International Journal of Manufacturing Technology and Management (38 papers in press)

Regular Issues

• Effect of Machining Parameters in Drilling of Glass Fiber Reinforced Polymer Composite with Modified AJM Process.  
  by Basanta Kumar Nanda, Debabrata Dhupal 
  Abstract: Conventional drilling of Glass Fiber Reinforced Polymer (GFRP) composite produces delamination effect due to peel-up and pull out of the layers. This research work represents drilling of GFRP rectangular workpieces with fluidized bed abrasive jet machining (FB-AJM) process using silicon carbide (SiC) abrasives. Experiments were conducted according to Box-Behnken design matrix to measure the four responses, namely, material removal rate (W), surface roughness (Ra), depth of cut (h), and taper angle (TA) by utilizing bed pressure (P), nozzle tip distance (Z) and abrasive grain size (G) as input parameters. Desirability based particle swarm optimization (PSO) was performed for the multi-objective optimization to find the optimal input parameters P, Z and G of 6 kgf/cm2, 7 mm, 260μm respectively. A single experiment was performed at the predicted optimal conditions to validate the model with minimum error. The SEM analysis of the machined composite surface revealed the initiation and propagation of cracks along with embedment of erodent particle.
  Keywords: Glass Fiber Reinforced Polymer (GFRP); fluidized bed abrasive jet machining (FB-AJM); silicon carbide (SiC); response surface methodology (RSM); Desirability-Function; particle swarm optimization (PSO).
  
  
• FPGA Implementation of Gate Level Modified Adaptive Filter Architecture for Noise Cancellation Application  
  by Gomathi Swaminathan, Murugesan G 
  Abstract: This paper provides an approach for the implementation of modifications in the gate level in the adaptive filter architecture. An adaptive filter is appreciable when processing real time data and under the conditions when the signal statistics are not known a priori. Filtering data in real time needs a dedicated hardware. The resources available for implementing an efficient digital filtering algorithm are present in Field Programmable Gate Array. To design a dedicated hardware with low computational complexity, an approach of gate level modifications is incorporated in the EX-OR gate and the modified EX-OR gate is implemented in the coefficient decimation method. The proposed modified coefficient decimation method is applied in the adaptive algorithms such as Recursive Least Square, Affine Projection, and Kalman algorithm. The designed structures are experimented with the ECG and speech signal and implemented in the Xilinx Virtex 5 FPGA. Simulation and implementation results infer area reduction is achieved up to 50% and delay reduction of 10% is obtained in the proposed structures.
  Keywords: Field Programmable Gate Array; EX-OR; ECG; hardware; XILINX System Generator; full adder; half adder.
  DOI: 10.1504/IJMTM.2017.10011891
   
  
• TWO DIMENSIONAL CUTTING STOCK PROBLEM WITH MULTIPLE STOCK SIZES  
  by Umutcan Ayasand?r, Meral Azizoglu 
  Abstract: In this study, we consider a two dimensional cutting stock problem with multiple stock sizes and two stage guillotine cuts. Our objective is to maximize the difference between total revenue earned over all cut items and total cost spent over all used panels. We propose two mathematical models, derive some optimality properties and use them to enhance the performances of the models. We develop decomposition-based heuristics that use the best of the proposed models to solve the subproblems. The results of our computational study have revealed that the models can return optimal solutions for the instances with up to 30 items in 2 hours and the heuristics produce near-optimal solutions for the instances with up to 50 items in 5 minutes.
  Keywords: Integer Programming; Heuristics; Cutting Stock Problem.
  DOI: 10.1504/IJPS.2021.10043393
   
  
• Reallocation and Imported technology: Evidence from Vietnam manufacturing Sector  
  by Nguyen Khac Minh, Phung Mai Lan 
  Abstract: The objective of this study is to measure the contribution of "high- tech" importers (high-tech firms) to the productivity growth of the Vietnamese manufacturing industry. This analysis uses augmented Olley - Pakes static and dynamic productivity decomposition and the annual panel industrial survey data from the period of 2012-2016. The results indicate that high-tech firms account for only 20.8% of total firms but contribute 59.6% to productivity growth. The static decomposition shows that the reallocation process is an important mechanism for increasing the industrial productivity. The dynamic decomposition indicates that the exiting firms are the factor that reduces productivity growth while learning by doing and improving technology within the firm are limited and only significantly contribute in high-tech firms. The results also shows that high-tech importers not only increase their productivity but also become stronger in the market. The spillover effect from the high-tech firms is stronger than that of foreign-owned firms.
  Keywords: Static and dynamic decomposition; reallocation process; manufacturing industry.
  
