No abstract

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

The COVID-19 pandemic has widely disrupted manufacturing industries. This research focuses on how project management, Industry 4.0 technologies, and the Circular Economy contribute to Sustainable Supply Chain development during the pandemic. A multiple case study focusing on three companies in the metals industry, covering small-, medium-, and large-size companies from Thailand, is adopted to investigate the impact of the pandemic on companies using the dimensions of demand, production, and distribution disruptions. The result shows that project management supports Industry 4.0 technologies and Circular Economy adoption. Moreover, the COVID-19 pandemic also expedites Industry 4.0 technologies adoption. Product customization is one of the key focuses of the companies to differentiate from the competitors and create long-term competitive advantages. Industry 4.0 technologies and the Circular Economy have a positive influence on Sustainable Supply Chain development.