Template-Type: ReDIF-Article 1.0 Author-Name: Ram Khilari Author-X-Name-First: Ram Author-X-Name-Last: Khilari Author-Name: Om Prakash Wali Author-X-Name-First: Om Prakash Author-X-Name-Last: Wali Author-Name: Rajesh K. Singh Author-X-Name-First: Rajesh K. Author-X-Name-Last: Singh Title: Identification and prioritisation of technology management practices for enhancing competitiveness of auto components manufacturing firms in India Abstract: Auto component manufacturing is an important sector for India's industrial growth. During last six decades, this industry has made profound progress; its operations are still largely dependent on imported technology. It is lagging behind many industrially advanced countries. Enhancement of firms' competitiveness in this sector has been a major concern. Technology and its management is considered as one of the most important drivers for enhancing competitiveness, but which technology management practice be accorded highest priority and which one would be the next, and so on, has hitherto not been attempted. With this purpose, through literature review, competiveness indicators and technology management practices relevant to this sector have been identified. Using AHP model, prioritisation of competitiveness indicators and technology management practices affecting competitiveness, has been done. Based on the findings, the paper suggests a technology management framework for enhancing competitiveness for auto components manufacturing firms, which could also be useful to other sectors' manufacturing firms. Journal: Int. J. of Manufacturing Technology and Management Pages: 65-94 Issue: 1 Volume: 36 Year: 2022 Keywords: auto component; competitiveness; prioritisation; technology management. File-URL: http://www.inderscience.com/link.php?id=121601 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:1:p:65-94 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaoyan Zhao Author-X-Name-First: Xiaoyan Author-X-Name-Last: Zhao Author-Name: Fan Yang Author-X-Name-First: Fan Author-X-Name-Last: Yang Title: Research on wear characteristics of spraying material layer on hydraulic equipment of multi-axis CNC machine tool based on discrete element method Abstract: In order to solve the problems of low accuracy and long time-consuming of traditional methods in analysing the wear characteristics of spraying material layer of multi-axis CNC machine tool hydraulic equipment, a research method of wear characteristics of spraying material layer of multi-axis CNC machine tool hydraulic equipment based on discrete element method was proposed. The discrete element method was introduced to analyse the wear characteristics of spraying material layer of multi-axis CNC machine tool hydraulic equipment. Based on the discrete element method, the contact model of spraying material layer of multi-axis CNC machining hydraulic equipment was established. The friction coefficient and wear rate of multi-axis CNC machine tool hydraulic equipment spraying material layer under different load and sliding speed analysed. The experimental results show that the accuracy of the proposed method is up to 99% and the analysis time is about 7 s. Journal: Int. J. of Manufacturing Technology and Management Pages: 95-111 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: discrete element method; DEM; multi-axis NC machine tool; hydraulic equipment; kinematic model; spraying material layer; wear characteristics. File-URL: http://www.inderscience.com/link.php?id=123657 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:95-111 Template-Type: ReDIF-Article 1.0 Author-Name: Kehui Xuan Author-X-Name-First: Kehui Author-X-Name-Last: Xuan Author-Name: Guangchao Gu Author-X-Name-First: Guangchao Author-X-Name-Last: Gu Title: Optimisation of multi-channel to single channel control method for food packaging line based on PLC Abstract: In order to overcome the problems of low efficiency and high control error of single channel to multi-channel in food packaging line, a multi-channel to single channel control method for food packaging line based on PLC was proposed. This method uses PROFINET industrial Ethernet technology to design the network architecture of the control system. The machines and equipment are connected through the packaging and conveying chain, the basic speed of the packaging chain is calculated, the production task is coordinated, the frequency signal and speed signal of the frequency converter are converted, and the adjustment test is carried out in the later stage to achieve the predicted control effect. The experimental results show that the packaging efficiency is always above 96%, and the minimum control error is 0.002, which has good control effect and can meet the production requirements of food packaging plants. Journal: Int. J. of Manufacturing Technology and Management Pages: 112-126 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: programmable logic controller; PLC; food packaging line; multi-channel to single channel; control method; optimisation research. File-URL: http://www.inderscience.com/link.php?id=123658 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:112-126 Template-Type: ReDIF-Article 1.0 Author-Name: Tianci Pan Author-X-Name-First: Tianci Author-X-Name-Last: Pan Author-Name: Changhong Zhu Author-X-Name-First: Changhong Author-X-Name-Last: Zhu Title: Synchronous speed control for industrial production line based on BP neural network Abstract: In order to overcome the problems of large speed control error and poor anti-interference effect existing in the traditional speed control methods, the paper proposes a speed synchronisation control method of industrial production line based on BP neural network. Firstly, the state of production equipment is adjusted through PLC operation instruction, and amplifier circuit is designed to reduce the influence of signal interference. Then the speed control parameters of the production