Advancements in Sustainable Manufacturing Supply Chain Modelling: a Review

被引:0
作者
Ovundah K. Wofuru-Nyenke
Tobinson A. Briggs
Daniel O. Aikhuele
机构
[1] University of Port Harcourt,Department of Mechanical Engineering
来源
Process Integration and Optimization for Sustainability | 2023年 / 7卷
关键词
Manufacturing; Supply chain; Simulation; Modelling; Literature review;
D O I
暂无
中图分类号
学科分类号
摘要
Managers at various echelons of supply chains are continuously faced with problems of examining and improving supply chain processes with the aim of improving productivity and customer service level, while reducing emissions and total costs simultaneously. This study is aimed at presenting the trends in sustainable manufacturing supply chain modelling in order to establish the modelling approaches which have predominantly been used for improving manufacturing supply chains from years 2010 to 2020. The study employs the systematic literature review methodology for reviewing articles published within the 11-year period. We proffer a classification approach for manufacturing supply chain models, grouping these models into mathematical models, simulation models, hybrid models, and their subcategories. The results showed that though there is a rising trend in the use of simulation and hybrid models, mathematical models have been used more for sustainable manufacturing supply chain modelling. The rise in the use of simulation and hybrid models can be explained by the fact that these models tend to handle uncertain and stochastic data better than mathematical models, which perform better with deterministic data. This research will aid other researchers in recognising the current gaps in manufacturing supply chain modelling in order to identify future research directions.
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页码:3 / 27
页数:24
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共 678 条
[1]  
Aalaei A(2017)A robust optimization model for cellular manufacturing system into supply chain management Int J Prod Econ 183 667-679
[2]  
Davoudpour H(2019)A system dynamics approach to investigate the effects of disruption on the supply chain with a mitigation strategy IOP Conf Ser: Mater Sci Eng 697 012024-3795
[3]  
Abdullah M(2018)Simulation-based optimization of a stochastic supply chain considering supplier disruption: agent-based modeling and reinforcement learning Scientia Iranica 26 3780-1003
[4]  
Hishamuddin H(2019)An integrated chance-constrained stochastic model for a mobile phone closed-loop supply chain network with supplier selection J Clean Prod 226 988-42
[5]  
Bazin N(2011)A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty Int J Prod Econ 134 28-41
[6]  
Aghaie A(2013)A stochastic aggregate production planning model in a green supply chain: considering flexible lead times nonlinear purchase and shortage cost functions Eur J Oper Res 230 26-196
[7]  
Heidary MH(2017)A multi-scale agent-based modelling framework for urban freight distribution Trans Res Procedia 27 188-576
[8]  
Ahmadi S(2020)A discrete event simulation analysis of the bullwhip effect in a multi-product and multi-echelon supply chain of fast moving consumer goods Pakistan J Stat Operation Res 16 561-137
[9]  
Amin SH(2020)Reverse logistics optimization of an industrial air conditioner manufacturing company for designing sustainable supply chain: a fuzzy hybrid multi-criteria decision-making approach Wireless Netw 8 122-8
[10]  
Al-e-hashem SMJM(2014)Developing a fuzzy linear programming model for locating recovery facility in a closed loop supply chain Int J Sustain Eng 40 1-6550