International Journal of Internet Manufacturing and Services (26 papers in press)

Regular Issues

• A comprehensive review of Industry 4.0 in manufacturing sector: Current status and future research direction  
  by Rajeev Rathi, Mahipal Singh, Chinthapatla Vishnu Vardhan Rao, Varanasi Bhanu Teja, Ankit Kadian, Tanish Saxena 
  Abstract: Industry 4.0 (I4.0) technology is getting a wide attention in manufacturing environment because of having capability to enhance revenues, efficiency and minimise the cost. The literature lacks to explore the current status of I4.0 adoption in manufacturing industries of developing countries. In this regard, the present study theoretically examines the current status of I4.0 adoption in Indian manufacturing setting and also suggests appropriate recommendation for future research. For exploring the status of I4.0, a systematic literature review approach has been adopted. The outcomes reveal that the adoption of I4.0 in developing economy is still in initial phase and requires a rigorous policy and implementation framework of I4.0. The future generation of manufacturing systems is significantly influenced by the quick development of information technology. This paper facilitates to managers to formulate the smart guidelines through understanding of barriers and drivers of I4.0.
  Keywords: Industry 4.0; big data; cloud-based manufacturing; barrier and drives of I4.0; industrial IoT; smart manufacturing.
  DOI: 10.1504/IJIMS.2023.10048384
   
  
• Empirical analysis of I4.0 implementation enablers in context of Indian manufacturing industries using DEMATEL approach  
  by Mahipal Singh, Rajeev Rathi, Mainul Islam, Abdulla All Noman, Marjan Ahmed, Sala Uddin Ahemed, Md Nahid Alam 
  Abstract: Industry 4.0 (I4.0) revolution is the cyber-physical transformation and a growing trend towards automation in the manufacturing industry. This study empirically examines the critical enablers for I4.0 adoption in Indian manufacturing industries. Initially, 25 enablers are extracted from literature and screening of significant enablers is done through expert’s view. The screened enablers are prioritised using DEMATEL approach. The results indicate that internet of thing (IoT) enabler is got the 1st rank as it affects the most of enablers significantly, followed by artificial intelligence got 2nd rank and top management support obtained 3rd rank as a driver of I4.0 adoption. The obtained outcomes provide an understanding of significant enablers which promote the I4.0 implementation in the Indian manufacturing setting. This study also facilitates industrial managers to focus on enablers as per proposed ranking during making implementation strategies for I4.0 technology.
  Keywords: Industry 4.0; enablers; DEMATEL; internet of thing; IoT; manufacturing sector.
  DOI: 10.1504/IJIMS.2023.10048417
   
  
• UNLEASHING A DMAIC-ROADMAP FOR SUSTAINABLE DEPLOYMENT OF  
  by Eisha Mehta Sharma, Bikram Jit Singh 
  Abstract: With the evolution of automation and Industry 4.0, there has been a drastic revolution in the fields of manufacturing supply chains. This has even given rise to global competition and supply chain complexities as well. In the world of information technology, artificial intelligence (AI) plays a major role in running the things with ease and access. The main focus of this study will be on the Indian automobile supply chains (IASCs), where the implementation of AI will be suggested by framing a functional model through well-structured
  Keywords: artificial intelligence; non-parametric testing; automobile supply chain; ASC; DMAIC; deployment model.
  DOI: 10.1504/IJIMS.2023.10048858
   
  
• Sustainable Manufacturing of Advanced Mg-Zn-HAp/rGO Hybrid Nanocomposites and Evaluation of Mechanical and Microstructural Properties  
  by Venkata Satya Prasad Somayajula, Sashi Bhushan Prasad, Subhash Singh 
  Abstract: The growing demands of the consumers in the modern society has resulted in many advancements in the field of material science and manufacturing technology. It has become a necessity to meet the increasing demands of the consumers. The increasing manufacturing sectors have negatively impacted the environment and its resources in terms of pollution and material wastages. Therefore, to save the environment and reduce the environmental impact, the concept of sustainable manufacturing or green manufacturing came into existence. This focusses on manufacturing processes with minimal wastage and lower environmental impact. Keeping this in mind, the present study focuses on an efficient and sustainable manufacturing technique of stir casting to fabricate the hybrid nanocomposite (HNC) of a binary Mg-2.5Zn alloy, reinforced with various weight percentages of reduced graphene oxide (rGO) and hydroxyapatite (HAp). The Mg-based HNCs manufactured with enhanced mechanical characteristics endorses the green manufacturing technique due to minimal material wastage.
  Keywords: sustainable manufacturing; stir casting; green manufacturing; magnesium binary alloy; hybrid nanocomposites; reduced graphene oxide; rGO; hydroxyapatite; HAp.
  DOI: 10.1504/IJIMS.2023.10049047
   