  
• Capability management of manufacturing research centres: challenges and opportunities  
  by Olga Uflewska, T.C. Wong, Michael Ward 
  Abstract: This paper is the first to investigate capability management of manufacturing research centres within the High Value Manufacturing Catapult (HVMC). The HVMC was established to address the valley of death by bridging the gap between industry and academia in order to drive the UKs economic and technological growth. However, the current literature does not fully recognise capability management of manufacturing research centres, and hence overlook its link with operations management and strategic management within research centres environment. Regarding technology capabilities, manufacturing companies usually adopt their own measurements or assessment tools such as Technology Readiness Levels (TRL) or Manufacturing Readiness Levels (MRL) to track their technological progression. These tools, however, are not sufficient to devise important capability management practices due to research centres unique operating characteristics. It is evident that standardising such practices within the HVMC is vital, and this drives the need of developing a new capability management framework.
  Keywords: capability management; manufacturing research centres; valley of death; technology capabilities; maturity; readiness; people; equipment; project; framework.
  
  
• A Comprehensive Study of Identification of Microstructural Analysis in Various Reinforced Fly Ash Concretes  
  by J. Mahesh 
  Abstract: This investigation reveals a critical experimental study in identifying the pictorial view of pore structure of concrete in different types of concretes comprising of Class-F fly ash together with reinforcement over dissimilar fine aggregates like manufactured and river sands. Moreover, this investigation reports the analysis over dissimilar water curing conditions in finding out the pictorial view of pore structure of the concrete. For this experimentation, cement was partially replaced using fly ash and concrete mixes that were formed with 40%, 30% and 20% weights of cement and by using 16 mm diameter reinforcement. The performance analysis of this experiment was done by using X-ray diffraction spectrometry (XRD) and Scanning electron microscopy (SEM). Moreover, this investigation recommends the use of concrete mix with 30% fly ash replacement in concrete.
  Keywords: Concrete; Curing; Fly ash; Manufactured sand; XRD; SEM; Microstructure.
  
  
• PROCESS INNOVATION THE BLIND SPOT IN PRODUCT INNOVATION. DEVELOPMENT OF A GENERIC FRAMEWORK FOR THE FRONT-END IN PROCESS INNOVATION.  
  by Hubert Wittke, Alan Ryan, Ann Ledwith, Mark Southern 
  Abstract: This study aims to consolidate the fragmented knowledge dispersed across simple or incomplete (existing) frameworks on process innovation and identifies the research gaps in the management of the front-end stage. The outcomes contribute to the present knowledge by a comprehensive review (with the Systematic Literature Review methodology) and synthesis of twelve management frameworks of process innovation. The paper also presents a novel framework for management of the front-end of process innovation in manufacturing companies. This research identifies that the front-end in process innovation must integrate with activities linked to product innovation, if innovation projects are to be successful.
  Keywords: Process innovation; front-end; FFE; generic framework; product innovation; management; research gaps; systematic literature review; synthesis; manufacturing enterprises.
  
  
• Technological and organizational factors to succeed in Industry 4.0 transition implementation: an empirical study  
  by Valérie Rocchi, Daniel Brissaud, Arko Steinwender, Arnaud Bocquillon 
  Abstract: The Fourth industrial revolution and its disruptive ICT technologies for production systems are of crucial importance for the growth of European companies and especially SMEs. Nevertheless, few of them have reached the digital transformation with its expected performance yet. This paper aims at identifying the critical success factors that support a successful implementation of Factory of the Future practices. It relies on a qualitative survey addressed to 96 industrial companies that have already implemented Industry 4.0 technology and carried on in five Alpine Space countries. Five critical success factors have been identified and ranked on a Likert scale. From these ones, 24 guidelines have been designed for supporting the digital transition of industry. The results of the industry survey contribute to improve diagnosis and monitoring tools. This empirical study allows for going beyond the current industry 4.0 approaches and brings new tools for Factory of the Future implementation.
  Keywords: Industry 4.0; manufacturing; SMEs; critical success factors; industrial organisation; empirical study.
  
  
• An Optimization control method of manufacturing whole process based on real-time information drive  
  by Xiao-hua Qi, Guan-yi Wei 
  Abstract: In order to overcome the problems of low production efficiency and large deviation in production process tracking, this paper proposes a real-time information driven optimisation control method for the whole production process. Firstly, scan the manufacturing process through the physical unit of the whole manufacturing process. Secondly, the real-time information drive is used to design the information acquisition unit of the production line. Then, the real-time information flow drive of the production line is formed. Finally, the adaptive production and manufacturing parameters are calculated, and then combined with the firefly algorithm to complete the optimal control of the whole production and manufacturing process. The experimental results show that the enterprise output of this method is higher, and the tracking absolute value deviation does not exceed 0.01, indicating that the whole process optimisation control effect of this method is better.
  Keywords: information flow drive; real-time acquisition; production parameters; the whole process; firefly algorithm; optimal control.
  DOI: 10.1504/IJMTM.2022.10051232
   
