised recommendation results.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-19
Issue: 1
Volume: 42
Year: 2022
Keywords: machine learning; collaborative tagging system; personalised resource recommendation; similarity.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:1-19
Template-Type: ReDIF-Article 1.0
Author-Name: Ajith Tom James
Author-X-Name-First: Ajith Tom
Author-X-Name-Last: James
Title: Maintenance performance evaluation of bus fleet garages using a hybrid approach
Abstract:
Availability of automobiles in fleet service is very crucial and is often influenced by the maintenance. Generally, bus fleet organisations have got their own garage facilities. However, the maintenance performance levels of garages need not to be the same with all organisations and locations. Hence, a measurement system is necessary to evaluate the maintenance performance of garages for corrective actions. This paper develops a framework for maintenance performance measurement (MPM) based on MPIs specific to the objectives of fleet service maintenance garages based on hybrid methodology that is a combination analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The hybrid methodology is applied for comparing maintenance performance of garages of four different municipal bus fleet services in India. The novelty of this paper includes development of MPIs specific to garages of bus fleet and comparison of the fleet garages based on maintenance performance.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 472-501
Issue: 4
Volume: 41
Year: 2022
Keywords: fleet service garage; maintenance performance measurement; MPM; analytic hierarchy process; AHP; TOPSIS.
File-URL: http://www.inderscience.com/link.php?id=125000
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:4:p:472-501
Template-Type: ReDIF-Article 1.0
Author-Name: Jean Guilherme Azarias
Author-X-Name-First: Jean Guilherme
Author-X-Name-Last: Azarias
Author-Name: Aparecido dos Reis Coutinho
Author-X-Name-First: Aparecido dos Reis
Author-X-Name-Last: Coutinho
Title: The energy consumption in the turbocharger manufacturing system
Abstract:
The quantification of energy consumption in manufacturing systems is an essential step for the formulation of energy efficiency strategies. In the transport sector, turbochargers are important devices, which the manufacturing system shows intense energy consumption. This study aims to quantify energy consumption throughout the manufacturing system of a turbocharger. A case study was conducted to analyse the data collected in a turbocharger manufacturer. The total energy consumption is 347.15 MJ, with 240.28 MJ corresponding to the energy consumption for component production. This is the first experimental work related to the turbocharger production, in which the main technical contribution is focused on the LCA throughout various stages of the production process. In addition, the information presented can be used to conduct a comparison with other manufacturing systems and contribute to the development of greater energy efficiency in the automotive industry.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 130-146
Issue: 1
Volume: 42
Year: 2022
Keywords: energy consumption; turbocharger; life cycle energy assessment; LCEA; manufacturing; life cycle assessment; LCA.
File-URL: http://www.inderscience.com/link.php?id=126024
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:130-146
Template-Type: ReDIF-Article 1.0
Author-Name: Akash Salunke
Author-X-Name-First: Akash
Author-X-Name-Last: Salunke
Author-Name: Ajit Lokhande
Author-X-Name-First: Ajit
Author-X-Name-Last: Lokhande
Author-Name: Akash Neharkar
Author-X-Name-First: Akash
Author-X-Name-Last: Neharkar
Author-Name: Rupesh Satpute
Author-X-Name-First: Rupesh
Author-X-Name-Last: Satpute
Author-Name: Avinash Kamble
Author-X-Name-First: Avinash
Author-X-Name-Last: Kamble
Title: Selection of engine oil using multi-attribute decision-making methods
Abstract:
The role of internal combustion engines in automobile industry has already been well recognised. It is made with closer precisions thus involve higher costs and also, it is crucial to ensure efficient working of its various components. Engine oil of specific grades is used for reducing wear and tear of components and cooling of parts of the engine. Choice of appropriate engine oil for engines is critical task for designers. Designers need to identify oils with specific properties and functionalities in order to fulfil end requirements and desired functionalities of the engine. The different oils possess different properties. Systematic approach must be used for selection of oil. Thus, the present work focuses on the selection procedure for best engine oil using four criteria selected by using multi-attribute decision-making method. The proposed methods help to evaluate and rank different engine oils in order to assist the decision maker in selecting appropriate engine oil.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 96-117
Issue: 1
Volume: 42
Year: 2022
Keywords: multi-attribute decision-making method; engine oils selection; preference ranking organisation method for enrichment evaluation; additive ratio assessment method; organisation rangement et synthese de donnes relationnelles method; elimination and choice translating reality method; analytical hierarchy process.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:1:p:96-117
Template-Type: ReDIF-Article 1.0
Author-Name: Nilufa Yeasmin
Author-X-Name-First: Nilufa
Author-X-Name-Last: Yeasmin
Author-Name: Sultana Parveen
Author-X-Name-First: Sultana
Author-X-Name-Last: Parveen
Title: The efficient routing approach of a vehicle under the vehicle routing problem with simultaneous delivery and pickup for reducing the fuel consumption and pollutants emission
Abstract:
The vehicle routing problem with simultaneous delivery and pickup (VRPSDP) has received significant attention in logistics operations to minimise the travelling distance or travelling time. However, little is known regarding the VRPSDP in logistics operations which is used to reduce the emission of CO<SUB align="right"><SMALL>2</SMALL></SUB> in the environment (i.e., critical requirements of green logistics). Our study proposes the fuel-optimisation model for the vehicle under VRPSDP referred to as an eco-friendly VRPSDP model. This model aims to determine the efficient vehicle route that will reduce the vehicle's fuel consumption as well as decrease the negative impact on the environment. The genetic algorithm (GA) is applied to solve the proposed fuel optimisation model. Here, two types of genetic mutation operator, i.e. swap and inverse are used to find out which one would give the optimum results regarding fuel consumption. The computational tests show that that the inverse mutation performs better than the swap mutation and saves the fuel consumption of 4.1% over the swap mutation.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 502-518
Issue: 4
Volume: 41
Year: 2022
Keywords: fuel optimisation; vehicle routing problem with simultaneous delivery and pick up; genetic algorithm; swap mutation and inverse mutation; reverse logistics.
File-URL: http://www.inderscience.com/link.php?id=125002
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:4:p:502-518
Template-Type: ReDIF-Article 1.0
Author-Name: Mi Wang
Author-X-Name-First: Mi
Author-X-Name-Last: Wang
Title: Design of cloud service system for enterprise economic management based on hybrid cloud mode
Abstract:
In order to overcome the problems of traditional enterprise economic management cloud service system, such as long response time, this paper designs a cloud service system for enterprise economic management based on hybrid cloud mode. The system hardware is composed of server, optical switch, optical disk storage cabinet and management module. On the basis of the hardware design, the system software is designed. The K-means algorithm is used to mine the enterprise economic data, and the data is standardised and stored in the database. The experimental results show that the system designed in this paper has good compatibility and concurrency performance, the system response time is always less than 0.5 s, and the user satisfaction is between 6.8-9.6; therefore practical application effect is better.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 455-471
Issue: 4
Volume: 41
Year: 2022
Keywords: hybrid cloud model; enterprise; economic management; cloud service system; information retrieval.
File-URL: http://www.inderscience.com/link.php?id=125003
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:4:p:455-471
Template-Type: ReDIF-Article 1.0
Author-Name: M. Geranios
Author-X-Name-First: M.
Author-X-Name-Last: Geranios
Author-Name: M.I. Vidalis
Author-X-Name-First: M.I.
Author-X-Name-Last: Vidalis
Author-Name: S.I. Koukoumialos
Author-X-Name-First: S.I.
Author-X-Name-Last: Koukoumialos
Author-Name: A.C. Diamantidis
Author-X-Name-First: A.C.
Author-X-Name-Last: Diamantidis
Title: Analytical solution and optimisation of serial supply chains with multiple nodes, lost sales, continuous review replenishment policies, stochastic lead times and external demand
Abstract:
This work analyses a serial supply chain with an arbitrary number of nodes (retailer, wholesaler, manufacturer, supplier, etc.). Every node faces supply uncertainty in both replenishment lead time and quantity delivered (except for the most upstream node, assumed saturated). The most downstream node (retailer) faces external Poisson demand with rate <i>λ</i>. Each node follows a continuous review (<i>s</i><i><SUB align="right"><SMALL>i</SMALL></SUB></i>, <i>S</i><i><SUB align="right"><SMALL>i</SMALL></SUB></i>), <i>i</i> = 1, 2, …, <i>K</i> - 1 replenishment policy. If a node is insufficiently stocked, then the order is only partially satisfied. The system parameters that influence the performance of the supply chain are the number of nodes, the upper level of inventories, the reorder levels, the replenishment times, and the demand rate. The supply network is modelled as a continuous time Markov process with discrete states. We explore the structure of the transition matrices and develop a computational algorithm to generate the stationary probability distributions for any combination of the system parameters. We also use the proposed algorithm as a design and optimisation tool to determine the optimal inventory policies (i.e., reorder level and order-up-to-level) to maximise the fill rate (FR) or minimise the work-in-process (WIP) for multi-echelon serial supply chains.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 519-550
Issue: 4
Volume: 41
Year: 2022
Keywords: supply chain management; SCM; inventory control; lost demand; continuous review policy; performance evaluation.
File-URL: http://www.inderscience.com/link.php?id=125004
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:4:p:519-550
Template-Type: ReDIF-Article 1.0
Author-Name: Ramesh Rudrapati
Author-X-Name-First: Ramesh
Author-X-Name-Last: Rudrapati
Title: Industry 4.0: prospects and challenges leading to smart manufacturing
Abstract:
Fourth Industrial Revolution proposed advancements in production processes and its automation. Industry 4.0 (I4.0) is a broad domain to create smart factory which includes manufacturing methods, economy, data management, relationships between consumer and manufacturer, etc. I4.0 is introducing new themes of research to produce smart products which need to be explored at bottom levels of prospects and goals by academicians, business scholars, and various contributors of scientific community. The main aim of the present study is to review the prospects and challenges of I4.0 related various issues and aspects of smart manufacturing. Important components in I4.0 are also explored and discussed. Status of research works on I4.0 and its applications are included. Challenges faced by industrialists are mentioned and discussed. Various features and issues related to I4.0 discussed in the present study are expected to clarify the aims and fundamental components of I4.0. Concluding remarks has been drawn from the study.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 230-244
Issue: 2
Volume: 42
Year: 2022
Keywords: Industry 4.0; smart manufacturing; prospects of I4.0; challenges of I4.0.
File-URL: http://www.inderscience.com/link.php?id=126037
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:230-244
Template-Type: ReDIF-Article 1.0
Author-Name: Masoud Rahiminezhad Galankashi
Author-X-Name-First: Masoud Rahiminezhad
Author-X-Name-Last: Galankashi
Author-Name: Aida Rezaei
Author-X-Name-First: Aida
Author-X-Name-Last: Rezaei
Author-Name: Mobina Keyvanpazhooh
Author-X-Name-First: Mobina
Author-X-Name-Last: Keyvanpazhooh
Author-Name: Farimah Mokhatab Rafiei
Author-X-Name-First: Farimah Mokhatab
Author-X-Name-Last: Rafiei
Title: Assessment of suppliers and optimum order allocation in agile automotive manufacturing companies
Abstract:
This paper develops a systematic approach to assist agile automotive manufacturers to assess their potential suppliers and allocate required orders. Agile manufacturing (AM) and its related concepts have been discussed in previous literature. However, its integration with purchasing and supplier selection is less examined. Therefore, the development process of agile supplier selection framework is the main addressed problem of this research. A comprehensive investigation on previous studies and analytic hierarchy process (AHP) were applied to finalise agile supplier selection criteria. Next, the developed agile supplier selection criteria were applied to assess suppliers using fuzzy analytic hierarchy process (FAHP). Finally, a multi-period and multi-objective order allocation model was developed to determine optimum agile purchasing quantity of items from suppliers. Therefore, the main outputs of this research include agile supplier selection criteria, ranking of suppliers and multi-period purchasing quantity from suppliers. In addition, a sensitivity analysis was applied to provide more understandable and practical outputs.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 245-276
Issue: 2
Volume: 42
Year: 2022
Keywords: supplier selection; agile manufacturing; AM; order allocation; analytic hierarchy process; AHP; fuzzy analytic hierarchy process; FAHP.