line are adjusted by adaptive control method, and the parameters are fused by fuzzy control theory. Finally, the speed of the industrial production line is synchronously controlled by BP neural network. The experimental results show that the control error coefficient of this method is always lower than 9%, and the influence of step disturbance signal is low, indicating that this method has good application performance. Journal: Int. J. of Manufacturing Technology and Management Pages: 127-140 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: BP neural network; industrial production lines; speed control; fuzzy control theory; PLC instructions; adaptive control. File-URL: http://www.inderscience.com/link.php?id=123659 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:127-140 Template-Type: ReDIF-Article 1.0 Author-Name: Bin Huang Author-X-Name-First: Bin Author-X-Name-Last: Huang Author-Name: Yankai Xiao Author-X-Name-First: Yankai Author-X-Name-Last: Xiao Author-Name: Yizheng Chen Author-X-Name-First: Yizheng Author-X-Name-Last: Chen Title: Modelling and group decision-making method for virtual enterprise partner selection with fuzzy completion time and due date Abstract: We have studied the partner selection problem (PSP) in virtual enterprises with different preferences and uncertainties in completion time and due date. As a result, a new model employing fuzzy sets theory has been established to explain fuzzy completion time and fuzzy due date. For the candidate solutions obtained by decision-makers with different preferences, a multi-objective group decision-making (MOGDM) approach has been proposed to select the best partner combination. Finally, a numerical example has been presented to demonstrate the validity of the model and method. Journal: Int. J. of Manufacturing Technology and Management Pages: 1-12 Issue: 1 Volume: 36 Year: 2022 Keywords: partner selection; virtual enterprise; fuzzy completion time; fuzzy due date. File-URL: http://www.inderscience.com/link.php?id=121612 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:1:p:1-12 Template-Type: ReDIF-Article 1.0 Author-Name: Bo Peng Author-X-Name-First: Bo Author-X-Name-Last: Peng Title: Research on operation stability evaluation of industrial automation system based on improved deep learning Abstract: In order to overcome the problems of low evaluation accuracy, long evaluation time and high data extraction error of traditional methods, an evaluation method of industrial automation system operation stability based on improved deep learning is proposed. This paper analyses the key indicators of industrial automation system operation stability evaluation, activates the sample data with the help of binary cross entropy function, and obtains the partial derivative of artificial neural network to complete the improvement of artificial neural network. The running characteristics of industrial automation system are extracted, and the feature data are de-noising with the help of self-encoder. These data are input into the improved artificial neural network, and the evaluation results are output. The experimental results show that the highest evaluation accuracy of the proposed method is about 96%, the evaluation time is less than 0.6 s, and the error of feature data extraction is only 2.1%. Journal: Int. J. of Manufacturing Technology and Management Pages: 141-153 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: improved deep learning; industrial automation system; stability evaluation; binary cross entropy function; self-encoder. File-URL: http://www.inderscience.com/link.php?id=123660 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:141-153 Template-Type: ReDIF-Article 1.0 Author-Name: Yan Sun Author-X-Name-First: Yan Author-X-Name-Last: Sun Title: Optimisation design of reverse logistics network based on hybrid genetic algorithm Abstract: Traditional enterprise reverse logistics network optimisation has problems of low sales profit and low asset income rate. A new hybrid genetic algorithm is proposed to optimise it. First, this paper determines the influencing factors of reverse logistics network optimisation. Then constructs an enterprise reverse logistics network model and designs the decomposition and coordination algorithm that divides this reverse network into small groups. Finally, it judges the optimisation scheme and solves the reverse logistics network model with the help of genetic algorithm to optimise. It can be seen from the comparison: through this method, the profit margin of sales and return on assets can reach 90%; it can enhance the operating profit of the enterprise. Journal: Int. J. of Manufacturing Technology and Management Pages: 154-167 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: hybrid genetic algorithm; reverse logistics network; network model; decomposition coordination algorithm; genetic algorithm. File-URL: http://www.inderscience.com/link.php?id=123661 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:154-167 Template-Type: ReDIF-Article 1.0 Author-Name: Renxing Wen Author-X-Name-First: Renxing Author-X-Name-Last: Wen Title: Optimisation method for NC machining parameters of mechanical mould based on artificial neural network Abstract: In order to overcome the problems of low production profit and high processing cost existing in traditional methods, an optimisation method for NC machining parameters of mechanical mould based on artificial neural network is proposed. Considering the cutting speed, feed rate, cutting depth, machine power and spindle speed in the process of NC machining of mechanical mould, the maximum profit, minimum processing cost and maximum productivity are taken as the optimisation objectives, and the objective function of NC machining parameters optimisation of mechanical mould is constructed. The NC machining parameters of mechanical mould are taken as the input of parameter optimisation model, and the artificial