  
• Analysis of green manufacturing attributes through partial least square structural equation modelling  
  by Jasvinder Singh, CHANDAN DEEP SINGH, Dharmpal Deepak 
  Abstract: With the rise of industrialisation and globalisation, manufacturing industries are under pressure to integrate more eco-friendly manufacturing techniques into their operations. As per literature, there are huge requirement to consider such factors which drive the green manufacturing (GM) implementation in manufacturing sectors. Therefore, in the present work, GM implementation factors are identified and modelled them in context of the Indian manufacturing industries. The data related to GM implementation factors was collected by sharing online questionnaire with the industry experts and professionals. The collected data have been analysed through partial least squares structural equation modelling (PLS-SEM). The result of study reveals that GM implementation issues, organisational style, role of legislation (RoL) in promoting GM and eco knowledge (EcoK) are the main factors that influence the
  Keywords: GM implementation factors; partial least square structural equation modelling; PLS-SEM; organisational style.
  DOI: 10.1504/IJIMS.2023.10049132
   
  
• Perspectives of Pilot Testing as a Lean Tool: To conduct a Sustainable Survey in Indian Textile Industry  
  by ASHWANI SHARMA, Bikram Jit Singh 
  Abstract: Lean manufacturing is a philosophy of eliminating waste through continuous improvement. This paper is an outcome of a survey study conducted in a textile industry in north India. Though the concept of lean has shown good results in manufacturing industry, but still it is a challenge to implement traditional lean tools in complex survey-based studies, usually carried out in Indian textile sector. In present study, a questionnaire is designed to capture the true voice of different stakeholders, without ignoring the critical constraints of the vast textile environment of the country. This has further caused the confusion and makes this critical process of gathering feedback more complicated. Through this research paper, a unique effort is made to exploit lean philosophy and a slight freedom has been taken to select out-of-basket lean tools, to reduce the vague inflation in survey-based textile research. The
  Keywords: lean; pilot testing; questionnaire; sampling; cluster analysis; Cronbach’s alpha.
  DOI: 10.1504/IJIMS.2023.10049207
   
  
• Establishing and Analyzing Relationship among Green Lean Six Sigma Barriers: A Structural Mapping Approach  
  by Vishwas Yadav, Pardeep Gahlot 
  Abstract: The purpose of this study is to comprehend the contextual relationship among GLSS barriers to facilitating the implementation of this novel sustainable approach within industrial organisations. Moreover, different removal measures for the barriers are also suggested in this research. To establish a relationship among GLSS barriers through interpretive structural modelling (ISM) and impact matrix cross-reference multiplication applied to classification (MICMAC) analysis which is a preferred choice of researchers to develop a structural framework. A total of 16 barriers were identified with the help of a systematic literature review and additionally authenticated by the expert opinions of industrial personnel for better applicability. The study reveals that lack of customer involvement emerges as the most critical barrier. Furthermore, the outcomes of MICMAC analysis project the cluster-based findings and portrays that; five barriers are found as linkage and dependent barriers, six barriers as driving, and no barrier as autonomous.
  Keywords: lean manufacturing; green technology; Lean Six Sigma; Green Lean Six Sigma; GLSS; barriers; interpretive structural modelling; ISM; sustainability.
  DOI: 10.1504/IJIMS.2022.10049853
   