File-URL: http://www.inderscience.com/link.php?id=126038
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:245-276
Template-Type: ReDIF-Article 1.0
Author-Name: Neeta Sharma
Author-X-Name-First: Neeta
Author-X-Name-Last: Sharma
Author-Name: Prem Vrat
Author-X-Name-First: Prem
Author-X-Name-Last: Vrat
Title: Behavioural inventory management: a new approach to inventory classification based on stock-induced consumption index
Abstract:
This paper presents an analysis of exploratory survey conducted to investigate the consumers' perception by using the instrument of structured questionnaire about stock-induced consumption of various commodities which would invariably result in resource wastage. The intended outcome of this survey is to find out the stock-induced consumption index of these commodities which exhibit behavioural tendencies of different consumers. This would eventually be used by inventory control practitioners to estimate the shape parameter (β) of these commodities because parameter estimation is identified as the major limitation resulting in poor applicability of the stock-dependent demand inventory models. In addition, this paper attempts to classify these commodities on the basis of their high, medium and low potential for stock-induced consumption (HML analysis) to facilitate use of resources to their maximum efficiency by concentrating on items having the greatest potential for wasteful consumption. Perishability is considered as one of the driving forces in stock-induced consumption and an attempt is made to establish a relationship between perishability of these commodities and their stock-induced consumption. The individual consumer behaviour influences the waste caused by stock-induced consumption and the paper proposes to bring in behavioural inventory management in managing material waste.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-18
Issue: 1
Volume: 41
Year: 2022
Keywords: stock-dependent demand; stock-induced consumption index; perishability index; HML analysis; behavioural inventory management.
File-URL: http://www.inderscience.com/link.php?id=122967
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:1:p:1-18
Template-Type: ReDIF-Article 1.0
Author-Name: Shahed Sholekar
Author-X-Name-First: Shahed
Author-X-Name-Last: Sholekar
Author-Name: Mehdi Seifbarghy
Author-X-Name-First: Mehdi
Author-X-Name-Last: Seifbarghy
Author-Name: Davar Pishva
Author-X-Name-First: Davar
Author-X-Name-Last: Pishva
Title: Innovative local search heuristics for uncapacitated facility location problem
Abstract:
This paper presents four different local search heuristics, abbreviated as PSC, PSTC, PTSC and PFSC, for handling the UFLP. It compares their outcome with that of a previously proposed equivalent heuristic called add-swap neighbourhood search (ASNS). One of its main focus is to reduce processing time since ASNS heuristic's computational time is quite long and continues to increase in an exponential order with magnitude of the problem. The proposed heuristics use a two-phase approach wherein the first phase ranks the potential facilities' locations and selects an initial solution from the ranking; and the second phase keeps on adding other locations from the ranking list, one at a time, until the stop criterion is achieved. Its results show that the proposed heuristics reduce computational time dramatically when compared with the ASNS. Furthermore, the PFSC heuristic provides better performance in both computational time and solution quality when dealing with large size problems.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 172-192
Issue: 2
Volume: 42
Year: 2022
Keywords: location; UFLP; uncapacitated; local search; heuristics; mixed-integer programming.
File-URL: http://www.inderscience.com/link.php?id=126039
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:172-192
Template-Type: ReDIF-Article 1.0
Author-Name: Yuval Cohen
Author-X-Name-First: Yuval
Author-X-Name-Last: Cohen
Author-Name: Maurizio Faccio
Author-X-Name-First: Maurizio
Author-X-Name-Last: Faccio
Author-Name: Mauro Gamberi
Author-X-Name-First: Mauro
Author-X-Name-Last: Gamberi
Title: Absenteeism and turnover performance analysis of multi-model and mixed-model assembly lines
Abstract:
Assembly lines are characterised by high rates of turnover and absenteeism. Any case of absenteeism or turnover requires assigning a replacement worker who is often inexperienced. Learning process is crucial for increasing productivity in such replacement cases, but learning is dependent on the variety of product models produced on that line. The complexity effect of the tasks at the assembly station, owing to a multi-model pattern, can result in a forgetting curve. The current research investigates the absenteeism in various batch sizes of multi-model and mixed-model assembly lines, introducing an innovative adaptation of the learning and forgetting functions. Secondly, it analyses the assembly system performance through a simulation study, focusing on the models' commonality and models sequences in the case of new substitute workers. A case study and a simulation analysis are reported to validate the research.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 147-171
Issue: 2
Volume: 42
Year: 2022
Keywords: absenteeism; turnover; learning; forgetting; multi-model; mixed-model.
File-URL: http://www.inderscience.com/link.php?id=126040
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:147-171
Template-Type: ReDIF-Article 1.0
Author-Name: Md. Rakibul Hoque
Author-X-Name-First: Md. Rakibul
Author-X-Name-Last: Hoque
Author-Name: Jinnatul Raihan Mumu
Author-X-Name-First: Jinnatul Raihan
Author-X-Name-Last: Mumu
Author-Name: Peter Wanke
Author-X-Name-First: Peter
Author-X-Name-Last: Wanke
Author-Name: Md. Abul Kalam Azad
Author-X-Name-First: Md. Abul Kalam
Author-X-Name-Last: Azad
Title: Application of machine learning techniques in chronic disease literature: from citation mapping to research front
Abstract:
This study aims to conduct a hybrid review on applying machine learning techniques in chronic disease literature using both bibliometric and systematic review techniques. The dataset consists of 206 Scopus indexed journal articles from 2004 to 2020. The bibliometric results identify the most contributing authors, journal sources, author network, bibliometric coupling of documents, and the co-citation network. The systematic review reveals the most promising research areas, which include machine learning algorithms integrated with other techniques such as deep learning, artificial neural network, and data mining to predict chronic diseases in gastroenterology, cardiology, and neurology. Although machine learning techniques are rising in popularity in chronic disease literature, there is more room for improvement such as the challenges involved in using machine learning to predict chronic diseases, feasibility studies, and the necessity of rehabilitation and readmission in hospitals to predict a chronic attack.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 193-210
Issue: 2
Volume: 42
Year: 2022
Keywords: machine learning; chronic disease; diabetes; deep learning; bibliometric analysis; systematic review.
File-URL: http://www.inderscience.com/link.php?id=126041
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:193-210
Template-Type: ReDIF-Article 1.0
Author-Name: Jae-Dong Hong
Author-X-Name-First: Jae-Dong
Author-X-Name-Last: Hong
Title: Applying cross-efficiency evaluation methods for multi-objective emergency relief supply chain network model
Abstract:
This paper studies a multi-objective emergency relief supply chain network (<i>ERSCN</i>) model, which would play a critical role in providing disaster relief items in time. Data envelopment analysis (DEA) method is applied to identify efficient <i>ERSCN</i> schemes among the proposed schemes. To overcome the weakness of the classical DEA method, a cross-efficiency (CE) evaluation method was proposed to improve DEA's poor discriminating power. But the original CE method also reveals its own weaknesses. So, the three CE methods, called as aggressive, benevolent, and neutral methods, are proposed to complement the shortcomings of the classical DEA and CE-DEA methods. This paper proposes a process of applying these CE evaluation methods in DEA for designing the <i>ERSCN</i> system. Through a case study, the applicability of the proposed procedure is demonstrated. We observe that it performs well regarding identifying the efficient <i>ERSCN</i> systems and can be used as an important tool to design various supply chain network schemes efficiently and effectively.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 19-40
Issue: 1
Volume: 41
Year: 2022
Keywords: data envelopment analysis; DEA; cross-efficiency evaluation; emergency supply chain network.
File-URL: http://www.inderscience.com/link.php?id=122971
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:1:p:19-40
Template-Type: ReDIF-Article 1.0
Author-Name: Ali Goharshenasan
Author-X-Name-First: Ali
Author-X-Name-Last: Goharshenasan
Author-Name: Abbas Sheikh Aboumasoudi
Author-X-Name-First: Abbas Sheikh
Author-X-Name-Last: Aboumasoudi
Author-Name: Arash Shahin
Author-X-Name-First: Arash
Author-X-Name-Last: Shahin
Author-Name: Azarnoush Ansari
Author-X-Name-First: Azarnoush
Author-X-Name-Last: Ansari
Title: Identifying and classifying sustainable supply chain performance indicators: a GRI-based multivariate analysis
Abstract:
This study aims to identify and classify the performance indicators of a sustainable supply chain based on the Global Report Initiative (GRI) standard using multivariate analysis. Marjan Tile Company has been selected for the case study. Performance indicators of the sustainable supply chain have been reviewed and the GRI standard has been selected. Then, the value of each indicator has been measured using a questionnaire filled by the experts of the company. In the next step, the data has been analysed using multivariate analysis and principal component analysis (PCA). Findings on the classification of performance indicators indicated that human rights varied from nine sub-dimensions to three indicator clusters, and the indicators relevant to social dimensions of society scope and social scope of product liability varied from five sub-dimensions to three indicator clusters, implying the maximum and minimum variation of the clusters.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 41-70
Issue: 1
Volume: 41
Year: 2022
Keywords: sustainable supply chain; SSC; multivariate analysis; social dimension; GRI standard; ceramic and tile industry.