  
• An Intelligent Buffer Capacity Allocation Method for Flexible Production Lines Based on Conjugate Bayes Estimation  
  by Jinrong Li  
  Abstract: In order to overcome the problems of low productivity, high vacancy rate and long allocation time in traditional methods, an intelligent buffer capacity allocation method based on conjugate Bayesian estimation is proposed in this paper. Firstly, the basic function of flexible production line is determined, and the relationship between steady performance parameters and buffer capacity is analysed. Secondly, Gershwin decomposition method is used to solve the performance parameters of flexible production line system. Then, the proper conjugate prior information is determined and the process distribution parameters are estimated using conjugate Bayes. Finally, the buffer capacity intelligent allocation value of flexible production line is calculated to realise buffer capacity intelligent allocation of flexible production line. The experimental results show that the proposed method can achieve 97.6% equipment productivity, 2.3% equipment vacancy rate and 6.6s allocation time, and has good buffer capacity allocation effect.
  Keywords: conjugate Bayesian estimation; flexible production line; prior information; buffer capacity; intelligent allocation of capacity.
  DOI: 10.1504/IJMTM.2022.10051233
   
  
• Dexterity control of multi-arm sorting robot based on machine learning  
  by Linyan Pan 
  Abstract: In order to overcome the problems of large dexterity control error of manipulator joint and poor sorting and positioning accuracy, this paper designs a dexterity control method of multi manipulator sorting robot based on machine learning. Firstly, the attitude of the multi manipulator coordinate system on the rigid body is obtained. Secondly, the translation matrix is constructed by using the translation transformation method. Then, the rotation matrix is constructed to determine the inverse motion law of the robot. Finally, determine the dexterity parameters of the manipulator joint, introduce the machine learning algorithm to calculate the dexterity parameter control error, and correct the error through the activation function to complete the dexterity control. The experimental results show that the error of this method is always less than 0.1% and the positioning accuracy is higher than 90%, which shows that the dexterity control effect of this method is good.
  Keywords: machine learning: multi-manipulator; robot; dexterity; translation transformation; rotation matrix; activation function.
  DOI: 10.1504/IJMTM.2022.10051411
   
  
• Fuzzy System for Image Defect Detection Based on Machine Vision  
  by Yiqiang Lai, Yongjun Qi, Xianfeng Zeng 
  Abstract: With the continuous upgrading of the industrial field, the market’s requirements for product quality are also increasing, which requires more accurate product monitoring equipment. This paper analyses the composition of the vision system, and compares the collected images with the defects under manual detection based on the non-local mean denoising algorithm, and the results meet the system requirements. The experimental results show that the image size is 140*141, and the distortion rate is 0.992; the image size is 120*81, and the distortion rate is 0.703. This means that the larger the image size, the higher the distortion. Before the improved algorithm, a total of 47 defects were detected, while after the improved algorithm, a total of 83 defects were detected. It can be seen that when the algorithm is improved, the number of defect detections increases significantly.
  Keywords: machine vision; image processing; image defect detection; fuzzy systems.
  DOI: 10.1504/IJMTM.2022.10051413
   
  
• Image Dehazing Network based on Improved Convolutional Neural Network  
  by Changxiu Dai  
  Abstract: Image dehazing enhances its quality by restoring the actual pixels influenced by poor light and intensity due to environmental and other factors. Hazy images are rectified to improve visibility, guidance, and object recognition through channel attribute corrections. This article introduces a pre-emptive dehazing network (PDN) using an improved convolutional neural network (ICNN) for single to multi-image dehazing. In the proposed method, neural network layers are operated for intensity-based single and multi-feature analysis. The image is split based on intensity pixels for identifying the channel corrections. This channel correction and intensity verifications are processed using CNN in different independent layers. In the CNN training, the channel correction from the hidden layers and pixel correlation from the external dataset is performed for dehazing the image pixels. The dehazed pixels are organised based on the original input organisation for verifying the similarity measure. The proposed method’s performance is validated utilising the metrics similarity, error, precision, F1-score, and time complexity.
  Keywords: channel correction; convolutional neural network; CNN; image dehazing; pixel correlation; pre-emptive dehazing network; PDN.
  DOI: 10.1504/IJMTM.2022.10051436
   
  
• Economic Investment Risk Prediction Model and Algorithm based on Data Mining Method  
  by Yi Chen  
  Abstract: Investment decisions have a broad and far-reaching impact on the operating conditions of the entire enterprise. Once the investment decision is wrong, it will bring huge risks. As a data analysis technology, data mining can simulate mathematical models or algorithms by analysing historical data, which greatly improves the accuracy of prediction. The purpose of this paper is to study the application of data mining technology in the field of investment management. This paper constructs an economic investment risk prediction model based on data mining. The research results show that the sensitive factor affecting the investment status in the model obtained by the data mining algorithm is the quick ratio. When the quick ratio is less than or equal to 1.603, the investment is one year; if the result is greater than 1.603, the investment is five years.
  Keywords: investment risk; data mining; cluster analysis; factor analysis; decision tree.
  DOI: 10.1504/IJMTM.2022.10051525
   