  
• Lean Work management through exploration and investigation of performance metrics: A service perspective  
  by Mahender Singh Kaswan, Varun Kumar, Pawan Kumar 
  Abstract: Continuous exploration of performance or Lean metrics provides a real time assessment of the available capacity of the organisational resources and provides a deep insight into the know-how of the organisation. This research work deals with exploration and investigation of Lean metrics of a contact centre involved in the counselling process of a pioneer university of India. For this, different metrics related to performance have been explored and then same evaluated for certain periods of time to adjudge real estimate of employee performance. The dataset for this study have been collected through continuous interaction with authorities engaged in the counselling process for the prospective students of the university. It has been found that quality assurance score and nomination for best counsellor directly affects the conversion of admission in most of the cases and provides impetus to the counsellors to be self-motivated.
  Keywords: quality score; admission; lean; efficacy; work performance; contact centre; education.
  DOI: 10.1504/IJIMS.2023.10050064
   
  
• A Compensation method of end pose error of industrial welding robot based on Internet of things  
  by Juchen Li, Cuirong Zhao, Sarah Atifah Saruchi, MAHMUD IWAN SOLIHIN, Chiong Meng Choung 
  Abstract: In order to reduce the end pose error of industrial welding robot, a new end pose error compensation method of industrial welding robot based on internet of things (IoT) is proposed. Firstly, the end pose acquisition sensor is set to collect the end pose sample data of the welding robot under the IoT architecture. Secondly, the availability of pose data is improved by homogeneous transformation. Finally, the end rotation feature of the welding robot is calculated, and the Kalman filter model is used to fuse the end pose parameters of the industrial welding robot. According to the covariance matrix, the error compensation function of industrial welding robot is constructed. The experimental results show that the proposed end pose error compensation method of industrial welding robot based on the internet of things has higher end pose compensation effect, the maximum error after compensation is not more than 0.2 mm.
  Keywords: internet of things; IoT; industrial welding robot; end pose; error compensation.
  DOI: 10.1504/IJIMS.2023.10050954
   
  
• Market-based Environmental Regulation, Green Technology Innovation and Green and Low-carbon Economy  
  by Li Jia, Xu Yibo 
  Abstract: The establishment of a green and low-carbon economic development system is of great significance in promoting the overall green transformation of economic development. Based on the Super-SBM model, this paper constructs a green and low-carbon economic development index, uses the dynamic panel data of 30 provinces and cities in China from 2006 to 2018 to study the relationship between market-based environmental regulation, green technology innovation and green low-carbon and economy. The results indicated that market-based environmental regulation has a significant inhibitory effect on green technological innovation, and the combined effect of market-based environmental regulation and green technological innovation can effectively weaken the
  Keywords: green and low-carbon economy; market-based environmental regulation; green economy demonstration area; carbon neutrality; empirical study.
  DOI: 10.1504/IJIMS.2024.10051039
   
  
• Operational Excellence Through Lean Six Sigma -A Case of Multi-specialty Hospital  
  by Manjeet Kharub, Sudhir Rana, P. Srinivas Reddy, Himanshu Gupta 
  Abstract: This research aims to improve patient satisfaction by lowering wait times in a hospital’s outpatient department. Lean Six Sigma (define, measure, analyse, improve, and control) was used to reach the target. VoC, VoB, COPIS flow chart, project charter, fishbone diagram, fitting line plots, DOE cube plot, and I-MR charts were used. Fluctuating staff numbers, physician availability, early morning meetings, an insufficient number of workers to handle registration counters, and a lack of regular processes caused long patient wait times. Statistically, patient satisfaction declines with waiting time. Design of experiment (DOE) found that on-site doctors increased patient satisfaction. The optimal wait time was 8.350 minutes. The team reduced the mean wait time from 24.257 to 9.18 minutes by employing 6.57 to 2.77 minutes. This case study’s step-by-step strategy ensures LSS success in healthcare. The step-by-step approach described in this case study will ensure the success of LSS efforts in the healthcare industry.
  Keywords: operational excellence; Lean Six Sigma; LSS; patient waiting time; healthcare; case study; design of experiment; DOE.
  DOI: 10.1504/IJIMS.2023.10051041
   