neural network is used to solve the model. The experimental results show that the proposed method has high production profit, low processing cost, high productivity and good practical application effect. Journal: Int. J. of Manufacturing Technology and Management Pages: 168-182 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: artificial neural network; mechanical mould; data processing; parameter optimisation; objective function. File-URL: http://www.inderscience.com/link.php?id=123662 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:168-182 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaocong Yan Author-X-Name-First: Xiaocong Author-X-Name-Last: Yan Author-Name: Feng Liu Author-X-Name-First: Feng Author-X-Name-Last: Liu Title: Intelligent colour matching method for industrial products based on firefly algorithm Abstract: In order to overcome the problem of long time consuming and low feasibility of producing colour scheme in traditional product colour matching method, this paper designs an intelligent colour matching method for industrial products based on firefly algorithm. Firstly, the colour cases of industrial products are obtained through the selection of colour matching samples, colour selection and fusion and colour case expression process. Then, based on the analysis of firefly algorithm update rules, the colour library of industrial products is established. Based on this, the coding mode and colour fitness of firefly algorithm are designed, and the intelligent colour matching of industrial products is completed by firefly individual brightness sorting and continuous iterative updating. The results show that in the experiment, the maximum time of the method to generate the colour scheme is 14.1 s, and the maximum F-measure value can reach 0.95, which proves that the method has high effectiveness. Journal: Int. J. of Manufacturing Technology and Management Pages: 183-195 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: industrial products; colour case; the colour library; firefly algorithm; coding; product colour. File-URL: http://www.inderscience.com/link.php?id=123663 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:183-195 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Xue Author-X-Name-First: Jing Author-X-Name-Last: Xue Author-Name: Jina Cui Author-X-Name-First: Jina Author-X-Name-Last: Cui Title: A cooperative game model of supply chain logistics information based on collaborative immune quantum particle swarm optimisation Abstract: Due to the problems of poor stability and low degree of cooperation in information cooperative game, a cooperative game model of supply chain logistics information based on collaborative immune quantum particle swarm optimisation is proposed. Taking the breadth and depth of supply chain logistics information sharing as the evaluation objective, the cooperative game model of supply chain logistics information is constructed by setting the cooperative conditions of game and the stable strategy of information sharing and dynamic game. The Nash equilibrium solution in the cooperative game model of supply chain logistics information is taken as the optimisation particle, the global optimal solution of the cooperative game model of supply chain logistics information is obtained, and the design of the cooperative game model of supply chain logistics information is completed. The experiment shows that the maximum stability coefficient of supply chain logistics information cooperation of the proposed model is about 0.91. Journal: Int. J. of Manufacturing Technology and Management Pages: 196-212 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: information cooperative; collaborative immune; quantum particle swarm optimisation; game theory; supply chain; logistics information; stability. File-URL: http://www.inderscience.com/link.php?id=123664 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:196-212 Template-Type: ReDIF-Article 1.0 Author-Name: Dewang Shi Author-X-Name-First: Dewang Author-X-Name-Last: Shi Title: Budget performance evaluation model of manufacturing enterprises based on triangular fuzzy multi-attribute decision making Abstract: There are some problems in the existing budget performance evaluation models, such as high budget performance evaluation error and long evaluation time. This paper proposes a budget performance evaluation model of manufacturing enterprises based on triangular fuzzy multi-attribute decision. According to the construction principle of the budget performance evaluation index system of processing and manufacturing enterprises, the budget performance evaluation index system of processing and manufacturing enterprises is constructed; the triangular fuzzy number theory is used to gather the mixed evaluation information, combined with the multi-attribute decision-making method, the multi-attribute decision-making matrix is determined, and the evaluation index weight is determined. Using evidential reasoning algorithm, using scoring function and precision function, sorting alternatives, the design of manufacturing enterprise budget performance evaluation model is realised. The results show that the minimum error of the design model is about 0.2%, and the evaluation time is about 0.5 s. Journal: Int. J. of Manufacturing Technology and Management Pages: 213-226 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: manufacturing enterprises; budget performance evaluation; performance evaluation index; score function. File-URL: http://www.inderscience.com/link.php?id=123665 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:213-226 Template-Type: ReDIF-Article 1.0 Author-Name: Huiping Chang Author-X-Name-First: Huiping Author-X-Name-Last: Chang Title: Target economic scheduling model of intelligent manufacturing products based on penalty function Abstract: In order to solve the problem that the existing target economic scheduling model of intelligent