Pub Date : 2023-04-03DOI: 10.1142/s0219686723500324
Arman Bahari, Sattar Nouri, Behnoosh Moody
In recent decades, the use of supply chain management is essential for developing new technologies and setting the ground in expanding major global markets to integrate suppliers, manufacturers, warehouses, and stores effectively. In addition, the growing competition in the modern business environment has created an increasing trend of new products and improved product quality for attracting more consumers. However, an increase in the related costs and uncertainty in these innovations requires the development of algorithms to solve optimization problems. Therefore, this study is aimed to implement a multi-product supply chain including raw material suppliers, factories, distributors, and customers to maximize the quality and minimize costs. To this aim, supplier quality, distribution centers, and manufacturing products were considered for the quality model, while warehousing costs, product production, transportation, defective raw materials, and the like were regarded for the cost model. Then, the NSGAII algorithm was used for solving the created optimization problem, and accordingly, the optimal Pareto points were calculated. Based on the results, the proposed model can give the manufacturer the ability to decide on a multi-product and multi-time supply chain by involving cost and quality variables. Thus, the owner can manage the supply chain of the factory effectively.
{"title":"Supply Chain Optimization under Risk and Uncertainty using Nondominated Sorting Genetic Algorithm II for Automobile Industry","authors":"Arman Bahari, Sattar Nouri, Behnoosh Moody","doi":"10.1142/s0219686723500324","DOIUrl":"https://doi.org/10.1142/s0219686723500324","url":null,"abstract":"In recent decades, the use of supply chain management is essential for developing new technologies and setting the ground in expanding major global markets to integrate suppliers, manufacturers, warehouses, and stores effectively. In addition, the growing competition in the modern business environment has created an increasing trend of new products and improved product quality for attracting more consumers. However, an increase in the related costs and uncertainty in these innovations requires the development of algorithms to solve optimization problems. Therefore, this study is aimed to implement a multi-product supply chain including raw material suppliers, factories, distributors, and customers to maximize the quality and minimize costs. To this aim, supplier quality, distribution centers, and manufacturing products were considered for the quality model, while warehousing costs, product production, transportation, defective raw materials, and the like were regarded for the cost model. Then, the NSGAII algorithm was used for solving the created optimization problem, and accordingly, the optimal Pareto points were calculated. Based on the results, the proposed model can give the manufacturer the ability to decide on a multi-product and multi-time supply chain by involving cost and quality variables. Thus, the owner can manage the supply chain of the factory effectively.","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43354937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1142/s0219686723500415
K. Mandal, M. Sekh, D. Bose, S. Mitra, S. Sarkar
{"title":"Impact of dielectric conductivityand other process parameters on machining characteristics in WEDM of al 6065 alloy","authors":"K. Mandal, M. Sekh, D. Bose, S. Mitra, S. Sarkar","doi":"10.1142/s0219686723500415","DOIUrl":"https://doi.org/10.1142/s0219686723500415","url":null,"abstract":"","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42048162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1142/s0219686723500427
D. Kalyani
{"title":"A Comprehensive Review and Open Issues on Supply Chain Management Models","authors":"D. Kalyani","doi":"10.1142/s0219686723500427","DOIUrl":"https://doi.org/10.1142/s0219686723500427","url":null,"abstract":"","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47228461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1142/s0219686723500439
Seolhui Son, J. Chung
{"title":"Evaluation of Investment Strategies for Automated Material Handling Systems in Semiconductor/Display Fabrication","authors":"Seolhui Son, J. Chung","doi":"10.1142/s0219686723500439","DOIUrl":"https://doi.org/10.1142/s0219686723500439","url":null,"abstract":"","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44714202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-17DOI: 10.1142/s0219686723500385
Suhasini Tatiparti, Kirti Mahajan, Sowmya Kethi Reddi, H. Mickle Aancy, B. Kumar
{"title":"Analyzing the Financial Risk Factors Impacting the Economic Benefits of the Consumer Electronic Goods Manufacturing Industry in India","authors":"Suhasini Tatiparti, Kirti Mahajan, Sowmya Kethi Reddi, H. Mickle Aancy, B. Kumar","doi":"10.1142/s0219686723500385","DOIUrl":"https://doi.org/10.1142/s0219686723500385","url":null,"abstract":"","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45824837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1142/s0219686723500063
Yongfei Li, Jin Zhang, Guiying He, Songbo Wei, Yu Zhang, Abdul Rehman
In recent years, environmental pollution and resource waste have become the focus of heated discussion around the world. In order to realize green and sustainable development, the development of green supply chain (GSC) has attracted the attention of many scholars. The research object of this paper is the dual-channel green supply chain (DGSC) composed of online channels and offline channels. The supplier is the leader of the entire DGSC, and it needs to optimize the wholesale price of the product and the level of green investment to maximize its own benefit. In addition, the supplier also needs to establish contracts with network sales platform (NSP) and store sales platform (SSP) to increase the benefit of NSP and SSP, and ultimately increase the benefit level of the entire DGSC. Among them, we constructed a centralized decision (CD) model and a decentralized decision (DD) model, and obtained the optimal pricing, optimal greenness and optimal benefit of the supplier, NSP and SSP under the two models. We found that the benefits of SC members under the DD model are generally lower than those of the CC model. Therefore, we built contracts between the supplier, NSP and SSP to coordinate. Finally, we substituted specific parameters to verify the model. The following conclusions are drawn: (i) When consumers prefer online sales channels, it will positively affect the online sales price, online sales volume and greenness level of DGSC. At the same time, it negatively affects offline sales price and sales volume. (ii) The benefit of DGSC and the benefit of NSP, SSP, and the supplier show a phenomenon of decline first and then increase with respect to consumers’ preference for online sales channels. (iii) Under the coordination contract, the subsidy factor positively affects the benefits of the supplier and online and offline wholesale prices, and negatively affects the benefits of online platforms and physical stores.