File-URL: http://www.inderscience.com/link.php?id=122972
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:1:p:41-70
Template-Type: ReDIF-Article 1.0
Author-Name: Tomás José Fontalvo-Herrera
Author-X-Name-First: Tomás José
Author-X-Name-Last: Fontalvo-Herrera
Author-Name: Roberto Herrera
Author-X-Name-First: Roberto
Author-X-Name-Last: Herrera
Author-Name: Yulibeth Gonzalez
Author-X-Name-First: Yulibeth
Author-X-Name-Last: Gonzalez
Title: Yield-level performance of quality dimensions trough T2 charts and multivariate capacity indicators applied to a fumigation services company
Abstract:
This research provides a yield-level performance of quality dimensions trough a T-squared control chart and a multivariate capacity indicator to assess the dimensions of the fumigation service. Six Sigma concepts, control charts and multivariate capability indicators were used as the theoretical basis. The research was evaluative, for which all the information regarding the quality dimensions was evaluated in 11 periods of 2019, for which the primary sources associated with the records generated by the fumigation services company were used. As results, the yield level performance was excellent; and the multivariate control chart shows variability in the quality dimensions in the analysed periods; and the multivariate capacity indicator makes it possible evaluate punctually and globally the service quality, showing a good performance. A three-phase method is proposed that allows to evaluate the service dimensions through a periodic, global, longitudinal and multidimensional perspective to guarantee the sustainability of the service quality.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 71-90
Issue: 1
Volume: 41
Year: 2022
Keywords: service quality; Six Sigma in service; multivariate control charts; multivariate capability indicators; fumigation services.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:1:p:71-90
Template-Type: ReDIF-Article 1.0
Author-Name: Tingting Sui
Author-X-Name-First: Tingting
Author-X-Name-Last: Sui
Author-Name: Jinhao Liu
Author-X-Name-First: Jinhao
Author-X-Name-Last: Liu
Author-Name: Liang Chen
Author-X-Name-First: Liang
Author-X-Name-Last: Chen
Author-Name: Qingqing Huang
Author-X-Name-First: Qingqing
Author-X-Name-Last: Huang
Author-Name: Tiebo Sun
Author-X-Name-First: Tiebo
Author-X-Name-Last: Sun
Title: An innovative forestry chassis with legs installed bionic walking foot
Abstract:
This paper studies a creative forestry chassis installed bionic walking foot with adjustable support foot (FC-BWF%ASF) based on bionic principle, proposes a method to improve terrain trafficability by avoiding direct contact with obstacles and pits of unpredictable shapes and dimensions in forestland, which is realised by controlling the posture of BWF%ASF. The kinematics model is established by D-H method and trajectory is planned with compound cycloid method. Finally, the effectiveness is verified through simulation experiment in ADAMS. The results show that the chassis can surmount obstacle of 60 mm height as ASF rotates 45 degrees, while no rotation is needed to move over sunken pit of 120 mm width. Additionally, the fluctuation range of frame barycentre in two conditions is within 1 mm and 4 mm, respectively. The conclusion shows that within structural parameters, the novel foot structure contributes to cross irregular terrain with quiet good stability.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 91-114
Issue: 1
Volume: 41
Year: 2022
Keywords: forest chassis; mechanical model; kinematics analysis; passing strategy; multibody dynamics simulation.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:1:p:91-114
Template-Type: ReDIF-Article 1.0
Author-Name: Zhe Wang
Author-X-Name-First: Zhe
Author-X-Name-Last: Wang
Author-Name: Yanyu Chen
Author-X-Name-First: Yanyu
Author-X-Name-Last: Chen
Author-Name: Chunjiao Gao
Author-X-Name-First: Chunjiao
Author-X-Name-Last: Gao
Title: Exchange rate risk sharing model of transnational supply chain considering background risk
Abstract:
By extending the single exchange rate risk in previous studies to a general additive and multiplicative background risk form, this paper proposes a game model including a retailer, a manufacturer and a supplier. Explicit expressions of the optimal decisions for the retailer, the manufacturer and the supplier are given, respectively. Furthermore, the impacts of different forms of risk on the risk-sharing behaviour of the node enterprises in the supply chain are discussed. It is found that, if there is only additive background risk, there is no risk-sharing behaviour between the retailer and the manufacturer. When multiplicative background risk exists, both retailers and manufacturers share the background risk and price risk. The risk sharing degree between retailers and manufacturers increases with the fluctuation of background risk factors, and the risk sharing degree between suppliers (retailers) and manufacturer decreases with the increase of price risk.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 115-133
Issue: 1
Volume: 41
Year: 2022
Keywords: supply chain decision; additive background risk; multiplicative background risk; risk-sharing.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:1:p:115-133
Template-Type: ReDIF-Article 1.0
Author-Name: Lei Cao
Author-X-Name-First: Lei
Author-X-Name-Last: Cao
Author-Name: Shouli Gao
Author-X-Name-First: Shouli
Author-X-Name-Last: Gao
Author-Name: Dongya Zhao
Author-X-Name-First: Dongya
Author-X-Name-Last: Zhao
Title: A new data-driven sliding mode learning control for discrete-time MIMO linear systems
Abstract:
A new data-driven sliding mode learning control (DDSMLC) is designed for a class of discrete-time MIMO linear systems in the presence of uncertainties. In this scheme, a new control is designed to enforce the states to reach and remain on the sliding surface. In addition, a recursive algorithm using system measured data is adopted to estimate the unknown system parameters, so a complete data-driven sliding mode control is designed, which does not need to know any parameters in the system. Moreover, the chattering is reduced because there is no non-smooth control used in DDSMLC. After the strict stability analysis, the effectiveness of DDSMLC is validated by MATLAB simulations.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 211-229
Issue: 2
Volume: 42
Year: 2022
Keywords: data-driven; discrete-time MIMO linear systems; parameter estimation algorithm; sliding mode learning control.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:2:p:211-229
Template-Type: ReDIF-Article 1.0
Author-Name: Seyed Milad Mirnajafizadeh
Author-X-Name-First: Seyed Milad
Author-X-Name-Last: Mirnajafizadeh
Author-Name: Mehdi Bijari
Author-X-Name-First: Mehdi
Author-X-Name-Last: Bijari
Title: Robust simultaneous lot-sizing and scheduling with considering controllable processing time and fixed carbon emission in flow-shop environment
Abstract:
A new robust model is presented for simultaneous lot-sizing and scheduling problem in a flow-shop environment with controllable processing time in this study. In view of the importance of carbon emissions in green production, this model takes account of limitations in this respect. Different speeds of machines can also affect production, back order, inventory holding costs, scrap rates, as well as carbon emissions. In the present study, a new model is proposed under certainty and uncertainty. In order to deal with uncertainty, robust optimisation is employed. The robust model in this study is in non-deterministic polynomial-time (NP) hardness complexity class; therefore, a total of five heuristic algorithms are introduced based on fix-and-relax (F%R) and fix-and-optimise (F%O) approaches to solve larger instances. In conclusion, the results obtained from the algorithms based on F%O are given higher quality solutions compared with those based on F%R heuristic.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 343-369
Issue: 3
Volume: 40
Year: 2022
Keywords: lot-sizing; scheduling; controllable processing time; carbon emission; robust optimisation; fix-and-optimise; F%O.
File-URL: http://www.inderscience.com/link.php?id=122241
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:343-369
Template-Type: ReDIF-Article 1.0
Author-Name: Yongzhong Wu
Author-X-Name-First: Yongzhong
Author-X-Name-Last: Wu
Author-Name: Xiangying Chen
Author-X-Name-First: Xiangying
Author-X-Name-Last: Chen
Author-Name: Yuxin Lu
Author-X-Name-First: Yuxin
Author-X-Name-Last: Lu
Author-Name: Yongwu Zhou
Author-X-Name-First: Yongwu
Author-X-Name-Last: Zhou
Title: Optimal pricing for ride sharing
Abstract:
The ride sharing business has developed rapidly in recent years. The pricing of the ride sharing service is critical for the profitability of the operators. Pricing too high may reduce passenger demand, and hence increase detours and distance, while pricing too low may reduce the revenue. In order to analyse the dynamics of optimal pricing, a mathematical model is developed to maximise the total profit. In the model, the higher-level pricing decision depends on the lower-level order assignment and routing problem. Numerical experiments with the model show that the operator does not necessarily benefit from providing the ride sharing option. The pricing of ride sharing is critical for profitability. When the total travel demand is high (e.g., in peak hours), the operator should adopt a lower relative pricing in order to maximise profit.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 277-291
Issue: 3
Volume: 40
Year: 2022
Keywords: ride sharing; optimal pricing; vehicle routing problem; VRP; choice model; order assignment.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:277-291
Template-Type: ReDIF-Article 1.0
Author-Name: Ammar Al-Bazi
Author-X-Name-First: Ammar
Author-X-Name-Last: Al-Bazi
Author-Name: Tunde V. Adediran
Author-X-Name-First: Tunde V.
Author-X-Name-Last: Adediran
Title: Agent-based heuristics model for measuring customer disruption impact on production and inventory replenishment
Abstract:
Agent-based simulation approach in production and inventory environment is capable of responding and adapting to disruptions caused by customers' changing requirements. The impacts of disruptions in production and inventory systems can be measured through learning and decision-making ability of system agents. In this paper, agent-based modelling integrated with heuristic optimisation approach is presented as embedded within a scheduling and rescheduling framework. The proposed approach is implemented in a disrupted OEMs parts manufacturing system. The integration of the framework modules in connection with inventory control helped production planners to manage disruptions by tracking order processing times and quantities and for performance measurement. The proposed approach is compared with the few existing related methods like the sequential method. The proposed approach not only revealed the impact of disruptions in terms of process times and order quantities but offered 'available times' which were applied for production support and inventory replenishment. This demonstrates a valuable and viable resolution strategy responding and adapting to disruptions caused by customers.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 370-398
Issue: 3
Volume: 40
Year: 2022
Keywords: customer disruption impact; inventory replenishment; agent-based simulation; heuristics optimisation; OEM environment; production scheduling.
File-URL: http://www.inderscience.com/link.php?id=122244
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:370-398
Template-Type: ReDIF-Article 1.0
Author-Name: Youxiang Zhu
Author-X-Name-First: Youxiang
Author-X-Name-Last: Zhu
Author-Name: Anqi Tian
Author-X-Name-First: Anqi
Author-X-Name-Last: Tian
Author-Name: Zhenyu Lu
Author-X-Name-First: Zhenyu
Author-X-Name-Last: Lu
Author-Name: Sijie Zhan
Author-X-Name-First: Sijie
Author-X-Name-Last: Zhan
Author-Name: Xiaoyong Wang
Author-X-Name-First: Xiaoyong
Author-X-Name-Last: Wang
Title: Research on operation and maintenance management risk assessment of power communication network based on DEMATEL
Abstract:
In order to overcome the problem of low accuracy of operation and maintenance risk assessment of power grid communication network, this paper proposes a method of operation and maintenance management risk assessment of power communication network based on DEMATEL. Based on the analysis of DEMATEL's power communication network pedigree, the assessment index system is divided into three first-class indexes: common business support, normal operation of communication network and operation and maintenance quality. The analytic hierarchy process (AHP) is introduced to calculate the risk value of operation and maintenance management of power communication network. The experimental results show that the accuracy of risk assessment method is close to 100%, and the failure rate is less than 3%, which improves the early warning rate. The accuracy of risk assessment, risk assessment rate and early warning rate of operation and maintenance management of power communication network have been improved.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 325-342
Issue: 3
Volume: 40
Year: 2022
Keywords: DEMATEL; power communication network; risk assessment; operation and maintenance.
File-URL: http://www.inderscience.com/link.php?id=122247
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:325-342
Template-Type: ReDIF-Article 1.0
Author-Name: Jianhong Xu
Author-X-Name-First: Jianhong
Author-X-Name-Last: Xu
Title: Research on energy consumption control method of green building based on BIM technology
Abstract:
In order to overcome the problems of large energy consumption control error and low control efficiency in traditional energy consumption control methods, a new energy consumption control method based on BIM technology is proposed in this paper. In this method, RSstudio data mining software is used to mine the energy consumption data of green buildings in CBECS building energy consumption information database to fill the data shortage. Using the orthogonal test method and building information simulation software to analyse the significance level of energy consumption of green building, simulate the energy consumption of green building, based on BIM technology, and implement the integrated design of energy consumption control of green building, in order to achieve the energy consumption control of green building. The experimental results show that the proposed energy consumption control method has lower control error and higher control efficiency, and the maximum control error is only 0.44.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 399-414
Issue: 3
Volume: 40
Year: 2022
Keywords: BIM technology; green building; energy consumption control; energy consumption simulation.