manufacturing products cannot reasonably control the number of feasible tasks, which leads to poor economic scheduling effects, a target economic scheduling model of intelligent manufacturing products based on a penalty function is proposed. Based on the overall structure of the economic dispatch model, the economic dispatch problem is described. Directed acyclic graphs were used to define the workflow of smart manufacturing products to design the best solutions. According to the established constraints, the penalty function is applied to the design of the economic dispatch model to complete the design of the economic dispatch model. Experimental results show that the scheduling time of the designed model is generally within 4 s, the scheduling cost is less than 60 yuan, and the scheduling accuracy can be maintained at about 70%, which is significantly better than the existing model. Journal: Int. J. of Manufacturing Technology and Management Pages: 227-240 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: penalty function; intelligent manufacturing product; economic dispatch model; workflow. File-URL: http://www.inderscience.com/link.php?id=123666 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:227-240 Template-Type: ReDIF-Article 1.0 Author-Name: Yulong Wan Author-X-Name-First: Yulong Author-X-Name-Last: Wan Author-Name: Xinchun Li Author-X-Name-First: Xinchun Author-X-Name-Last: Li Title: Dynamic planning method of product multimodal logistics transportation path Abstract: In order to overcome the problems of low accuracy of optimal path selection and long time of path planning existing in traditional logistics transportation path planning method, this paper designs a dynamic logistics transportation path planning method for multimodal transportation of products. A comprehensive index system of multimodal logistics transportation is constructed and fuzzy mathematics method is used to extract uncertainty evaluation factors of product multimodal transportation. According to the extraction results of uncertainty evaluation factors, a dynamic path planning model is constructed, and the genetic algorithm is used to solve the model constructed, and the results of multimodal logistics transportation path planning of products are output. The experimental results show that the optimal path selection accuracy of the proposed method is always above 98%, and the average path planning time is 0.76 s. The path planning effect is good, and it can be further extended in practice. Journal: Int. J. of Manufacturing Technology and Management Pages: 241-256 Issue: 2/3/4 Volume: 36 Year: 2022 Keywords: product multimodal transport; logistics transportation route; path dynamic planning; genetic algorithm. File-URL: http://www.inderscience.com/link.php?id=123667 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:2/3/4:p:241-256 Template-Type: ReDIF-Article 1.0 Author-Name: Abhijit Saha Author-X-Name-First: Abhijit Author-X-Name-Last: Saha Author-Name: Subhas Chandra Mondal Author-X-Name-First: Subhas Chandra Author-X-Name-Last: Mondal Title: Modelling bead width and bead hardness in submerged arc welding using dimensional analysis Abstract: The submerged arc welding (SAW) process finds wide industrial application due to its easy applicability, high current density and ability to deposit a large amount of weld metal using more than one wire at the same time. This paper presents the application of two techniques, namely, Rayleigh's dimensional analysis for modelling and grey relational analysis (GRA) for multi-objective optimisation for bead width and bead hardness in SAW based on welding parameters such as, welding current, arc voltage, welding speed and electrode stick out respectively. Based on the experimental result, it was concluded that GRA is suitable for the optimisation of multi-response problem. The best-fitting curves were obtained for experimentally observed values of both bead width and bead hardness on the basis of the Rayleigh's model. The comparison with experimental results will also served as further validation of the model. The proposed methodology can be applied to other manufacturing processes dealing multivariate data. Journal: Int. J. of Manufacturing Technology and Management Pages: 13-27 Issue: 1 Volume: 36 Year: 2022 Keywords: submerged arc welding; SAW; Rayleigh's theorem; dimensional analysis; grey relational analysis; GRA; bead width; bead hardness. File-URL: http://www.inderscience.com/link.php?id=121578 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:1:p:13-27 Template-Type: ReDIF-Article 1.0 Author-Name: Narendra Kumar Author-X-Name-First: Narendra Author-X-Name-Last: Kumar Author-Name: Prashant K. Jain Author-X-Name-First: Prashant K. Author-X-Name-Last: Jain Title: Extrusion-based additive manufacturing systems: current state, parameters optimisation, materials, research gap, challenges and future potential Abstract: In recent years, additive manufacturing (AM) has seen tremendous growth due to its capability of fabricating parts directly from CAD model with high geometric complexities. Among all available AM systems, the extrusion-based systems are popular than others due to their low-cost and simple design. Different variants of extrusion-based AM systems have been developed worldwide. The current article reviews the research trends in extrusion-based AM systems on process parameter optimisation, material development, system variants and their limitations. This review also highlights the present scenario, research gap, challenges and future possibilities of these techniques. Journal: Int. J. of Manufacturing Technology and Management Pages: 28-64 Issue: 1 Volume: 36 Year: 2022 Keywords: additive manufacturing; 3D printing; layered manufacturing; extrusion; optimisation; materials; pellet; filament. File-URL: http://www.inderscience.com/link.php?id=121580 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:36:y:2022:i:1:p:28-64