{"title":"Research on Pricing and Coordination of Dual-Channel Green Supply Chain","authors":"Yongfei Li, Jin Zhang, Guiying He, Songbo Wei, Yu Zhang, Abdul Rehman","doi":"10.1142/s0219686723500063","DOIUrl":"https://doi.org/10.1142/s0219686723500063","url":null,"abstract":"In recent years, environmental pollution and resource waste have become the focus of heated discussion around the world. In order to realize green and sustainable development, the development of green supply chain (GSC) has attracted the attention of many scholars. The research object of this paper is the dual-channel green supply chain (DGSC) composed of online channels and offline channels. The supplier is the leader of the entire DGSC, and it needs to optimize the wholesale price of the product and the level of green investment to maximize its own benefit. In addition, the supplier also needs to establish contracts with network sales platform (NSP) and store sales platform (SSP) to increase the benefit of NSP and SSP, and ultimately increase the benefit level of the entire DGSC. Among them, we constructed a centralized decision (CD) model and a decentralized decision (DD) model, and obtained the optimal pricing, optimal greenness and optimal benefit of the supplier, NSP and SSP under the two models. We found that the benefits of SC members under the DD model are generally lower than those of the CC model. Therefore, we built contracts between the supplier, NSP and SSP to coordinate. Finally, we substituted specific parameters to verify the model. The following conclusions are drawn: (i) When consumers prefer online sales channels, it will positively affect the online sales price, online sales volume and greenness level of DGSC. At the same time, it negatively affects offline sales price and sales volume. (ii) The benefit of DGSC and the benefit of NSP, SSP, and the supplier show a phenomenon of decline first and then increase with respect to consumers’ preference for online sales channels. (iii) Under the coordination contract, the subsidy factor positively affects the benefits of the supplier and online and offline wholesale prices, and negatively affects the benefits of online platforms and physical stores.","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136131245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-17DOI: 10.1142/s0219686723500397
Parisa Hajialirezaei, Seyed Hamid Reza Pasandideh
{"title":"A two-warehouse lot sizing problem for defective items with a completely backlogged shortage under limited storage capacity for rented warehouses","authors":"Parisa Hajialirezaei, Seyed Hamid Reza Pasandideh","doi":"10.1142/s0219686723500397","DOIUrl":"https://doi.org/10.1142/s0219686723500397","url":null,"abstract":"","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44070670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-28DOI: 10.1142/s0219686723500336
S. Vyavahare, Soham Teraiya, Shailendra Kumar
This paper describes an experimental study on re-entrant auxetic structures manufactured by fused deposition modeling (FDM). The feedstock materials of NPR structures are acrylonitrile butadiene styrene (ABS) and poly-lactic acid (PLA). Experimental study is performed to examine the effect of design factors (angle, width, and length of arm) of unit cell of auxetic structures on three responses namely strength, stiffness, and specific energy absorption (SEA) under flexural loading. From the experimental results, it is found that flexural strength improves with increase in all three design factors of ABS structures; while it improves with increase in angle and reduction in width and length of arm for PLA structures. Furthermore, based on experimental study, regression models of responses are developed using analysis of variance (ANOVA). Also, machine learning (ML) models using neural networks are developed to predict all three responses. Results of regression models are compared with NN models to assess accuracy of prediction. Finally, optimal configuration of auxetic structure is determined using gray relational analysis (GRA) to improve the responses; and reduce weight and fabrication time.
{"title":"Machine Learning and Regression Analysis Approaches for Investigation of Mechanical Properties of FDM Manufactured Re-Entrant Auxetic Structures Under Flexural Loading","authors":"S. Vyavahare, Soham Teraiya, Shailendra Kumar","doi":"10.1142/s0219686723500336","DOIUrl":"https://doi.org/10.1142/s0219686723500336","url":null,"abstract":"This paper describes an experimental study on re-entrant auxetic structures manufactured by fused deposition modeling (FDM). The feedstock materials of NPR structures are acrylonitrile butadiene styrene (ABS) and poly-lactic acid (PLA). Experimental study is performed to examine the effect of design factors (angle, width, and length of arm) of unit cell of auxetic structures on three responses namely strength, stiffness, and specific energy absorption (SEA) under flexural loading. From the experimental results, it is found that flexural strength improves with increase in all three design factors of ABS structures; while it improves with increase in angle and reduction in width and length of arm for PLA structures. Furthermore, based on experimental study, regression models of responses are developed using analysis of variance (ANOVA). Also, machine learning (ML) models using neural networks are developed to predict all three responses. Results of regression models are compared with NN models to assess accuracy of prediction. Finally, optimal configuration of auxetic structure is determined using gray relational analysis (GRA) to improve the responses; and reduce weight and fabrication time.","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49028496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-20DOI: 10.1142/s0219686723500373
Aniket Nargundkar, V. Gulia, A. Khan
{"title":"Nano-Abrasives Assisted Abrasive Water Jet Machining of Bio-Composites – An Experimental and Optimization Approach","authors":"Aniket Nargundkar, V. Gulia, A. Khan","doi":"10.1142/s0219686723500373","DOIUrl":"https://doi.org/10.1142/s0219686723500373","url":null,"abstract":"","PeriodicalId":44935,"journal":{"name":"Journal of Advanced Manufacturing Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47166957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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