File-URL: http://www.inderscience.com/link.php?id=122248
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:399-414
Template-Type: ReDIF-Article 1.0
Author-Name: Ling-min Yang
Author-X-Name-First: Ling-min
Author-X-Name-Last: Yang
Author-Name: Zhong-min Tang
Author-X-Name-First: Zhong-min
Author-X-Name-Last: Tang
Author-Name: Si-jun Liu
Author-X-Name-First: Si-jun
Author-X-Name-Last: Liu
Title: Research on optimisation method for project site selection based on improved genetic algorithm
Abstract:
In order to overcome the problems of low correlation between location impact index and target project, and low customer satisfaction in current research methods of project location, an optimisation method of project location based on improved genetic algorithm is proposed and designed. Collect the data needed for project site selection and integrate relevant data efficiently, and build the framework structure of project site selection. According to the evaluation index of project location, the existing genetic algorithm is improved. The improved genetic algorithm is applied to the optimisation of project location, and the eigenvalues and correlation factors of project location are optimised to realise the optimisation of project location. The experimental results show that the fit degree between the proposed method and the target project is between 0.9-1.0, and the user satisfaction is between 95%-99%, which proves that the proposed method has good robustness.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 309-324
Issue: 3
Volume: 40
Year: 2022
Keywords: improving genetic algorithm; project location; optimising method.
File-URL: http://www.inderscience.com/link.php?id=122260
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:309-324
Template-Type: ReDIF-Article 1.0
Author-Name: Nitin Panwar
Author-X-Name-First: Nitin
Author-X-Name-Last: Panwar
Author-Name: Sanjeev Kumar
Author-X-Name-First: Sanjeev
Author-X-Name-Last: Kumar
Title: Availability analysis using Markovian approach and maintenance planning of a process industry
Abstract:
In the present paper, a probabilistic method for stochastic modelling and performance evaluation of a pulping unit is suggested. The paper plant consists of various units like feeding, pulping system, bleaching system, screening system and paper production system. Pulping unit is one of the paper plant's most significant functional units, consisting of five repairable subsystems which are arranged in series. Using Markov process, differential equations are created after drawing transition diagram and these models are then used to discover the pulping unit's availability by considering the repair and failure information acquired from maintenance personnel. Based upon the various performance values for critical system using analytic hierarchy process (AHP), the priority weights of the considered criteria are found and ranking of failure causes are performed using vlse kriterijumska optimizacija kompromisno resenje (VIKOR) to find the most critical component.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 277-294
Issue: 3
Volume: 41
Year: 2022
Keywords: Markovian; stochastic modelling; multi-criteria decision making; MCDM; availability; AHP-VIKOR; maintenance planning.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:3:p:277-294
Template-Type: ReDIF-Article 1.0
Author-Name: Chuan He
Author-X-Name-First: Chuan
Author-X-Name-Last: He
Author-Name: Jin Lin
Author-X-Name-First: Jin
Author-X-Name-Last: Lin
Author-Name: Xin Xiang
Author-X-Name-First: Xin
Author-X-Name-Last: Xiang
Author-Name: Lie Yu
Author-X-Name-First: Lie
Author-X-Name-Last: Yu
Author-Name: Hui-hua Xiong
Author-X-Name-First: Hui-hua
Author-X-Name-Last: Xiong
Title: Design of energy consumption monitoring system of public buildings based on artificial neural network
Abstract:
In order to overcome the problems of low monitoring accuracy and long response time in traditional energy consumption monitoring system of public buildings, a new energy consumption monitoring system of public buildings based on artificial neural network is proposed. The system hardware is designed by using the energy consumption collection subsystem and energy consumption data transmission subsystem of public buildings. Through the genetic algorithm to optimise the constraint parameters of the physical sign extraction function to obtain the characteristics of public building energy consumption, combined with the main factors affecting the building energy consumption, the public building energy consumption monitoring model based on artificial neural network is established, and the real-time monitoring of public building energy consumption is realised through the model. The experimental results show that, compared with the traditional monitoring system, the minimum monitoring error of the designed system is only 0.01.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 349-362
Issue: 3
Volume: 41
Year: 2022
Keywords: artificial neural network; public building; energy consumption monitoring system; genetic algorithm.
File-URL: http://www.inderscience.com/link.php?id=124062
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:3:p:349-362
Template-Type: ReDIF-Article 1.0
Author-Name: Xiaowei Lin
Author-X-Name-First: Xiaowei
Author-X-Name-Last: Lin
Author-Name: Yaqin Peng
Author-X-Name-First: Yaqin
Author-X-Name-Last: Peng
Title: Research on the early warning system of regional financial risk
Abstract:
It is a systematic research work to design the early warning system of regional financial risk. This paper selects a total of 17 regional financial risk early warning indicators from the aspects of external macro-impact, regional macro-economic and regional micro-finance. The paper then uses the mapping method, GRITIC method and comprehensive scoring method to deal with the index standardisation, index weight and comprehensive risk measurement respectively, and construct the regional financial risk early warning system. Based on the empirical research of Fujian Province's actual data, the results show that there are implied fluctuations in the overall stability of regional finance in Fujian Province from 2013 to 2017, but some important early warning indicators still have different levels of risk. Finally, according to the early warning results of Fujian Province, the targeted financial risk prevention measures are put forward.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 404-415
Issue: 3
Volume: 41
Year: 2022
Keywords: regional financial risk; early warning system; mapping treatment; GRITIC method.
File-URL: http://www.inderscience.com/link.php?id=124063
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:3:p:404-415
Template-Type: ReDIF-Article 1.0
Author-Name: Osama T. Al Meanazel
Author-X-Name-First: Osama T. Al
Author-X-Name-Last: Meanazel
Author-Name: Haitham F. Dowiri
Author-X-Name-First: Haitham F.
Author-X-Name-Last: Dowiri
Author-Name: Hesham Ahmad Al-Momani
Author-X-Name-First: Hesham Ahmad
Author-X-Name-Last: Al-Momani
Title: Patient safety culture in Al Zarqa public hospital: case study
Abstract:
Patient safety concerns vary among healthcare provider settings, cultures of countries, policies and available resources. The primary purpose of this study is to analyse and establish a baseline assessment of the patient safety culture in Al Zarqa governorate hospitals. Hospitalised patients need to receive appropriate and high-quality treatment recommended in accordance with the latest professional knowledge. This study was conducted at two hospitals in Al Zarqa City, Prince Faisal Hospital (Prince Faisal Bin Al-Hussein Hospital) and Al Zarqa New Hospital (Al Zarqa Governmental Hospital). The total number of the participant was 131 from hospitals from 14 departments (59% from Al Zarqa New Hospital and 41% from Prince Faisal Hospital). The results of this study suggest that patient safety culture in Al Zarqa public hospitals needs more attention. The majority of the participants neither agreed nor disagreed on most of the points survey. However, they reported certain events that compromised safety, and at times having communicated with the hospitals about safety issues. Patient safety issues vary according to the setting, local culture, and available resources.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 336-348
Issue: 3
Volume: 41
Year: 2022
Keywords: patient safety culture; PSC; human safety; quality; healthcare; safety; patient culture.
File-URL: http://www.inderscience.com/link.php?id=124064
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:3:p:336-348
Template-Type: ReDIF-Article 1.0
Author-Name: Varthini Rajagopal
Author-X-Name-First: Varthini
Author-X-Name-Last: Rajagopal
Author-Name: Shanmugam Prasanna Venkatesan
Author-X-Name-First: Shanmugam Prasanna
Author-X-Name-Last: Venkatesan
Author-Name: Usha Mohan
Author-X-Name-First: Usha
Author-X-Name-Last: Mohan
Author-Name: Rishabh Gaur
Author-X-Name-First: Rishabh
Author-X-Name-Last: Gaur
Author-Name: Shubham Jha
Author-X-Name-First: Shubham
Author-X-Name-Last: Jha
Title: Analysing the supply chain network reconfiguration under disruption risk environment
Abstract:
A <i>p</i>-robust supply chain network (SCN) reconfiguration model under disruptions in dynamic mid-term horizon considering decision-maker (DM)'s risk-attitude is presented. Reconfiguration of SCN within a time horizon by utilising excess resources of undisrupted facilities, outsourcing and capacity expansion is studied. At first, the single-objective cost minimisation problem is formulated and extended as a multi-objective problem incorporating responsiveness as another objective. Pareto solutions are obtained using augmented ε-constraint (AUGMECON) method. The major inferences include: 1) the cost minimisation model opens a fewer facility under nominal condition and prefers capacity expansion strategy under disruptions; 2) the inclusion of responsiveness objective results in opening more facilities with outsourcing as preferred reactive strategy; 3) DM's attitude significantly affect structural decisions but not the parametric decisions such as capacity expansion, material flow redirection, and outsourcing; 4) a neutral DM selects a dispersed and diversified portfolio of facilities, whereas averse DM opens backup facilities closer to critical facilities.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 295-335
Issue: 3
Volume: 41
Year: 2022
Keywords: dynamic configuration; disruption; reactive mitigation strategies; risk-attitude; responsiveness; AUGMECON.
File-URL: http://www.inderscience.com/link.php?id=124065
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:3:p:295-335
Template-Type: ReDIF-Article 1.0
Author-Name: Shiyong Liu
Author-X-Name-First: Shiyong
Author-X-Name-Last: Liu
Author-Name: Sang Fu
Author-X-Name-First: Sang
Author-X-Name-Last: Fu
Title: Construction of a prediction model for individual investors' psychology and behaviour based on cognitive neuroscience
Abstract:
Traditional forecasting models cannot extract the trend information of retail investors' multi-scale psychological and behavioural data, and the predictions are not accurate. To solve this problem, a Markov-based individual investor psychology and behaviour prediction model is proposed. Using the wavelet multi-scale analysis method, the multi-scale data of individual investor's psychology and behaviour are extracted. A long-term-memory analysis is performed on multi-scale data of individual investors' psychology and behaviour using the correlation analysis method, and the trend information is extracted. On this basis, a Markov prediction model is established, and a modified investment preference model is introduced to improve the accuracy of the prediction. Using the individual similarity degree, the nearest neighbour set of the target individual is established, and a multi-order predictive Markov fusion model for multiple individuals is formed to achieve accurate prediction. The experimental results show that the proposed model achieves better nonlinear fitting and higher prediction accuracy.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 292-308
Issue: 3
Volume: 40
Year: 2022
Keywords: individual investors; psychology and behaviour; prediction model; Markov.
File-URL: http://www.inderscience.com/link.php?id=122275
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:3:p:292-308
Template-Type: ReDIF-Article 1.0
Author-Name: Akram Kohansal
Author-X-Name-First: Akram
Author-X-Name-Last: Kohansal
Author-Name: Shirin Shoaee
Author-X-Name-First: Shirin
Author-X-Name-Last: Shoaee
Author-Name: Mohammad Z. Raqab
Author-X-Name-First: Mohammad Z.
Author-X-Name-Last: Raqab
Title: Estimating the stress-strength parameter in multi-component systems based on adaptive hybrid progressive censoring
Abstract:
Under different probability distributions, numerous authors have discussed the estimation of the reliability in a stress-strength model. In this study, we investigate the reliability parameter estimation in multi-component stress-strength models based on the adaptive hybrid progressive censored sample of two-parameter Kumaraswamy distribution in various situations. In this regard, various methods such as the maximum likelihood, approximate maximum likelihood, Lindley's Bayesian, and Metropolis-Hastings methods are used to estimate the reliability parameter in this structure. Furthermore, the corresponding confidence intervals, bootstrap confidence intervals, and highest posterior density credible intervals of the multi-component reliability parameter are then established. Also, simulation studies are represented to evaluate and compare the performance of the proposed methods and one practical dataset to analyse illustrative purposes.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 363-403
Issue: 3
Volume: 41
Year: 2022
Keywords: adaptive type-II hybrid censored sample; Bayesian estimation; Kumaraswamy distribution; Monte Carlo simulation; multi-component stress-strength model; progressive censored sample.