  
• Design of Computer Image Automatic Processing System Based on Artificial Intelligence Algorithm  
  by Guoqiang You  
  Abstract: Automatic image processing systems are applied for recognising human faces in crowds, person identification, and face matching applications. The varying textures, input representation, and position impact detection accuracy and recognition. Therefore, this article introduces an automatic image processing method (AIPM) for face recognition (FR) using deep learning (DL) paradigm. This method extracts the textural features based on the image position and classifies them based on pixel mapping. Semantic (even) and uneven pixel variations are observed in the classification process. The semantic classified pixels are used for correlating different image segments that are further used for training the learning network. The uneven pixels classified using DL is discarded to prevent recognition errors. The DL paradigm verifies the pixel position and coordinate mapping between different inputs. The detection is improved based on the classified output for semantic and uneven pixels. The training is based on semantic and mapping pixels, for which the training is improvised using erroneous pixels. Therefore, precision is improved with controlled analysis complexity.
  Keywords: artificial intelligence; automatic processing; face recognition; feature extraction; automatic image processing method; AIPM.
  DOI: 10.1504/IJMTM.2022.10052039
   
  
• Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances  
  by Christopher Kelly, Richard Wysk, Ola Harrysson, Russell King, Brandon McConnell 
  Abstract: This work expands the capabilities of the Digital Additive and Subtractive Hybrid (DASH) system by including "geometric qualification" of mechanical products. Specifically, this research incorporates the extended Additive Manufacturing Format files (AMF-TOL) which include American Society of Mechanical Engineers (ASME) Y14.5 specifications for planes, cylinders and other features so that "in-process" inspection can be completed automatically. An example for the production of hols is provided to illustrate On-Machine-Measurement collects sample radii to estimate the size and position of finished cylindrical features. Statistical analysis was used to measure bounds for comparison to specified tolerance callouts to determine whether a part is within specification, within a user-defined level of confidence. Seven different sampling strategies were evaluated on a DASH part including the bird cage sampling strategy defined in ISO-12180. Part data was utilized to show that for large data samples no statistically significant difference in accuracy was identified for four methods. Finally, analysis shows that using the DASH process with automatic inspection is economically advantageous for low volume production runs.
  Keywords: Additive manufacturing; CNC machining; Hybrid manufacturing; Inspection.
  DOI: 10.1504/IJMTM.2023.10059964
   
  
• Automatic Human Face Recognition System of Image Processing Based on BP Neural Network Paradigm  
  by Pei Yang, Guoqiang You 
  Abstract: Observation video analysis is useful in recognising human faces in crowded and coinciding scenarios. Overlapping images result in false recognition due to non-semantic textural features. The boundary analysis varies for this process, generating segments exceeding masks of the original image. Backpropagation learning (BPL) based textural-edge detection and recognition model (TED-RM) is designed to resolve this issue. The proposed model exploits the masked and un-masked textural features for identifying the semantics of the input. After this identification process, appropriate features are analysed for semantics and correlation with the inward and overlapping video image input edges. The masked and un-masked regions’ semantic features are recurrently correlated with the previous datasets for independent human faces. The mapping feature points are identified and correlated with the actual edge of the training input. The non-semantic edge points are classified for further training and validation to detect errors in further input analysis. The proposed TED-RM improves 10.84% high accuracy, 11.5% less processing time, 10.2% high true positives, 5.55% less error, and 10.6% high recall compared to existing methods.
  Keywords: DRL; face recognition; image semantics; texture classification; video analytics.
  DOI: 10.1504/IJMTM.2022.10055027
   
  
• Collaborative robots in small and medium-sized enterprises: a field-based feasibility model  
  by Marcos Vido, Salvatore Digiesi, Francesco Facchini, Wagner Lucato 
  Abstract: The Industry 4.0 revolution has led to new concepts and transformations toward technological innovations. In the manufacturing sector, the use of collaborative robots has significantly increased in the last few years, enabling them to work safely alongside humans in a shared workspace. Within this perspective, small- and medium-sized enterprises (SMEs) have been facing several challenges compared to large organizations regarding the adoption of collaborative robots. Based on the literature, this paper aims to introduce a techno-economic feasibility model to evaluate the viability of using collaborative robots in a shared workplace, with a focus on SMEs. Consistent with the paper's aim, a conceptual model was developed, supported by experts' opinions using the Delphi method. The results of this work incorporate contributions to both the academic and industrial communities.
  Keywords: collaborative robot; SMEs; feasibility analysis; industry 4.0.
  
  
• Simulation of EPC Consortium Partnership Stability and Data Based on Prospect Theory  
  by Judan Hu, Shuang Tang, Minjie Yang 
  Abstract: For the rapid promotion and healthy development of the EPC general contracting mode, this paper constructs a game model for the stability evolution of the EPC consortium tripartite cooperation relationship based on the prospect theory from the perspective of the EPC consortium led by the design unit, analyses the behavioural interaction mechanism of the game subjects and the factors affecting the system evolution, and uses system dynamics for data simulation. The results show that the rate at which the EPC consortium triad eventually evolves into a stable cooperation strategy is positively related to the initial probability, loss avoidance coefficient, gain sensitivity, and gain/loss sharing coefficient, and negatively related to the risk pursuit coefficient. The steady state of the system is influenced by the strength of penalty and the level of regulation/cooperation cost. This paper can provide insights and a theoretical basis for the long-term stable development of EPC consortium.
  Keywords: EPC consortium; cooperative stability; evolutionary games; prospect theory; system dynamics.
  DOI: 10.1504/IJMTM.2023.10056209
   