  
• Information data perception allocation method for industrial Internet of things based on dissimilarity algorithm  
  by Yinlei Tian, Yan Yang 
  Abstract: In order to improve the efficiency and accuracy of industrial IOT information data perception and allocation, this paper proposes an industrial IOT information data perception and allocation method based on dissimilarity algorithm. Firstly, the dissimilarity matrix is constructed to determine the data attribute values. Secondly, according to the method of dissimilarity degree, the candidate point set of clustering centre point is determined. Build the generation allocation matrix to calculate the storage capacity of the node ID, calculate the security of the data node through the dissimilarity algorithm, remove the poor security allocation scheme, and get the information and data perception allocation results of the internet of things. The experimental results show that the distribution recall rate of this method can reach 97.2%, the distribution accuracy is 97.3%, and the distribution time is only 5.6 s, indicating that this method can improve the data aware distribution effect.
  Keywords: improved ant colony algorithm; data distribution delay function; dissimilarity algorithm; data aware allocation; initial cluster centre.
  DOI: 10.1504/IJIMS.2023.10051299
   
  
• Research on multi-objective workflow rapid scheduling based on improved heuristic algorithm  
  by Fangfang Liu, Xin Lv, Jing Wang 
  Abstract: Aiming at the problems of low efficiency and poor scheduling effect of traditional multi-objective workflow scheduling methods, a multi-objective workflow rapid scheduling method based on improved heuristic algorithm is designed. Firstly, analyse the mode of multi-objective workflow and determine the scheduling task of multi-objective workflow. Then, a directed acyclic graph is constructed to model complex multi-objective workflow tasks, determine the interdependency between task flows, and determine the priority of tasks. Finally, the heuristic algorithm is improved by using the elite solution of fitness value in the population. Based on the improved progressive heuristic algorithm, the task sequence of multi-objective workflow scheduling is updated, and the value of update parameters is determined according to the set random step size, and the constraint conditions are set to complete the multi-objective workflow scheduling. The experimental results show that the maximum scheduling time is 3.8 s and the maximum scheduling error is less than 2%.
  Keywords: improved heuristic algorithm; multi objective; workflow scheduling; directed acyclic graph; objective function; random step size.
  DOI: 10.1504/IJIMS.2023.10051408
   
  
• A novel decision-making scheme for hospital emergency services based on plant growth simulation algorithm  
  by Long Chen, Qinming Liu, Chunming Ye, Jiaxiang Li 
  Abstract: A novel decision model of hospital services decision-making based on cumulative prospect theory and plant growth simulation algorithm (PGSA) is proposed. First, this paper considers the bias of psychological behaviour characteristics of hospital emergency services decision makers, and the selection of patient emergency solutions is designed as a nonlinear programming model. Then, the integrated value of hospital scenarios under emergencies is calculated based on the loss and gain values of patient injury severity and emergency resource utilisation, and the cumulative prospect values of each emergency scenario are calculated based on interval probability and cumulative prospect theory. PGSA is used to weigh the accumulated prospect value vector of each decision maker. Finally, the data description shows that the decision process can make the hospital emergency services scenarios optimal under emergencies, it makes emergency decision making more in line with the actual situation and thus improves scientific and effective decision making.
  Keywords: hospital services; emergency resources; cumulative prospect theory; emergency services decision making; plant growth simulation algorithm; PGSA.
  DOI: 10.1504/IJIMS.2024.10051482
   
  
• Processing station tracking control method of assembly robot based on narrow band Internet of Things  
  by Linyan Pan 
  Abstract: This paper proposes a processing station tracking control method of assembly robot based on narrow band internet of things. Firstly, LTE carrier resource block is used to establish the physical layer of narrow band internet of things. Then, the data of the assembly robot’s processing stations were collected by using the control chart of measurement values, and the continuous pose space was processed by using the discretisation method to obtain a set of discrete processing stations. The tracking control problem of machining station position was transformed into the problem of optimising the selection of machining position from the set, and the station position was tracked through the clustering of machining objects. Experimental results show that the tracking control accuracy of this method is up to 98.8%, and the tracking control time is only 9.3 ms, which has good tracking control effect of assembly robot processing station.
  Keywords: narrow band internet of things; assembly robot; clustering algorithm; processing position; genetic algorithm; tracking control.
  DOI: 10.1504/IJIMS.2023.10051520
   