File-URL: http://www.inderscience.com/link.php?id=124069
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:3:p:363-403
Template-Type: ReDIF-Article 1.0
Author-Name: Boxuan Zhao
Author-X-Name-First: Boxuan
Author-X-Name-Last: Zhao
Author-Name: Jiao Zhao
Author-X-Name-First: Jiao
Author-X-Name-Last: Zhao
Author-Name: Yulei Gu
Author-X-Name-First: Yulei
Author-X-Name-Last: Gu
Author-Name: Jingshuai Yang
Author-X-Name-First: Jingshuai
Author-X-Name-Last: Yang
Title: A multi-strategy integration Pareto-based artificial colony algorithm for multi-objective flexible job shop scheduling problem with the earliness and tardiness criterion
Abstract:
This paper studies the multi-objective flexible job shop scheduling problem with the earliness and tardiness (E%T) criterion, explores the decoding and search strategies of algorithms under the coexistence of the mean E%T and makespan, and provides a makespan-constrainted three-phase decoding mechanism and local search strategies for both of them. Referencing to the flexibility of the artificial bee colony algorithm framework, multiple strategies are integrated properly in the algorithm to realise simultaneous optimisation of regular and irregular objectives. Through testing six benchmark instances of different scales with tight or loose delivery time for jobs, the distribution characteristics of the Pareto optimal solution set of the collaborative optimisation of the mean E%T and the makespan are explored. The proper integration of various search strategies can make the proposed algorithm have better performance.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 182-205
Issue: 2
Volume: 41
Year: 2022
Keywords: flexible job shop scheduling; just-in-time delivery; earliness and tardiness; E%T; multi-objective; artificial bee colony.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:182-205
Template-Type: ReDIF-Article 1.0
Author-Name: Hadi Zarea
Author-X-Name-First: Hadi
Author-X-Name-Last: Zarea
Author-Name: Zhan Su
Author-X-Name-First: Zhan
Author-X-Name-Last: Su
Author-Name: Hooman Abdollahi
Author-X-Name-First: Hooman
Author-X-Name-Last: Abdollahi
Title: Social commerce constructs and consumers' purchase intention from minimalist brands
Abstract:
The social media and online communities have established new platforms for e-commerce by engaging both consumers and corporations in producing new product or services. Moreover, individuals' interaction on the cyberspace has evolved e-commerce towards social commerce. On the other hand, business incorporations have found the use of minimalism application in designing, which removes unnecessary aspects, attracts more audience. Therefore, drawing on literature the authors propound a new adopted model to portray a more transparent vision of social commerce. To examine the relationships among the model constructs, an empirical study was organised for this purpose; a survey was designed. In doing so, structural equation modelling (SEM) methodology has been used with Smart PLS 3 software in order to confirm or reject assumptions in the present study and is employed to gauge the proposed model.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 221-236
Issue: 2
Volume: 41
Year: 2022
Keywords: social commerce construct; trust; purchase intention; minimalist brand; brand loyalty.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:221-236
Template-Type: ReDIF-Article 1.0
Author-Name: Ibrahim Garbie
Author-X-Name-First: Ibrahim
Author-X-Name-Last: Garbie
Author-Name: Abdelrahman Garbie
Author-X-Name-First: Abdelrahman
Author-X-Name-Last: Garbie
Title: A holistic perspective of the sustainable manufacturing: a novel conceptual approach
Abstract:
Sustainability is recently considered the buzzword in manufacturing environments. Analysis and investigation of sustainability in manufacturing becomes urgent not only from one stream but also from the whole manufacturing streams. The main goal of this paper is to explain how to classify sustainability in all streams of manufacturing as a whole (machine components design, manufacturing processes and manufacturing systems) through identifying the sustainability enablers. A framework to analyse the whole manufacturing streams will be illustrated and discussed to identify which enablers are significant in each manufacturing stream and which manufacturing stream is more significant towards whole manufacturing sustainability than others. A novel assessment for measuring the manufacturing sustainability will be presented. It seemed that the stream of the manufacturing system represented the highest turbulent one due to the diversity and numerous sustainable enablers. It was also observed from this analysis and investigation that understanding sustainable manufacturing as a whole is a comprehensive task and it is recommended as one of major pillars towards the Industry 4.0.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 135-167
Issue: 2
Volume: 41
Year: 2022
Keywords: sustainable manufacturing; sustainability/sustainable development; manufacturing process; manufacturing systems; machine design.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:135-167
Template-Type: ReDIF-Article 1.0
Author-Name: Nita P.A. Hidayat
Author-X-Name-First: Nita P.A.
Author-X-Name-Last: Hidayat
Author-Name: Andi Cakravastia
Author-X-Name-First: Andi
Author-X-Name-Last: Cakravastia
Author-Name: Wisnu Aribowo
Author-X-Name-First: Wisnu
Author-X-Name-Last: Aribowo
Author-Name: Abdul Hakim Halim
Author-X-Name-First: Abdul Hakim
Author-X-Name-Last: Halim
Title: A single-stage batch scheduling model with m heterogeneous batch processors producing multiple items parts demanded at different due dates
Abstract:
This research deals with a batch scheduling problem to minimise total actual flowtime of parts through the shop with <i>m</i> heterogeneous batch processors, i.e., the machine simultaneously processing all parts in a batch. The parts to be processed are multiple items, and the completed parts must be delivered at different due dates. The total actual flow time of parts can be defined as an interval between arrival times of the parts and their respective due dates. The objective of minimising the total actual flowtime is not only to satisfy the due dates as a commitment to the customers, but also to minimise the length of total time spent by the parts in the shop. The problem is formulated as a mathematical model and an algorithm to solve the problem is proposed. Numerical examples show that the proposed algorithm can effectively solve the problem.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 254-275
Issue: 2
Volume: 41
Year: 2022
Keywords: batch scheduling; batch processor; actual flowtime.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:254-275
Template-Type: ReDIF-Article 1.0
Author-Name: Xi Chen
Author-X-Name-First: Xi
Author-X-Name-Last: Chen
Author-Name: Jieru Wang
Author-X-Name-First: Jieru
Author-X-Name-Last: Wang
Title: Accurate medical information recommendation system based on big data analysis
Abstract:
In order to solve the problems of low recommendation accuracy and long response time in traditional medical information recommendation system, a medical information accurate-recommendation system based on big data analysis is proposed. The system is designed as medical information data acquisition module, medical information storage module and medical information accurate-recommendation module. In the medical information data acquisition module, crawler technology is used to obtain medical information data, and association rule algorithm is used to mine the medical information data. In the medical information storage module, personalised configuration is set. In the medical information accurate-recommendation module, the user interest model is quantified by vector space method, and BP algorithm and SOM algorithm are introduced to complete the accuracy of medical information recommend. The experimental results show that: the highest accuracy rate of medical information recommendation is 98.8%, and the shortest retrieval response time is 20 ms.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 237-253
Issue: 2
Volume: 41
Year: 2022
Keywords: big data technology; medical information; preprocessing; accurate recommendation.
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:237-253
Template-Type: ReDIF-Article 1.0
Author-Name: Mohsen Fayyazi
Author-X-Name-First: Mohsen
Author-X-Name-Last: Fayyazi
Author-Name: Siamak Haji Yakhchali
Author-X-Name-First: Siamak Haji
Author-X-Name-Last: Yakhchali
Author-Name: Mir Saman Pishvaee
Author-X-Name-First: Mir Saman
Author-X-Name-Last: Pishvaee
Author-Name: Fariborz Jolai
Author-X-Name-First: Fariborz
Author-X-Name-Last: Jolai
Title: A forward modelling approach to optimise the portfolio of projects among oil companies under uncertainty: a reactive two-stage stochastic model
Abstract:
Because of high volatility in oil price, oil companies should change their strategies along with changing oil prices. Thus, dynamic portfolio management is strongly recommended to increase the rate of oil production and determine resource allocation for projects in each period of the planning horizon. To achieving the objective, a two-stage stochastic mathematical model is developed to optimise the portfolio of oil projects. To make the model more realistic, splitting the projects and their resumption are permitted. To solve the model, a robust optimisation approach is designed, and the results of the robust and two-stage stochastic designs are compared. These comparisons are based on a realisation algorithm developed by this study. To illustrate the capability and power of the stochastic model in handling the uncertainty, a case study on an oil company is presented.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 427-451
Issue: 4
Volume: 42
Year: 2022
Keywords: portfolio management; resource assignment; project scheduling; stochastic programming; robust optimisation.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:4:p:427-451
Template-Type: ReDIF-Article 1.0
Author-Name: Daniela Contreras
Author-X-Name-First: Daniela
Author-X-Name-Last: Contreras
Author-Name: Rodrigo Linfati
Author-X-Name-First: Rodrigo
Author-X-Name-Last: Linfati
Author-Name: John Willmer Escobar
Author-X-Name-First: John Willmer
Author-X-Name-Last: Escobar
Title: A model-based decision framework for the multi-depot multi-travelling salesman problem with split and delivery demand considering different key performance indicators
Abstract:
This paper introduces the multi-depot multi-travelling salesman problem with split and delivery demand (M<i>m</i>TSP-SD). The problem has been formulated as a flexible optimisation model that considers four key performance indicators (KPIs): the minimisation of the route distance, the minimum daily demand to satisfy similar demand between crews, and the equivalent kilometres travelled between crews. The efficiency of the proposed approach has been tested in three types of instances adapted from a green area maintenance company dedicated to the management of any vegetation, cutting grass or weeds and/or collecting leaves, watering, or fertilising, among many other services. The results confirm the efficiency of the proposed approach and the positive impact in determining the different performance measures that are considered.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 478-498
Issue: 4
Volume: 42
Year: 2022
Keywords: multi-travelling salesman problem; m-TSP; balance of travellers; key performance indicator; KPI; MmTSP-SD; visit planning; mixed-integer linear programming.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:4:p:478-498
Template-Type: ReDIF-Article 1.0
Author-Name: Meghdad Haji Mohammad Ali Jahromi
Author-X-Name-First: Meghdad Haji Mohammad Ali
Author-X-Name-Last: Jahromi
Author-Name: Ali Nazeri
Author-X-Name-First: Ali
Author-X-Name-Last: Nazeri
Author-Name: Ehsan Ghorbani
Author-X-Name-First: Ehsan
Author-X-Name-Last: Ghorbani
Title: Goal programming approach for agile sustainable pharmaceutical supply chain
Abstract:
In this paper, a pharmaceutical supply chain network with four levels including suppliers, major distributors, retailers and customers was considered and in order to have agility and sustainability benefits simultaneously, goal programming approach has been used. In fact, an optimum structure regarding sustainable aspects of supply chain in light of economic, social, environmental and political aspects (i.e., as important aspects in the current situation) were designed. Also, for this purpose, a digraph corresponded to a feasible structure under real situation of pharmaceutical supply chain was considered, and then with help of goal programming approach, an optimum configuration, which is a sub-digraph from the main, will be achieved. Results show that the model has high capability to configure pharmaceutical chain according to expectations of the managers and experts of the chain.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 499-515
Issue: 4
Volume: 42
Year: 2022
Keywords: sustainable supply chain; goal programming; pharmaceutical supply chain.