  
• Study on Intelligent Control Method of Pharmaceutical Production Quality Based on Chromatographic Fingerprint  
  by Liyuan Zhang, Yong Yang, Xuefeng Wang 
  Abstract: Aiming at the problems of low control accuracy and long control time in traditional intelligent control methods of drug production quality, an intelligent control method of drug production quality based on chromatographic fingerprint was proposed. Extract the chromatographic fingerprint of drug production quality, and use wavelet transform to de-noise the obtained fingerprint. According to the preprocessing results, use the real-time mean method to calculate the mean value of the real-time converted chromatographic fingerprint data. Through the tolerance zone of the fingerprint, convert the drug chromatographic fingerprint data. Based on the data conversion results, grade the drug production quality through fuzzy classification, The interval hesitation fuzzy control chart is constructed to carry out intelligent control of drug production quality. The experimental results show that the proposed method has higher precision and shorter control time for drug production quality intelligent control.
  Keywords: Chromatographic fingerprint; Drug production quality; Intelligent control; Real-time mean method; Fuzzy control chart.
  DOI: 10.1504/IJMTM.2023.10056614
   
  
• A method for surface wear detection of machined parts based on image processing  
  by Weilin Zeng, Weizhao Guo, Jiang Qiu, Hong Wen 
  Abstract: In order to reduce the error in the surface wear detection of machined parts, improve the detection accuracy of the failure degree of parts, and shorten the detection time, a method of surface wear detection of machined parts based on image processing is designed. Firstly, the wear mechanism is analyzed and the mathematical model of wear law is established; Then the relationship model of surface wear of machined parts is analyzed to determine the range of wear data to be detected. Finally, three components are used to determine the gray level image of part surface wear, calculate the pixel value of the maximum gray level image, and then binary processing is carried out. The noise is removed by means of the mean filtering algorithm. Finally, the wear detection of machined parts is realized by calculating the weighted mean. The results show that the wear detection error of the proposed method is low and has credibility.
  Keywords: image processing; Machined parts; Surface wear; Limit value; Mean filtering; Binarization.
  DOI: 10.1504/IJMTM.2023.10056615
   
  
• Multi product supply chain scheduling method based on hybrid genetic algorithm  
  by Lingmin Yang 
  Abstract: In order to solve the shortcomings of traditional methods such as high Hamming loss value and low demand supply rate, a multi product supply chain scheduling method based on hybrid genetic algorithm was designed. Build supply time series, and sort the priority of supply chain scheduling according to the priority attribute values of backup plans in each link of the supply chain closed-loop model. Taking the shortest scheduling time as the objective function and the location constraints of the revolving warehouse as the constraints, the scheduling results are obtained by combining the genetic algorithm. In order to avoid the genetic algorithm falling into the local optimum, the simulated annealing algorithm is introduced to solve the global optimal solution of the objective function to achieve the coordinated scheduling of the supply chain. The experimental results show that this method can achieve multi product supply chain scheduling more reasonably and effectively.
  Keywords: Genetic algorithm; Simulated annealing algorithm; Multi product supply chain; Supply chain scheduling; Dispatch time; Positioning of turnover warehouse.
  DOI: 10.1504/IJMTM.2023.10056616
   
  
• Research on the integrated logistics supply chain management model of foreign trade processing products  
  by Kui Wang, Fangfang Zhang, Jizhi Wang, Hongmei Zhao 
  Abstract: There are some problems in the integrated logistics supply chain management model of foreign trade processing products, such as high management risk coefficient, large model effectiveness evaluation error, and low supply chain evaluation accuracy. Therefore, this paper designs a method to evaluate the integrated logistics supply chain management mode of foreign trade processing products. Firstly, the characteristics of integrated logistics supply chain management mode for different foreign trade processing products are determined. Then, with the help of the analytic hierarchy process to determine the management model evaluation indicators and weights. Finally, determine the maximum demand of each node in the integrated logistics supply chain, build the model effectiveness evaluation model, and realise the evaluation of the supply chain management model. Experiments show that the proposed method can effectively reduce the risk coefficient and improve the accuracy of the model effectiveness evaluation.
  Keywords: foreign trade processing products; integrated supply chain; management mode; risk coefficient; analytic hierarchy process; judgement matrix.
  DOI: 10.1504/IJMTM.2023.10056617
   
  
• Research on welding path modification of welding industrial robot based on leapfrog algorithm  
  by Fangwei Pan 
  Abstract: Aiming at the problems of large welding path correction error, low searching accuracy of industrial robot welding path, and long correction time, a welding path correction method based on leapfrog algorithm was proposed for welding industrial robot. Firstly, the key components of the industrial welding robot system and its interaction are determined, and its control system and operation principle are analyzed; Then calculate the total resistance and voltage change value of spot welding industrial robot, realize the change of position relationship in its running path by means of homogeneous transformation method, and determine the change of technical parameters of the robot under different rotation angles; Finally, the optimal path is searched globally, and the welding path of the welding industrial robot is modified by the idea of differential evolution. The results show that the proposed method can reduce the welding path correction error, and the correction time is short.
  Keywords: leapfrog algorithm; Welding industrial robot; Welding path; Correction method; Homogeneous transformation; global search.
  DOI: 10.1504/IJMTM.2023.10056618
   