  
• Optimal strategies for an uncertain forward and reverse multi-period logistics network using heuristic algorithm: A case study of Shanghai perishable products  
  by Jianquan Guo, Lian Chen, Bingzi Tang, Mitsuo Gen 
  Abstract: In view of the high economic volatility, serious environmental pollution and updated demands of customers for distribution efficiency caused by uncertain demand or recovery, improper handling and untimely delivery of perishable products under various circumstances. An uncertain perishable products forward and reverse logistics network and its optimal strategies are proposed with the consideration of multi-period and multi-objective. The first objective is to minimise the overall cost of the system, the second objective is minimum environmental impact and the third one is about just-in-time delivery. Model’s validity was proved by a hybrid GA-PSO algorithm, aided by an exact solver (CPLEX) with a case of a perishable products enterprise in Shanghai. Finally, some useful references and managerial insights are proposed to create a forward and reverse logistics network for perishable products enterprises.
  Keywords: perishable products; uncertain forward and reverse logistics network; multi-period and multi-objective; hybrid particle swarm optimisation and genetic algorithm.
  DOI: 10.1504/IJIMS.2024.10051752
   
  
• Multi-objective Scheduling Method of Workflow Task Based on Tabu Search Algorithm  
  by Jie Zhao, Chungeng Ma, Wenyan Zhao 
  Abstract: In order to reduce the execution cost of multi-objective scheduling of workflow tasks, a multi-objective scheduling method of workflow tasks based on tabu search algorithm is designed. With the optimisation goals of transmission volume, load balance and time consumption, a multi-objective scheduling model of workflow tasks is constructed; combined with the tabu search algorithm and sequential quadratic programming method, the TS-SQP algorithm is designed to solve the objective function model and complete the multi-objective scheduling of tasks. The test results show that the execution cost of a single job of this method is reduced to 0.42 yuan, and the satisfaction of the deadline is higher than 40%, which can obtain a better scheduling effect.
  Keywords: tabu search algorithm; load balancing; workflow task; sequential quadratic programming method; multi-objective scheduling.
  DOI: 10.1504/IJIMS.2023.10051872
   
  
• Data fusion method of industrial Internet of Things based on fuzzy theory  
  by Qiaoyun Chen, Chunmeng Lu 
  Abstract: In order to overcome the problem of poor data fusion effect of data fusion method. This paper proposes a data fusion method of industrial internet of Things based on fuzzy theory. Firstly, the data acquisition area is divided and the data is collected by the absolute median difference method. Secondly, fuzzy set is constructed to extract data attribute features according to membership function. Then, the trusted data is screened by clustering routing protocol and classified by exponential smoothing method. Finally, the spatial and temporal correlation degree is used to allocate the fusion weights, and the industrial internet of things data fusion is carried out by fuzzy theory. Experimental results show that the classification accuracy of the proposed method can reach 99%, the data fusion rate can reach 99.5%, and the fusion time is only 3.92 s. The proposed method can improve the data fusion effect.
  Keywords: clustering routing protocol; fuzzy theory; fuzzy classification; membership function.
  DOI: 10.1504/IJIMS.2023.10051928
   
  
• High-fidelity modelling of multiple transporters block transportation based on digital twin at shipyards  
  by Tian Luo, Zhenyu Xu, Xin Song, Miaomiao Sun 
  Abstract: In order to solve the problems of poor scheduling and inefficiency of transporters in block transportation at shipyard, this paper proposed a framework of multiple transporters for block transportation scheduling systems with a digital twin-based (DT) five-dimensional model. The proposed framework can be used to identify low-efficiency of multidisciplinary, multi-physics, multiscale, and dynamic changes over time at shipyards to optimise the efficiency of multiple transporter scheduling and block transportation. DT provides the fidelity required to realistically predict transporter scheduling schemes with rescheduling actions under various interference conditions. The high-fidelity model is investigated using three levels of geometry, dynamics and data. An optimal simulation model experiment with multiple transporters is adopted to improve transportation efficiency. The results show that the proposed DT framework and high-fidelity model are effective, and both the utilisation of transporters and the transportation efficiency of blocks are improved.
  Keywords: high-fidelity modelling; simulation; block transportation; multiple transporters transportation; digital twin; DT.
  DOI: 10.1504/IJIMS.2024.10052164
   