File-URL: http://www.inderscience.com/link.php?id=127420
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:4:p:499-515
Template-Type: ReDIF-Article 1.0
Author-Name: Sara S. Moosavi
Author-X-Name-First: Sara S.
Author-X-Name-Last: Moosavi
Author-Name: Amir T. Payandeh Najafabadi
Author-X-Name-First: Amir T. Payandeh
Author-X-Name-Last: Najafabadi
Title: Pricing of variable long-term care annuities with guaranteed lifetime withdrawal and limited hospitalisation coverage benefits
Abstract:
Improvements in medical technology and longevity risk increase the popularity of healthcare insurance products. This article combines several well-known healthcare products and develops a theoretical model for a variable annuity product with some specific benefits. More precisely, the new product is a variable annuity product that accompanies with long-term care coverage, limited hospitalisation coverage and a guaranteed lifelong withdrawal benefit option. Under a non-arbitrage market (the geometric Brownian motion) investment, the fair lam sum premium of such insurance products has been evaluated. Using an MCMC simulation method, a numerical study has been conducted to illustrate the capability of the product.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 168-181
Issue: 2
Volume: 41
Year: 2022
Keywords: variable annuity; long-term care; life care annuity; guaranteed lifetime withdrawal benefit; hospitalisation coverage.
File-URL: http://www.inderscience.com/link.php?id=123581
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:168-181
Template-Type: ReDIF-Article 1.0
Author-Name: Youkyung Won
Author-X-Name-First: Youkyung
Author-X-Name-Last: Won
Title: PMP approach for solving the binary static multi-objective generalised cell formation problem
Abstract:
The <i>p</i>-median problem (PMP) approach has been used as an effective alternative for solving small-to-medium-sized single-objective cell formation (SOCF) problems. Cell load balancing is an important consideration in multi-objective cell formation (MOCF) problems for reflecting realistic manufacturing factors. However, few cell formation (CF) studies using the conventional PMP approach with the binary machine-part incidence matrix (MPIM) alone have considered multiple objectives including cell load balancing because the conventional binary MPIM can only indicate whether parts are processed on particular machines. In this study, we emphasise the importance of cell load balancing even in binary MPIM-based multi-objective generalised cell formation (MOGCF) problems with alternative process plans for parts and demonstrate that the binary MPIM-based CF without consideration of cell load balancing can lead to inferior solutions. This study shows that the PMP approach can effectively solve large-sized MOGCF problems by considering the minimisation of cell load imbalance and inter-cellular part moves, which result in inefficient cells. Our PMP approach first solves the SOCF problem and then attempts to satisfy conflicting multiple objectives <i>ex post facto</i> with a subsequent heuristic procedure. The computational results show that the proposed PMP approach is very effective for large-sized MOGCF problems.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 516-544
Issue: 4
Volume: 42
Year: 2022
Keywords: PMP approach; generalised multi-objective cell formation; cell load balancing.
File-URL: http://www.inderscience.com/link.php?id=127421
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:4:p:516-544
Template-Type: ReDIF-Article 1.0
Author-Name: Ngwenya Andries Rakobela
Author-X-Name-First: Ngwenya Andries
Author-X-Name-Last: Rakobela
Author-Name: Michael Kweneojo O. Ayomoh
Author-X-Name-First: Michael Kweneojo O.
Author-X-Name-Last: Ayomoh
Author-Name: Thinandahva Thomas Munyai
Author-X-Name-First: Thinandahva Thomas
Author-X-Name-Last: Munyai
Author-Name: Kgashane Stephen Nyakala
Author-X-Name-First: Kgashane Stephen
Author-X-Name-Last: Nyakala
Title: Productivity enhancement in caravan manufacturing: an organisational resource centric approach
Abstract:
This paper has identified organisational factors and resources that contribute to low productivity and poor quality in caravan manufacturing. Eight productivity-enhancing factors directly linked to caravan manufacturing process were identified and a framework to enhance productivity of caravan manufacturing was proposed. The dataset utilised in this research was obtained from a qualitative data gathering process premised on system observation. The supplier input process output customer (SIPOC) and value stream mapping (VSM) were both utilised to assess the current 'as-is' productivity level of the case-study system. The same tools were deployed for identification of waste generating processes in the system, conduct of analysis for reduction of work in progress inventory and lead times associated with non-value adding activities. The analysis conducted herein was carried out through content and comparative analysis methods using MS Excel 2013 software while the causes and effect matrix was used for data measurement on a prescribed rating scale.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 409-426
Issue: 4
Volume: 42
Year: 2022
Keywords: caravan manufacturing; organisational resources; productivity; quality enhancement.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:4:p:409-426
Template-Type: ReDIF-Article 1.0
Author-Name: P. Valarmathi
Author-X-Name-First: P.
Author-X-Name-Last: Valarmathi
Author-Name: R. Dhanalakshmi
Author-X-Name-First: R.
Author-X-Name-Last: Dhanalakshmi
Author-Name: Narendran Rajagopalan
Author-X-Name-First: Narendran
Author-X-Name-Last: Rajagopalan
Author-Name: Bam Bahadur Sinha
Author-X-Name-First: Bam Bahadur
Author-X-Name-Last: Sinha
Title: Diversification-oriented accuracy prediction in recommender systems
Abstract:
Tremendous amount of data generated by e-commerce users on items (e.g., purchase or rating history), sets some key challenges for the online knowledge discovery scheme. Recommendation systems are an important element of the digital marketplace such as e-stores and service providers that use the generated information to discover preferred products of the consumers. Developing an effective recommender system that produces diverse suggestions without compromising the precision of the customised list is challenging for online systems. This paper aims at diversifying recommendation by integrating graph-based algorithm supported with significant nearest neighbour strategy for enhancing recommendation precision. The experimental efficacy on the 100K dataset of MovieLens shows that the proposed hybrid model has a strong coverage and superior efficiency in product recommendations.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 206-220
Issue: 2
Volume: 41
Year: 2022
Keywords: e-commerce; significant nearest neighbour; SNN; graph-based algorithm; GBA; diversification; coverage; MovieLens.
File-URL: http://www.inderscience.com/link.php?id=123583
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Handle: RePEc:ids:ijisen:v:41:y:2022:i:2:p:206-220
Template-Type: ReDIF-Article 1.0
Author-Name: Diva Kurnianingtyas
Author-X-Name-First: Diva
Author-X-Name-Last: Kurnianingtyas
Author-Name: Budi Santosa
Author-X-Name-First: Budi
Author-X-Name-Last: Santosa
Author-Name: Nurhadi Siswanto
Author-X-Name-First: Nurhadi
Author-X-Name-Last: Siswanto
Title: A system dynamic to reforming of the healthcare sector in the Indonesian National Health Insurance System Program
Abstract:
National Health Insurance System (NHIS) was established by the Indonesian Government to ensure the health needs of its people. However, the programme encountered many obstacles due to inefficiencies caused by changes in people's behaviour. The aim is to identify key factors, evaluate and plan further policies using Indonesian data from 2014 to 2018. The system's dynamics approach is used to build a model for determining policy alternatives that only focuses on referral reform and limiting health service coverage. The proposed model was proven correct and then implemented in 2019 to plan a policy solution. The result was limiting healthcare coverage as a short-term strategy, whereas changing tiered referrals to combined referrals could be considered a long-term strategy. However, the success of this strategy will only occur if there is good collaboration between health services and regulations. In addition, it is necessary to improve the structure of healthcare.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 452-477
Issue: 4
Volume: 42
Year: 2022
Keywords: system dynamics; simulation; National Health Insurance System; NHIS; patient referral mechanism; financial strategy.
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Handle: RePEc:ids:ijisen:v:42:y:2022:i:4:p:452-477
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Author-Name: Dheeraj Nimawat
Author-X-Name-First: Dheeraj
Author-X-Name-Last: Nimawat
Author-Name: B.D. Gidwani
Author-X-Name-First: B.D.
Author-X-Name-Last: Gidwani
Title: An overview of Industry 4.0 in manufacturing industries
Abstract:
In the current scenario, manufacturing industries are rapidly moving towards customised production instead of mass production, to meet the current market competition. Industry 4.0 prompts the digitalisation time. Industry 4.0 emphasises intelligent products, potential customers, and change of industrial machine suits. The whole thing is digital; manufacturing systems, business models, machines, working and demand environments, products, and operators. It is interconnected inside the advanced and innovative view with the comparing virtual portrayal. The new Industrial Revolution carries significant changes to companies that should adjust their machines, frameworks, and workers' abilities to continue their business in an extremely competitive market. Industry 4.0 inventiveness has engaged an impressive concentration of industries and researchers. This paper comprises of 164 reputed research papers and addresses evolution of Industry 4.0, key technologies, initiatives by various nations in this era, review of empirical analysis on Industry 4.0, and presented a future scope in the area of Industry 4.0 regarding survey of barriers to adopt Industry 4.0, maturity of Industry 4.0 concept, and impact of key technologies of Industry 4.0 in the today's scenario. This paper will help to the existing and future industries, and researchers in the context of Industry 4.0.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 415-454
Issue: 4
Volume: 40
Year: 2022
Keywords: Industry 4.0; big data; autonomous robots; simulation; additive manufacturing; industrial internet of things; IIoT; augmented reality; cyber-physical systems; CPS; fourth Industrial Revolution.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:415-454
Template-Type: ReDIF-Article 1.0
Author-Name: Leena Ghrayeb
Author-X-Name-First: Leena
Author-X-Name-Last: Ghrayeb
Author-Name: Shanthi Muthuswamy
Author-X-Name-First: Shanthi
Author-X-Name-Last: Muthuswamy
Author-Name: Purushothaman Damodaran
Author-X-Name-First: Purushothaman
Author-X-Name-Last: Damodaran
Title: Minimising makespan of batch processing machine with unequal ready times
Abstract:
This research considers scheduling a single batch processing machine at a contract electronics manufacturer. The processing times, ready times and the sizes of the jobs are given and the total size of the batch should not exceed the machine capacity. The batch ready time is equal to the latest ready time of all the jobs in the batch. The objective is to minimise the makespan. The commercial solver used to solve the mathematical formulation proposed requires long run times. Consequently, several heuristics and lower bounding procedures are proposed. Through an experimental study, it is shown that one of the lower bounds is within 40% of the best known integer solution from CPLEX for the 200-job instances. The heuristics are very effective in finding good quality solutions with short run times. For smaller problem instances, the quality of the heuristic solution is within 10% of the best known solution from CPLEX.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 496-512
Issue: 4
Volume: 40
Year: 2022
Keywords: batch processing machine; BPM; scheduling; makespan; heuristics; lower bound.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:496-512
Template-Type: ReDIF-Article 1.0
Author-Name: Santha Raja Kumari Upadhyayula
Author-X-Name-First: Santha Raja Kumari
Author-X-Name-Last: Upadhyayula
Author-Name: Shanthi Muthuswamy
Author-X-Name-First: Shanthi
Author-X-Name-Last: Muthuswamy
Author-Name: Purushothaman Damodaran
Author-X-Name-First: Purushothaman
Author-X-Name-Last: Damodaran
Title: A simulated annealing approach to minimise makespan in a hybrid flowshop with a batch processing machine
Abstract:
A two-stage hybrid flowshop with a batch processing machine (BPM) in stage 1 and a set of discrete processing machines in stage 2 is considered in this research. Job sizes and their processing times are given. The BPM can process multiple jobs simultaneously as long as the total size of all jobs does not exceed its capacity, and the processing time is dictated by the longest processing job in the batch. In stage 2, the jobs have to be processed one at a time. The objective is to minimise the makespan. As the problem under study is NP-hard, a simulated annealing (SA) algorithm was designed. A mathematical formulation was also developed and a commercial solver was used to solve the problem instances. An experimental study was conducted to compare SA with the solver. The study highlights the efficiency of SA in solving larger problem instances with good quality solution in shorter computational time.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 513-532
Issue: 4
Volume: 40
Year: 2022
Keywords: batch processing machines; BPMs; scheduling; hybrid flowshop; simulated annealing; makespan; heuristics.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:513-532
Template-Type: ReDIF-Article 1.0
Author-Name: Guanlin Chen
Author-X-Name-First: Guanlin
Author-X-Name-Last: Chen
Author-Name: Jiapeng Shen
Author-X-Name-First: Jiapeng
Author-X-Name-Last: Shen
Author-Name: Min Li
Author-X-Name-First: Min
Author-X-Name-Last: Li
Author-Name: Min Jiang
Author-X-Name-First: Min
Author-X-Name-Last: Jiang
Title: A novel urban road management system based on data mining
Abstract:
With the accelerating process of urbanisation in China, new problems and challenges have also emerged in the management of urban roads. In order to apply the data analysis technology to the above problems, we propose a combined forecasting model which can help us to forecast the number of daily cases that will happen in a region over the next few days. Our experimental results show that this model has better predictive ability than other models and can be applied to a variety of situations. What's more, in order to apply the model to real life, we also develop a novel urban road management system (NURMS) which realises some useful functions such as prediction of the number of daily cases, inquiry of daily cases, and statistical analysis of historical data. We believe our work will bring effective data support to the management of urban roads.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 472-483
Issue: 4
Volume: 40
Year: 2022
Keywords: data mining; support vector regression; SVR; back propagation; BP; ARIMA; urban road management.
