Towards a simulation-based optimization approach to integrate supply chain planning and control

Pires, Matheus Cardoso; Frazzon, Enzo Morosini; Danielli, Apolo M. Carreirão; Kück, Mirko; Freitag, Michael

doi:10.1016/j.procir.2018.03.288

Cited by 15 publications

(4 citation statements)

References 26 publications

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“…Some researchers have combined mathematical and simulation-based optimisation for planning and maximising profit of multi-period, multi-echelon, and multi-product supply chain networks (Chiadamrong and Piyathanavong 2017 ; Ji and Chiadamrong 2019 ; Pires et al 2018 ; Sitek et al 2014 ). Salem and Haouari ( 2016 ) developed a hybrid simulation-optimisation framework for studying a three-echelon stochastic supply chain network having uncertain demand and supply, aiming to minimise total cost.…”

Section: Results Of the Systematic Literature Reviewmentioning

confidence: 99%

Advancements in Sustainable Manufacturing Supply Chain Modelling: a Review

Wofuru-Nyenke

Briggs

Aikhuele

2022

Process Integr Optim Sustain

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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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Section: Results Of the Systematic Literature Reviewmentioning

confidence: 99%

Advancements in Sustainable Manufacturing Supply Chain Modelling: a Review

Wofuru-Nyenke

Briggs

Aikhuele

2022

Process Integr Optim Sustain

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“…They developed a multi-objective simulation-based optimization model to solve the problem of inventory replenishment with premium freight in convergent supply chains by minimizing the total inventory cost, and setting the inbound and outbound premium freight ratios. Pires et al (2018) studied a simulation-based optimization approach to integrate supply chain planning and control. They developed adaptive simulation-based optimization and Industry 4.0 technologies to integrate manufacturing supply chain planning tasks.…”

Section: Optimization In Supply Chain Master Planningmentioning

confidence: 99%

Fuzzy multi-objective optimization with α-cut analysis for supply chain master planning problem

Sutthibutr¹,

Chiadamrong²

2019

10.5267/j.uscm

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This study considers a supply chain master planning problem in an uncertain environment where operating costs, customer demand, production capacity, manufacturer's acceptable defective rate, and manufacturer's acceptable service level are uncertain. Our supply chain consists of one manufacturer, multiple suppliers, and multiple distribution centers. While one objective is to minimize the total costs of logistics that consists of purchasing cost, production cost, and distribution cost, the other objective is to maximize total value of purchasing. These objectives are in conflict with each other. In this paper, the fuzzy multi-objective linear model is applied with-Cut analysis to achieve the optimal supply chain master planning in an uncertain environment by balancing these two conflicting objectives. The-Cut analysis is introduced to ensure decision-makers that the outcome satisfies their preferences based on a specified minimum allowed satisfaction value ().

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“…Firms must manufacture high-quality, reasonably-priced products that satisfy the needs of various customers, while simultaneously meeting delivery times. For this purpose, researchers have been actively investigating the application of smart manufacturing (SM) technology to improve productivity as well as the optimal use of manufacturing resources in dynamic environments [4,5]. SM is a collection of advanced technologies that facilitate effective and accurate real-time decision-making by combining various information and communication technologies (ICTs) with the existing manufacturing industry [6].…”

Section: Introductionmentioning

confidence: 99%

Integrated Platform and Digital Twin Application for Global Automotive Part Suppliers

Yang¹,

Lee²,

Kang³

et al. 2020

IFIP Advances in Information and Communication Technology

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For global automakers that manufacture products through a globally distributed supply chain, it is essential for this supply chain to be managed efficiently to enhance the efficiency and responsiveness to uncertain changes in the market. These manufacturers face limitations associated with independent applications, such as difficulties in collecting information from distributed sites and the inability to make quick decisions. To solve this problem, researchers have been actively investigating the application of smart manufacturing technology to improve productivity as well as the optimal use of manufacturing resources in dynamic environments. Furthermore, different countries have different cultures, regulations, and policies. Hence, a universal integrated platform is required to address these difficulties. Accordingly, this study proposes an integrated cyberphysical system-based platform that reflects international standards and has versatile applications. This platform can be used to utilize information from various distributed manufacturing sites in real time. In addition, the proposed system was verified through a field application case study.

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Towards a simulation-based optimization approach to integrate supply chain planning and control

Cited by 15 publications

References 26 publications

Advancements in Sustainable Manufacturing Supply Chain Modelling: a Review

Advancements in Sustainable Manufacturing Supply Chain Modelling: a Review

Fuzzy multi-objective optimization with α-cut analysis for supply chain master planning problem

Integrated Platform and Digital Twin Application for Global Automotive Part Suppliers

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