  
• Study on cost benefit estimation of enterprise environmental management based on multiple linear regression  
  by Mi Wang 
  Abstract: There are some problems in the cost benefit estimation of enterprise environmental management, such as poor precision of estimation results, low correlation of estimation indexes and long estimation time. Therefore, a cost benefit estimation method of enterprise environmental management based on multiple linear regression is proposed. First, the enterprise environmental management cost indicator system is constructed, and then the similarity between the indicator data is determined by using association rules and support calculation, and then combined and quantified. Finally, quantitatively describe the indicator data to determine that there is no correlation between them, remove the interference items in the indicator data, build an evaluation model with multiple linear regression, and verify the goodness of fit of the results through the sum of squares decomposition formula to complete the benefit estimation. The results show that the proposed method improves the accuracy of the estimation results, and the estimation speed is fast.
  Keywords: multiple linear regression; Enterprise environment; administration cost; Benefit estimation; Similarity; Quantitative description; Sum of squares decomposition.
  DOI: 10.1504/IJMTM.2023.10056619
   
  
• Service quality evaluation of agricultural cold chain logistics supply chain based on k-means clustering algorithm  
  by YuXi Zhang  
  Abstract: In order to improve the reliability of the cold chain logistics supply chain and shorten the response time of the supply chain, a quality evaluation method of agricultural cold chain logistics supply chain based on k-means clustering algorithm was proposed. First of all, build the quality evaluation system of agricultural cold chain logistics supply chain. Secondly, the root method is selected to check the consistency of the judgment matrix, and the weight vector of the logistics supply chain quality evaluation is calculated. Finally, the k-means clustering algorithm is used to evaluate the supply chain service quality. The experimental results show that the supply chain quality reliability of this method is 0.98, and the service response time is only 6 minutes; The service satisfaction rate can reach 99.6%.
  Keywords: K-means clustering algorithm; Weight vector; Analytic Hierarchy Process; Agriculture products; Cold chain logistics; Service quality assessment.
  DOI: 10.1504/IJMTM.2023.10056620
   
  
• Risk Assessment Method of Human Resources Outsourcing Based on Risk Matrix  
  by Yi Zhou  
  Abstract: In order to reduce the error of risk assessment and improve the correlation of risk indicators, a risk assessment method of human resource outsourcing based on risk matrix method is proposed. Determine the risk indicators of human resource outsourcing, use the rough set theory to determine the indiscernibility of the evaluation indicators, and use F-score to calculate the risk evaluation indicators and their information gain; Build a risk matrix coordinate chart to identify outsourcing risk factors, calculate the probability of outsourcing risk occurrence using the conditional random field joint probability formula, and build a risk assessment model through the risk matrix method to complete the risk assessment. The experimental results show that the evaluation error of the proposed method is always less than 2%, and the maximum correlation coefficient is close to 1, which verifies the effectiveness of the method.
  Keywords: Risk matrix method; Human resources; Outsourcing risk; F-score; Information gain; Joint probability of conditional random fields.
  DOI: 10.1504/IJMTM.2023.10056621
   
  
• Real time location method of electric power material storage based on RFID technology  
  by Fei Li, Tuo Xin 
  Abstract: In order to overcome the problems of traditional warehousing location methods, such as time-consuming and low positioning accuracy, a real-time positioning method for electric power materials warehousing based on RFID technology is proposed. Firstly, the weight centroid between the electrical materials to be measured is determined by the trilateral measurement method to complete the distance measurement of electrical materials in storage. Secondly, determine the proportion of the weight of the location of electrical materials in storage, and set the electrical materials storage label with the help of Gaussian filter. Finally, RFID technology is introduced to analyze the probability of collision of electronic labels of warehousing materials. With the help of time stamp calculation, the collision of electronic labels is avoided and the warehousing location of materials is completed. The experimental results show that the positioning accuracy of this method is high, and the highest positioning accuracy reaches 92%.
  Keywords: RFID technology; Power material storage; Real time positioning; Gaussian filter; Electronic label.
  DOI: 10.1504/IJMTM.2023.10056623
   
  
• Digital Packaging Design Method of Intelligent Products Based on Internet of Things Technology  
  by Gai Song  
  Abstract: Aiming at the problems of large feature extraction error and poor packaging image design effect in the process of digital packaging design of intelligent products at present, this paper designs a digital packaging design method for intelligent products based on the Internet of Things technology. First of all, build a digital packaging data collection platform for intelligent products based on the Internet of Things technology; Then, the digital packaging features of intelligent products are extracted by Harris corner feature method; Finally, the automatic generation model of packaging is constructed, and the automatic generation model is solved by maximizing the information entropy to complete the digital packaging design of intelligent products. The experimental results show that the minimum feature extraction error of the proposed method is 0.2%, and the maximum packaging color enhancement is 95%, which can effectively reduce the extraction error, and the digital packaging generation effect is good.
  Keywords: Internet of Things technology; Intelligent products; Digital packaging; Move window; Harris Corner Feature.
  DOI: 10.1504/IJMTM.2023.10056628
   