File-URL: http://www.inderscience.com/link.php?id=122827
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:472-483
Template-Type: ReDIF-Article 1.0
Author-Name: Liu Kuiwu
Author-X-Name-First: Liu
Author-X-Name-Last: Kuiwu
Title: Research on high-speed motion control of green environmental protection production line for high-speed flexible cartridge packing
Abstract:
In order to overcome the poor track control performance of the production line motion control method, a high-speed motion control method of green environmental protection production line with high-speed flexible box packing is proposed. This method obtains the speed constraint conditions according to the speed connection between the path segments, carries out the speed preprocessing between the path segments, introduces the polynomial quintic interpolation algorithm plans, generates the motion trajectory, obtains the speed control curve of the production line, implements the path planning, constructs the high-speed motion control model of the production line, and realises the high-speed motion control of the production line. The experimental results show that the interruption of the trajectory control line is the smallest, the controller tends to be stable for 2 s, the packaging error can be controlled within ±0.4 mm, and the trajectory control performance is better than the traditional method.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 455-471
Issue: 4
Volume: 40
Year: 2022
Keywords: high-speed flexible cartridge; packing; green production line; high-speed motion control.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:455-471
Template-Type: ReDIF-Article 1.0
Author-Name: Yingwei Geng
Author-X-Name-First: Yingwei
Author-X-Name-Last: Geng
Title: Design of the autonomous learning system for students in remote open education based on MOOC
Abstract:
In order to realise the new education mode of students' autonomous learning and meet the learning needs of open education, this paper proposes the design of students' autonomous learning system based on MOOC. First of all, the embedded scheduling method is used to sample the students' information, the distance open education independent learning resources are used, and the sampling information and statistical average analysis method are used to control the students' autonomous learning mode in MOOC. Through the adaptive optimisation of machine learning, the autonomous learning system of students in distance open education is optimised and simulated. The result shows that this method has a good adaptive ability in distance open education, and effectively enhances the autonomous learning ability of distance education students.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 484-495
Issue: 4
Volume: 40
Year: 2022
Keywords: mass open online course; MOOC; remote open education; autonomous learning; system design.
File-URL: http://www.inderscience.com/link.php?id=122832
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:484-495
Template-Type: ReDIF-Article 1.0
Author-Name: Naveen Virmani
Author-X-Name-First: Naveen
Author-X-Name-Last: Virmani
Author-Name: Urmi Ravindra Salve
Author-X-Name-First: Urmi Ravindra
Author-X-Name-Last: Salve
Title: Assessment of human and system related barriers during implementation of green leagile Six Sigma in Indian manufacturing industries
Abstract:
There is a radical change in level of competition during past few years in manufacturing industries. Today, the customers desire high quality products at economical price and at in minimum span of time. So, it is required for industries to adopt manufacturing strategies in compliance with customer requirements and preferences. Also, there is a need of using greener and sustainable technologies to manufacture products. Therefore, it is imperative to produce economical products quickly while maintaining quality norms (ISO, OHSAS, etc.). For accomplishing these objectives, industries are required to adopt state-of-art technology, methods and research strategies to compete in the global market. In this paper, concept of green leagile Six Sigma has been discussed and human and system related barriers had been identified through literature review. EFA technique is used to categorise the attributes into constructs. CFA was used for model fit. Operational barrier is found to have profound effect in implementation of GLSS concept in the industries.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 157-180
Issue: 2
Volume: 40
Year: 2022
Keywords: green leagile Six Sigma; GLSS; agile; green; exploratory factor analysis; EFA; confirmatory factor analysis; CFA; lean; Six Sigma.
File-URL: http://www.inderscience.com/link.php?id=121044
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:2:p:157-180
Template-Type: ReDIF-Article 1.0
Author-Name: Amdework Gochel
Author-X-Name-First: Amdework
Author-X-Name-Last: Gochel
Author-Name: Sisay G. Gebeyehu
Author-X-Name-First: Sisay G.
Author-X-Name-Last: Gebeyehu
Author-Name: Muluken Abebe
Author-X-Name-First: Muluken
Author-X-Name-Last: Abebe
Title: Production lead time improvement through lean manufacturing
Abstract:
The study presents the application of a lean manufacturing system in Hibiret Manufacturing and Machine Building Industry (HMMBI). The aim of the research is to improve the production lead time by minimising non-value adding activities. Both qualitative and quantitative data are used. The movement of production activities is drawn by the spaghetti model. Value-added and non-value added activities are identified using value stream mapping (VSM). Minitab quality companion and SigmaXL tools are employed to draw VSM and generate the value of performance indicators respectively. After identifying the bottleneck areas, suggested measurements are taken. As a result, work in process time is reduced by 50.37 hours, waiting time reduced by 50.37 hour, process cycle efficiency is enhanced by 8.6% and the travel distance is reduced by 951 metres. Finally, production lead time is improved by 50.361 hours. Thus, it is concluded that the research has found a significant benefit for HMMBI and similar manufacturing industries.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 147-156
Issue: 2
Volume: 40
Year: 2022
Keywords: lead time; lean manufacturing; value stream map.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:2:p:147-156
Template-Type: ReDIF-Article 1.0
Author-Name: K.G. Durga Prasad
Author-X-Name-First: K.G. Durga
Author-X-Name-Last: Prasad
Author-Name: P. Krishna Murthy
Author-X-Name-First: P. Krishna
Author-X-Name-Last: Murthy
Author-Name: Ch. Hima Gireesh
Author-X-Name-First: Ch. Hima
Author-X-Name-Last: Gireesh
Author-Name: K.D.S. Sravani
Author-X-Name-First: K.D.S.
Author-X-Name-Last: Sravani
Title: Conceptual design of ergonomic food truck using QFD-GRA-DSM hybrid methodology - a case study
Abstract:
As the competition among the food truck business entrepreneurs is growing rapidly in India, food truck owners have to capture the tastes of the consumers from time to time, maintain trained staff for food preparation, create healthy, hygienic environment, ensure quality in service etc. In addition to these, the effective utilisation of limited kitchen space to meet all the requirements is essential. In this context, ergonomic intervention in designing kitchen space of the food truck is one of the prime considerations. In this paper, a methodology is developed by using quality function deployment (QFD), grey relational analysis (GRA) and design structure matrix (DSM) method for conceptual design of ergonomic food truck with a view to deploy the requirements of users in to the design of kitchen portion of the food truck. The proposed methodology is demonstrated through a case study in this paper.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 255-275
Issue: 2
Volume: 40
Year: 2022
Keywords: conceptual design of a product; ergonomics; food truck; quality function deployment; QFD; grey relational analysis; GRA; design structure matrix method.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:2:p:255-275
Template-Type: ReDIF-Article 1.0
Author-Name: Timothee Kombe
Author-X-Name-First: Timothee
Author-X-Name-Last: Kombe
Author-Name: Sandra Nzeneu
Author-X-Name-First: Sandra
Author-X-Name-Last: Nzeneu
Title: Prognosis of failures due to the abnormal temperature increase of the malt crusher, using ANFIS neuro-fuzzy approach: case study of the flour mill of the breweries of Cameroon
Abstract:
In this article, we present a method for predicting malt grinder failures. The objective is to control the evolution of the temperature of the grinding chamber, in order to optimise the availability and reliability of the grinder. The methodological approach is based on the ANFIS neuro-fuzzy network, which offers, in a single tool, precision for nonlinear systems. The predicted temperature is classified according to a mode of operation of the equipment. The evaluation of the performance of the prediction and classification systems is characterised respectively by a learning error function of 0.1236 and a classification rate of 79.6%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 228-254
Issue: 2
Volume: 40
Year: 2022
Keywords: artificial intelligence; hybrid neuro-fuzzy network; form recognition; failure; prognosis; Cameroon.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:2:p:228-254
Template-Type: ReDIF-Article 1.0
Author-Name: Aman Bhatnagar
Author-X-Name-First: Aman
Author-X-Name-Last: Bhatnagar
Author-Name: Ravi Shankar
Author-X-Name-First: Ravi
Author-X-Name-Last: Shankar
Author-Name: Prem Vrat
Author-X-Name-First: Prem
Author-X-Name-Last: Vrat
Title: Demand-supply planning and sustainability aspect for agro-based perishables in cold-chain
Abstract:
The primary objective of this paper is to: 1) determine the optimum storage requirements for agro-based perishables using production and distribution planning model to absorb the demand fluctuations in an economic manner, encouraging inter-state transportation of perishables so that available infrastructure is utilised efficiently; 2) determine the cost variation along the potato value chain from farm to fork; 3) analysing the cost of building cold storage; 4) focus on the sustainability aspect of cold-chain in order to have better utilisation of the cold storages and logistics, thereby reducing food loss and carbon footprints; 5) determine the payback period of the investment made, profit and loss (PnL), un-discounted rate of return, earnings before interest, taxes, and amortisation (EBITA) profit after tax (PAT), projected balance sheet and depreciation schedule. This paper investigates the usefulness and efficacy of the production and distribution planning in terms of meeting the growing demand of food across states, focusing on potato. It helps in designing a system and in developing operating decision rule to minimise the total system cost.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 79-103
Issue: 1
Volume: 40
Year: 2022
Keywords: cold-chain; cold storage; potato value-chain; agri-logistics.
File-URL: http://www.inderscience.com/link.php?id=120802
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:79-103
Template-Type: ReDIF-Article 1.0
Author-Name: Hagag Maher
Author-X-Name-First: Hagag
Author-X-Name-Last: Maher
Author-Name: Mohamed F. Aly
Author-X-Name-First: Mohamed F.
Author-X-Name-Last: Aly
Author-Name: Islam H. Afefy
Author-X-Name-First: Islam H.