  
• Risk Analysis of Private Equity Financing of Manufacturing Industry Based on DANP model  
  by Haotian Ma, Alia Erbolat, Rende Li 
  Abstract: The risk of private equity financing is a multi-level, multi-factor complex system, and its risk assessment has the characteristics of ambiguity and uncertainty. In order to be able to conduct a comprehensive and effective evaluation of private equity financing under carbon neutrality, a DNP method of hybrid multi-objective decision MCDM is applied to evaluate the risk of private equity financing. The results show that: The DANP method uses the ANP method to perform the double-weighted operation to obtain the mixed weight of the four-level index based on the weight of the three-level index of the DEMATEL method. It considers the interaction between levels and makes the risk analysis of private equity financing more reliable. Besides, empirical analysis of the impact of various influencing factors on private equity financing. The research results not only reduce the investment risk of private equity funds in the financing process but also make better assessments for financing companies. It also improves the DANP method and performs double-weighted mixed operations between levels to avoid the unreliability of the system, thereby enriching the risk research of private equity financing based on quantitative methods.
  Keywords: private equity financing; risk assessing indicator system; risk evaluation; DANP model; blended weight; manufacturing industry.
  DOI: 10.1504/IJIMS.2024.10052437
   
  
• An empirical study of Lean and Green Practices in Indian Manufacturing Companies: Drivers & Barriers  
  by Geeta Sachdeva, Shallini Taneja 
  Abstract: Lean and Green (L&G) is one of the emerging subject evolving around manufacturing companies now days. Indian manufacturing sector has already started adapting the lean frameworks for successful implementation of Green practices which can be supportive in achieving green goals as well. Based on contemporary literature and industry experts, the current investigation aims to discover and assess the drivers and obstacles associated with current lean-green (L&G) deployment techniques in Indian manufacturing companies. Exploratory Factor Analysis and Reliability analysis was used to identify drivers and barriers for integrating Lean & Green (L&G) in the organization, which reduced 31 items into four constructs namely: Societal concern for protection and benefits to natural environment, Enhancing stakeholders’ satisfaction and operational sustainability, Lack of ecosystem for Green &Lean Practices and Cultural disconnect at workplace. The aftermaths of the current study provide insights for policymakers and the companies in this sector for formulating their future strategies for developing the sustainable models towards making the green society at a holistic level.
  Keywords: Lean practices; Green practices; drivers; benefits; barriers; obstacles.
  DOI: 10.1504/IJIMS.2023.10052635
   
  
• A state-of-the-art literature review on Lean Six Sigma from Manufacturing Sustainability and Industry 4.0 Viewpoints  
  by Sandeep Kumar, Rakesh Kumar Phanden, BHARATH KUMAR S, Ravinder Kumar 
  Abstract: The sustainability-focused and Industry 4.0-empowered Lean Six Sigma (LSS) approach is evolving as a robust business agenda for quality excellence in the manufacturing sector. This paper aims to present a state-of-the-art literature review on LSS from manufacturing sustainability and Industry 4.0 viewpoints. Authors have extracted the related literature from various databases and segregated it for descriptive, empirical, and exploratory research perspectives. Also, the list of common and uncommon enablers and barriers is presented. This paper provides many future research directions on LSS in the manufacturing sector from both Industry 4.0 and manufacturing sustainability viewpoints.
  Keywords: Industry 4.0; I4.0; manufacturing sustainability; Lean Six Sigma; LSS; literature review; enablers; barriers; manufacturing sector.
  DOI: 10.1504/IJIMS.2023.10052745
   
