Assessment the effect of rapid prototyping implementation on supply chain sustainability: a system dynamics approach

Arian, Nazanin Hosseini; Pooya, Alireza; Rahimnia, Fariborz; Sibevei, Ali

doi:10.1007/s12063-021-00228-6

Cited by 8 publications

(1 citation statement)

References 88 publications

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“…Sustainable supplier selection in automotive industry [148] Data from expert interviews used, simulated using SD in fuzzy environment in VENSIM to find the best potential sustainable supplier Strategic Effect of rapid prototyping implementation on SC sustainability [200] A generic SD model simulating the RP-adapted SC. Using VENSIM software and modeling economic, social and environmental KPIs Tactical Sustainable supplier management [201] A virtual warehouse simulated using VENSIM.…”

Section: Strategicmentioning

confidence: 99%

Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy

Khan

Abonyi

2022

Sustainability

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At the current worrisome rate of global consumption, the linear economy model of producing goods, using them, and then disposing of them with no thought of the environmental, social, or economic consequences, is unsustainable and points to a deeply flawed manufacturing framework. Circular economy (CE) is presented as an alternative framework to address the management of emissions, scarcity of resources, and economic sustainability such that the resources are kept ‘in the loop’. In the context of manufacturing supply chains (SCs), the 6R’s of rethink, refuse, reduce, reuse, repair, and recycle have been proposed in line with the achievement of targeted net-zero emissions. In order to bring that about, the required changes in the framework for assessing the state of manufacturing SCs with regard to sustainability are indispensable. Verifiable and empirical model-based approaches such as modeling and simulation (M&S) techniques find pronounced use in realizing the ideal of CE. The simulation models find extensive use across various aspects of SCs, including analysis of the impacts, and support for optimal re-design and operation. Using the PRISMA framework to sift through published research, as gathered from SCOPUS, this review is based on 202 research papers spanning from 2015 to the present. This review provides an overview of the simulation tools being put to use in the context of sustainability in the manufacturing SCs, such that various aspects and contours of the collected research articles spanning from 2015 to the present, are highlighted. This article focuses on the three major simulation techniques in the literature, namely, Discrete Event Simulation (DES), Agent-Based Simulation (ABS), and System Dynamics (SD). With regards to their application in manufacturing SCs, each modeling technique has its pros and its cons which are evinced in case of data requirement, model magnification, model resolution, and environment interaction, among others. These limitations are remedied through use of hybrids wherein two or more than two modeling techniques are applied for the desired results. The article also indicates various open-source software solutions that are being employed in research and the industry. This article, in essence, has three objectives. First to present to the prospective researchers, the current state of research, the concerns that have been presented in the field of sustainability modeling, and how they have been resolved. Secondly, it serves as a comprehensive bibliography of peer-reviewed research published from 2015–2022 and, finally, indicating the limitations of the techniques with regards to sustainability assessment. The article also indicates the necessity of a new M&S framework and its prerequisites.

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Section: Strategicmentioning

confidence: 99%

Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy

Khan

Abonyi

2022

Sustainability

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Exploring the adoption and long-term effects of ChatGPT in a sustainable supply chain

Roozkhosh,

Pooya,

Modares

et al. 2024

Flex Serv Manuf J

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Blockchain acceptance rate prediction in the resilient supply chain with hybrid system dynamics and machine learning approach

2022

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In today’s era, the importance and implementation of blockchain networks have become feasible as it improves the resilience of the supply chain network at all levels by clarifying information and creating security in the network, improving the speed of response, and gaining the trust of customers. This paper aims to investigate the behavior of the blockchain acceptance rate (BAR) in the home appliances flexible supply chain in Iran using. system dynamics (SD), which is used to better define the relationships between the variables of the model that are non-linearly connected. Through simulating the behavior of the BAR in the long term in the supply chain, whilst conducting sensitivity analysis, policy design, and validation, this model will be implemented for the years 2020 to 2030. Additionally, post-simulation, blockchain acceptance behavior will be assessed by having simulated data considered as input for studied Multi-Layer Perceptron (MLP) and Vector Regression (SVR) (data that have the highest correlation with BAR). The acceptance rate behavior is predicted with the help of machine learning methods to have the best behavior and prediction for the data of 2020-2022 since the prediction function is compared to daily real data obtained these years. The results show that in 2030, the BAR will be around 0.6 if the COVID-19 outbreak impact is medium, and if the considered policy designs are implemented, this rate will reach a maximum of 0.8. So paying attention to the creation and design of policies can achieve positive implications for increasing the resilience of the supply chain in the long run. Findings suggest that the SD-MLP method is better than the SD-SVR method as it has less error and can predict the better behavior of the BAR.

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Assessment the effect of rapid prototyping implementation on supply chain sustainability: a system dynamics approach

Cited by 8 publications

References 88 publications

Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy

Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy

Exploring the adoption and long-term effects of ChatGPT in a sustainable supply chain

Blockchain acceptance rate prediction in the resilient supply chain with hybrid system dynamics and machine learning approach

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