Author-X-Name-Last: Afefy
Author-Name: Tamer F. Abdelmaguid
Author-X-Name-First: Tamer F.
Author-X-Name-Last: Abdelmaguid
Title: A maintenance optimisation approach based on genetic algorithm for multi-component systems considering the effect of human error
Abstract:
The total maintenance cost can be reduced by grouping maintenance actions of several components. This paper contributes to the existing literature by introducing an enhanced maintenance optimisation approach that considers the effect of maintenance crew loading due to grouping on the maintenance decisions of multi-component systems. A modified mathematical model is firstly developed for evaluating the failure probability function of each component, the remaining useful life and the maintenance cost. Economic and structural dependencies are taken into consideration. A simulation is secondly implemented to provide estimates of the associated costs with changes in the decision variables. Using the simulation model, an optimisation approach based on a genetic algorithm is thirdly developed to minimise the long-term mean maintenance cost per unit time. Computational results show that the proposed maintenance optimisation approach provides considerable maintenance cost savings and emphasises the importance of considering the effect of maintenance crew constraints in maintenance scheduling.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 51-78
Issue: 1
Volume: 40
Year: 2022
Keywords: maintenance grouping; multi-component systems; genetic algorithm; maintenance human constraints; maintenance process simulation.
File-URL: http://www.inderscience.com/link.php?id=120803
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:51-78
Template-Type: ReDIF-Article 1.0
Author-Name: Ibrahim Joseph Mwasubila
Author-X-Name-First: Ibrahim Joseph
Author-X-Name-Last: Mwasubila
Author-Name: Ismail W.R. Taifa
Author-X-Name-First: Ismail W.R.
Author-X-Name-Last: Taifa
Author-Name: Beatus A.T. Kundi
Author-X-Name-First: Beatus A.T.
Author-X-Name-Last: Kundi
Title: An analytical study on establishing strategies for improving the productivity of the spinning industries
Abstract:
Strategies for improving the productivity of the spinning industries are much needed. In this paper, a case of a spinning industry was systematically studied. The strategies for enhancing productivity were established through a mixed approach. The studied industry experienced low productivity as they were only achieving 55%-68% of their production plan. Also, their actual operational machine availability was 67%. The proposed strategies include improving the spooling and the drawing process by installing new machinery technology; improve raw materials and components flow; hiring well-trained workers; develop employee training programs; search for new market segments; establish effective information and communications technology section, and develop an implementable maintenance plan. The study also revealed that system dynamics modelling helps to arrange descriptive information analytically. Thus, Vensim® software was applied to illustrate the differences between productivity, specifically before and after implementing the established strategies. The study considered only a single industry and 'single-factor productivity measures'.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-28
Issue: 1
Volume: 40
Year: 2022
Keywords: productivity improvement; single-factor productivity; multifactor productivity measures; productivity index; strategies; competitive strategy; system dynamics; Vensim software; spinning mill.
File-URL: http://www.inderscience.com/link.php?id=120804
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:1-28
Template-Type: ReDIF-Article 1.0
Author-Name: Natalia Segura Rosas
Author-X-Name-First: Natalia Segura
Author-X-Name-Last: Rosas
Author-Name: John Willmer Escobar
Author-X-Name-First: John Willmer
Author-X-Name-Last: Escobar
Author-Name: Juan Camilo Paz
Author-X-Name-First: Juan Camilo
Author-X-Name-Last: Paz
Title: Optimisation of multi-objective supply chain networks considering cost minimisation and environmental criteria
Abstract:
This article considers the optimisation problem of a multi-objective mass-consumption supply chain network considering cost minimisation and environmental criteria, as well as the analysis of scenarios with variable demand. This study seeks to determine the closure and consolidation of distribution centres and the identification of product flows in the network. The efficiency of the mathematical model has been tested with real information obtained from a Colombian multinational company manufacturing products of mass-consumption. The results confirm the efficiency of the model and its positive impact on determining the environmental impact of gas emissions related to the type of transportation used and the appropriate cost for the case study company.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 126-146
Issue: 1
Volume: 40
Year: 2022
Keywords: network optimisation; multi-objective mathematical model; total cost; environmental impact; logistics; scenario analysis.
File-URL: http://www.inderscience.com/link.php?id=120805
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:126-146
Template-Type: ReDIF-Article 1.0
Author-Name: Lucas Schmidt Goecks
Author-X-Name-First: Lucas Schmidt
Author-X-Name-Last: Goecks
Author-Name: Taciana Mareth
Author-X-Name-First: Taciana
Author-X-Name-Last: Mareth
Author-Name: André Luis Korzenowski
Author-X-Name-First: André Luis
Author-X-Name-Last: Korzenowski
Author-Name: Jorge André Ribas Moraes
Author-X-Name-First: Jorge André Ribas
Author-X-Name-Last: Moraes
Author-Name: Elpidio Oscar Benitez Nara
Author-X-Name-First: Elpidio Oscar Benitez
Author-X-Name-Last: Nara
Title: Analytic hierarchy process as a decision-making tool for systematic layout planning, involving social responsibility criteria: a case study
Abstract:
Layout planning is a significant business problem for companies, it involves reducing inventories, lead time and space usage, making the plant adaptable to future changes, and providing a healthy, convenient, and secure environment for employees. In convergence with these goals, decision-making becomes a vital activity to reach a reasonable choice. In this way, this study aimed to analyse the contribution of the analytic hierarchy process (AHP) to systematic layout planning (SLP) as a method of layout planning for company managers, involving social responsibility criteria. Firstly, a technical study was performed presenting possibilities of layouts from the tools for SLP planning. Next, the best proposal was selected using the AHP. The results show that layouts 4 and 2 are the ones that best meet the needs of the company under analysis. Already, layouts 5 and 1, because they have a very long flow of materials, have shown inferior results.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 29-50
Issue: 1
Volume: 40
Year: 2022
Keywords: systematic layout planning; SLP; analytic hierarchy process; AHP; layout planning; social responsibility criteria.
File-URL: http://www.inderscience.com/link.php?id=120806
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:29-50
Template-Type: ReDIF-Article 1.0
Author-Name: Ke-jia Chen
Author-X-Name-First: Ke-jia
Author-X-Name-Last: Chen
Author-Name: Jin-Hua Zhang
Author-X-Name-First: Jin-Hua
Author-X-Name-Last: Zhang
Author-Name: Yi-xin Lan
Author-X-Name-First: Yi-xin
Author-X-Name-Last: Lan
Author-Name: Ping Chen
Author-X-Name-First: Ping
Author-X-Name-Last: Chen
Title: E-commerce logistics provider selection based on multi-criteria decision-making approach with uncertain information
Abstract:
Logistics provider selection is a multi-criteria decision-making problem faced by e-commerce companies. Considering the complexity of the problem and the uncertainty of the decision information, an integrated approach of GTOPSIS is proposed for evaluating and selecting the most suitable logistics provider. The GTOPSIS approach integrates the three-parameter interval grey number (T-PIGN) into the technique for order preference by similarity to ideal solution (TOPSIS). It allows decision-makers to use T-PIGN to represent the performance of the alternatives which can retain and utilise the original uncertain assessment information of alternatives to the greatest extent. Besides, the PERT distribution is adopted to weight the three parameters of T-PIGN. A real-life case study is presented to demonstrate the practicality and effectiveness of the GTOPSIS approach.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 104-125
Issue: 1
Volume: 40
Year: 2022
Keywords: multi-criteria decision-making; MCDM; logistics provider selection; interval grey number; TOPSIS.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:104-125
Template-Type: ReDIF-Article 1.0
Author-Name: Tseng-Chang Yen
Author-X-Name-First: Tseng-Chang
Author-X-Name-Last: Yen
Author-Name: Chia-Huang Wu
Author-X-Name-First: Chia-Huang
Author-X-Name-Last: Wu
Author-Name: Kuo-Hsiung Wang
Author-X-Name-First: Kuo-Hsiung
Author-X-Name-Last: Wang
Author-Name: Wei-Ping Lai
Author-X-Name-First: Wei-Ping
Author-X-Name-Last: Lai
Title: Optimisation analysis of the F-policy retrial machine repair problem with working breakdowns
Abstract:
This paper deals with a retrial machine repair problem with working breakdowns that combines <i>F</i>-policy and exponentially start-up time before allowing failed machines to join the system. A server is subject to working breakdowns when at least one failed machine is in the system. Using the matrix-analytic method, we develop the steady-state probabilities of the number of failed machines in an orbit. Closed-form expressions of major system performance characteristics and the total expected cost function are presented. A particle swarm optimisation algorithm is implemented to determine the optimal management <i>F</i>-policy and joint optimal values for fast and slow service rates simultaneously at minimum cost. A sensitivity analysis with numerical illustrations is as well presented.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 200-227
Issue: 2
Volume: 40
Year: 2022
Keywords: F-policy; matrix-analytic method; optimisation analysis; retrial; sensitivity analysis; working breakdowns.
File-URL: http://www.inderscience.com/link.php?id=121068
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:2:p:200-227
Template-Type: ReDIF-Article 1.0
Author-Name: Chirakiat Saithong
Author-X-Name-First: Chirakiat
Author-X-Name-Last: Saithong
Author-Name: Huynh Trung Luong
Author-X-Name-First: Huynh Trung
Author-X-Name-Last: Luong
Title: A periodic review order-up-to inventory policy in the presence of stochastic supply disruption
Abstract:
In many supply chains, supply disruptions may lead to interruption of a firm's operation and produce huge damage to the firm's performance. Thus, the firm should deal with those disruptions through adopting appropriate strategies. Inventory holding approach is appropriate which holds inventory more than usual in order to respond demand during supply disruption period. In this study, we study a system which comprises a supplier, who is facing with disruption, and a retailer. The problem of interest is to help the retailer derive the optimal inventory policy in the presence of stochastic supply disruption which minimises total costs per time unit in a periodic review order-up-to setting. Replenishment lead time is also considered in our problem. Numerical experiments are conducted to illustrate the applicability of the proposed model.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 181-199
Issue: 2
Volume: 40
Year: 2022
Keywords: periodic review; order-up-to inventory policy; supply disruption; stochastic demand; stochastic supply.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:2:p:181-199
Template-Type: ReDIF-Article 1.0
Author-Name: Sadjad Moradi
Author-X-Name-First: Sadjad
Author-X-Name-Last: Moradi
Author-Name: Nemat Allah Taghi-Nezhad
Author-X-Name-First: Nemat Allah
Author-X-Name-Last: Taghi-Nezhad
Title: Selecting the robust constrained shortest path under uncertainty
Abstract:
This article deals with the problem of finding a constrained shortest path on a network in which, each arc is introduced by two factors, length and time. Distance parameter is minimised and travel time is limited. Since travel time on a path depends on many factors that are constantly changing, time parameter is considered as a random variable and we assume that it is limited in specified interval. Considering the uncertainty budget, the problem is firstly modelled in the form of a Γ-robust model and then an efficient optimal method is presented to solve the problem for different levels of conservatism so that we can choose the best level of conservatism by comparing the results. The results of the implementation of the solution algorithm on different networks show that it is possible to obtain a reliable route, in which the probability of violation of travel time constraint decreases by increasing the conservatism level. However, as the level of conservatism increases, the length of the optimal robust path increases.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 533-550
Issue: 4
Volume: 40
Year: 2022
Keywords: shortest path problem; robust path; uncertainty budget; conservatism level.
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Handle: RePEc:ids:ijisen:v:40:y:2022:i:4:p:533-550