  
• A framework for the systematic implementation of Green Lean Six Sigma to improve performance in the manufacturing industry  
  by Vishwas Yadav, Pardeep Gahlot, Raj Kumar Duhan, Mahender Singh Kaswan, Rajeev Rathi, Gunjan Yadav, Pawan Kumar, Varun Kumar 
  Abstract: Green Lean Six Sigma (GLSS) is an all-inclusive methodology that assists the optimal utilization of resources, minimizes waste, and imparts the pathway for sustainable development. This study proposes a novel five facet GLSS framework for the manufacturing industry to improve performance in terms of different sustainability dimensions. The framework has been designed based on three key dimensions: Insights from literature, the experience of authors, and inputs from the case organization members. The framework is validated in an Indian automotive component manufacturing organization. From the effective implementation of the proposed GLSS framework, defects were minimized from 18000 ppm to 7000 ppm and environmental impacts were brought down from 44.70 Pt to 32.70 Pt. This study facilitates industrial managers and practitioners to adopt the GLSS approach to improve sustainability dynamics in the manufacturing industries.
  Keywords: Lean; Six Sigma; Green manufacturing; Green Lean Six Sigma; framework; Sustainability.
  DOI: 10.1504/IJIMS.2023.10054193
   
  
• Multi-path reliable routing technology of industrial Internet of things based on sparrow search algorithm  
  by Chungeng Ma, Wenjing Ma, Lixia Hou 
  Abstract: The routing technology of industrial Internet of Things (IoT) has no obvious advantages in reliability and balance, so a multi-path reliable routing technology of industrial IoT based on sparrow search algorithm is proposed in this paper. Firstly, a topology model is constructed by comprehensively considering the node part and path connection mode of the industrial IoT. Then the hierarchical protocol is used to set up the routing protocol, and calculate the trust degree of nodes and paths of the industrial IoT. Finally, the sparrow search algorithm is used to select the reliable data transmission path. Through route switching and updating, the multi-path reliable routing technology of the industrial IoT is realized. The experimental results show that the data delivery rate of this technology is increased by 2.67%, and the routing load balance is significantly improved, that is, it has obvious advantages in reliability and balance.
  Keywords: Sparrow search algorithm; Industrial Internet of things; Multipath routing; Reliable routing; Chinese library classification number: TP393 Document identification code: A.
  DOI: 10.1504/IJIMS.2023.10054244
   
  
• Optimization of site selection for urban material distribution during the COVID-19 pandemic  
  by Houjun Lu, Tian Zhu 
  Abstract: Improving the resilience of regional logistics and supply chains in controlled cities as the COVID-19 epidemic normalises can have a positive impact on epidemic prevention and management. This paper proposes a resilient logistics mode that establishes large warehouses outside sealed and controlled urban areas to support the distribution of materials required for the public. The selection of the material distribution sites is essential to save cost and time during the distribution process. The distribution of materials in urban communities is disrupted by uncertain factors, such as regional road closures and controls, impassable roads and diminished transport capacity. Therefore, for epidemic containment and control, a site selection model for material distribution in urban areas is required. The site selection has two goals, achieving the highest satisfaction in the demand points, and obtaining the lowest total construction costs in the distribution points. In addition, a risk coefficient for road closure and control is introduced to construct a multi-attribute satisfaction decay function. The division of the epidemic prevention and control stages is described with the quantitative variables of the epidemic control measures.
  Keywords: epidemic lockdown; resilient logistics; site selection; simulated annealing algorithm.
  DOI: 10.1504/IJIMS.2024.10054388
   
  
• Fault location method of industrial Ethernet communication line based on Bayesian  
  by Yang LIU, Mingli LIU, Ge ZHANG, Shaofeng ZHAO, Ze WANG 
  Abstract: Because the traditional fault location method of industrial Ethernet network communication line has the problems of high location false alarm rate, low location accuracy rate and long location time, a Bayesian-based industrial Ethernet network communication line fault location method is proposed. First, the fault signal is measured by discrete Fourier transform algorithm. Then according to the measurement results, the fault features are extracted. Finally, the extracted features are input into Bayesian as training samples, and Bayesian is used to calculate the maximum posterior probability output corresponding to the input data, build a fault localisation model, and obtain the localisation results. The experimental results show that the fault localisation rate of the proposed method is only 0.8%, the localisation accuracy rate is as high as 98.6%, and the localisation time is 10.3 s. The fault localisation effect is good, and the fault localisation time can be effectively shortened.
  Keywords: Bayesian; industrial Ethernet network; information entropy; communication line; fault location.
  DOI: 10.1504/IJIMS.2024.10054812