  
• An Image Detail Enhancement of Smart Product UI Interface Based on Stationary Wavelet Transform  
  by Geng Chen, Quzhi Huang 
  Abstract: To overcome the problems of low image segmentation accuracy, low image signal-to-noise ratio and long image enhancement time in traditional methods, an image detail enhancement method of smart product UI interface based on stationary wavelet transform is proposed. The Gaussian mixture model is used to obtain the image parameters of the UI interface of smart products, and the image of multiple pixels is divided into marked categories by the maximum posterior probability criterion, so as to realize the segmentation of image noise area and normal area. The two-dimensional stationary wavelet transform is performed on the noisy area, and the inverse stationary wavelet transform is performed on the stationary wavelet coefficients to obtain a reconstructed image with enhanced details. Experimental results show that the image segmentation accuracy of this method fluctuates in the range of 96%-98%, the signal-to-noise ratio is 55.3dB, and the average image enhancement time is 66.9ms
  Keywords: stationary wavelet transform; smart products; UI interface; image detail enhancement; Gaussian mixture model; image reconstruction.
  DOI: 10.1504/IJMTM.2022.10059235
   
  
• Design of real-time monitoring method for production line equipment status based on cloud computing and Internet of Things technology  
  by Pei Li, Jing Yuan, Yawen Hong, Yashe Lei 
  Abstract: In order to solve the problems of low monitoring accuracy and long monitoring time in the traditional real-time monitoring method of production line equipment status, this paper designs the real-time monitoring method of production line equipment status based on cloud computing and internet of things technology. Based on the perception of the internet of things labels, collect production line equipment status data and real-time upload, extract time domain parameters of production line equipment status, build historical memory matrix, establish and train multiple state estimation model, design distributed processing cloud computing platform MapReduce framework, complete real-time monitoring of production line equipment status under this framework. The experimental results show that the real-time monitoring accuracy of production line equipment status by the proposed method is 98%, the monitoring time is within 7.25 s, and it has the application effect of high precision and low time consumption.
  Keywords: cloud computing; internet of things technology; production line equipment; condition monitoring; radio frequency identification; RFID.
  DOI: 10.1504/IJMTM.2023.10059822
   
  
• Analysis of the factors influencing the sustainable development of manufacturing industry under the wave of industry 4.0  
  by Xiaoying Bai, Yulong Wan 
  Abstract: As a pillar industry of the national economy, whether manufacturing industry can adapt to the environment of Industry 4.0 era and get sustainable development in this wave is a key issue in the field of manufacturing industry. Through the analysis of the background of Industry 4.0 wave, the research on the development status and problems of manufacturing industry, and the analysis of the influencing factors of the sustainable development of manufacturing industry, this paper makes clear the impact of environmental factors, investment factors and resource factors on the sustainable development of manufacturing industry under the Industry 4.0 wave. On the basis of the research results, we should formulate reasonable countermeasures for the sustainable development of manufacturing industry to promote the development of manufacturing industry in the new era.
  Keywords: Industry 4.0; manufacturing industry; sustainable development; environmental protection.
  DOI: 10.1504/IJMTM.2023.10059824
   
  
• Pre-settlement Audit in Project Cost Management Based on Cloud Computing  
  by Daibing Cheng, Zhongyan Luo, Rong Ju, Yong Zhang 
  Abstract: This research mainly analysed the audit method of pre-settlement in project cost management, which served as a reference for the work in this field. The basis of the pre-settlement audit was the specific information of construction material submitted by the construction party to ensure its authenticity and legitimacy, so that the benefits of investment could be fully exerted, and the ultimate goal of resources optimal allocation could be achieved. Because the pre-settlement audit was an extremely important process in the standardised project cost, there was a need to improve the audit level so that the effective management objectives could be achieved. Therefore, we introduced cloud computing to provide a certain basis for reducing audit cost effectively. The experimental results showed that the application of the cloud computing to the pre-settlement audit had produced positive effects, and the accuracy of the audit calculation could reach about 91%.
  Keywords: cloud computing; project cost management; pre-settlement work; review method.
  DOI: 10.1504/IJMTM.2022.10060191
   
  

Special Issue on: LISS16-OPMSC Optimisation Problems in Manufacturing and Supply Chains

• CORRELATION ANALYSIS AND PRIORITIZED ABC FSN MATRIX FOR PHARMACY INVENTORY MANAGEMENT  
  by Manivel Palanisamy 
  Abstract: Objective The aim of the study was to identify the pitfalls in the existing supply chain of private and hospital pharmacies, identify the variables that influencing more in the efficiency of the pharmacy, select the appropriate inventory analysis and suggest the prioritized inventory matrix to meet customer requirement in efficient manner. Methods The qualitative and quantitative data has been collected through questionnaire and interview of the pharmacy personnel. Through SPSS, the normal distribution and correlation analysis to be carried out on sample data. The pitfalls were solved by the selection of appropriate inventory analysis and suggesting the prioritized inventory matrix to narrowed down the drugs for monitoring and control strategies of pharmacy drugs. Results The normal distribution and correlation analysis results shows that the variables collected through questionnaire are normally distributed and the variables that most influence the efficiency of the pharmacy supply chain. The implementation of Prioritized ABC FSN matrix in pharmacy will helps to provide high-quality service to the customer and there will be an adequate supply of the items in the pharmacies. The future work also to be discussed. Conclusion The prioritized ABC FSN matrix to be adopted as a routine practice for optimal use of resources and elimination of out-of-stock and over stock situations in the hospital and private pharmacy.
  Keywords: Pharmacy Supply Chain; Inventory Management System; Stock Outs; Overstock; IT Support in Pharmacy; correlation analysis; Inventory analysis.
  
  

Special Issue on: Big Data and AI for Process Innovation in the Industry 4.0 Era

• Research on total amount prediction of import and export trade data based on combined predicting model  
  by Jianxin Chen, Xiaoke Zhao 
  Abstract: In order to overcome the problems of low index significance, low prediction efficiency and low prediction accuracy in the process of prediction of import and export trade data, a new research method for total amount prediction of import and export trade data based on combined prediction model. Combine neural network prediction method and support vector machine prediction method to build a combined prediction model. Through the back propagation process, it can reduce the error between the expected and the actual output, and modify the network threshold and weight, so as to realize the classification of samples in high-dimensional space in support vector machine, and the two methods are combined to complete the prediction of total import and export trade data. The experimental results show that the significance of the proposed method is close to 100%, the prediction time is within 0.5 min, and the prediction accuracy is more than 90%.
  Keywords: Combination predicting model; Import and export trade; Data predicting; Influencing factors.
  
  

Special Issue on: Advanced Manufacturing Technologies Development and Prospect

• Path planning method of industrial intelligent welding robot based on cuckoo search algorithm  
  by Shuangling Wang, Huige Chen 
  Abstract: In order to overcome the problems of large time cost and low planning accuracy of traditional path planning methods, a path planning method of industrial intelligent welding robot based on cuckoo search algorithm is designed. Firstly, the coordinate system of industrial intelligent welding robot motion and the kinematic model of industrial intelligent welding robot are constructed by using D-H parameter method. Then, set the non collinear points in the running space of the welding robot, calculate the running radius of the welding robot according to the determined center of the circle, and complete the obstacle location. Finally, the limited conditions of welding path planning of welding robot are set, and the cuckoo search algorithm is used to optimize the optimal welding path of robot. The experimental results show that the proposed method can effectively improve the efficiency and accuracy of path planning of industrial intelligent welding robot.
  Keywords: Cuckoo search algorithm; Industrial intelligent welding robot; Route planning; D-H parameter method;.
  
  
• Path coordination scheduling method of handling robot considering three-dimensional cargo space of intelligent warehouse  
  by Wang Cheng 
  Abstract: In order to optimize the path scheduling of the transport robot, shorten the operation time and improve the operation efficiency, a path coordination and scheduling method for the transport robot considering three-dimensional goods is proposed. Firstly, a transport robot path coordination scheduling model considering three-dimensional storage is constructed, and then the improved gray wolf optimization algorithm is used to solve the path coordination scheduling model, so as to obtain the optimal operation path of the transport robot considering the three-dimensional storage space of the smart warehouse. It is verified by experiments that this method has a good scheduling effect when considering the operation path of the three-dimensional cargo space handling robot in the smart warehouse. When transporting 500m~2500m goods, the time can be shortened by 5~13min, and the working efficiency of the handling robot can be improved.
  Keywords: Intelligent warehouse; Three dimensional cargo space; Carry; Robot; Path; Coordinated scheduling.
  
  
• The dynamic multi project human resource allocation method of manufacturing industry based on multidimensional model  
  by Yi Zhou 
  Abstract: In order to overcome the problems of low allocation accuracy and long allocation time, this paper designs a dynamic multi project human resource allocation method in manufacturing industry based on multidimensional model.Determine the total number of talents, workload and utilization efficiency, build a fuzzy set of human resources indicators, and calculate the different hierarchical weights of each indicator; The fuzzy comprehensive evaluation method is used to construct the index comprehensive evaluation matrix, the PCA interval model in the multi-dimensional model is used to orthogonalize each index, and the multilateral convex set model in the model is used to realize the intersection of index parameters in different regions, so as to realize the rational allocation of human resources.The experimental results show that the proposed method improves the accuracy of dynamic multi project human resources allocation in manufacturing industry, and the allocation time is short.
  Keywords: Multidimensional model; PCA interval model; Human resource allocation; fuzzy sets.
  DOI: 10.1504/IJMTM.2024.10059995