Production scheduling optimization for parallel machines subject to physical distancing due to COVID-19 pandemic

This paper, for the first time, presents a production scheduling model for a production line considering physical distancing between the machines' workforces. The production environment is an unrelated parallel-machine, in which for producing each part, different machines with different production rates and the required number of workers are available. We propose a three-objective mixed-integer linear programming mathematical model that aims to maximize the manufacturer's total benefit, parts' safety stock (SS) index, and the workforce's physical distance over a finite horizon (one year) by determining the optimal scheduling of the parts on the machines. Since a large production scheduling problem belongs to the Np-Hard category of problems, a non-dominated sorting genetic algorithm, and a non-dominated ranked GA algorithm are developed to solve the presented model in two stages using the empirical data from a Canadian plastic injection mold company. In the first stage, the LP-metrics approach is utilized for validating the meta-heuristics on a reduced-size problem. In the second stage, the validated meta-heuristics are utilized to optimize the company's yearly production schedule. The results indicate both metaheuristics are performing well in determining the optimal solution. Moreover, implementing physical distancing in the company reduces the company's monthly net benefit by around 9.56% compared to the normal operational conditions (without considering physical distancing).

In time of twilight, fiduciary accountable managers ensure sustainable business growth: Existing technology increases the production

Without a doubt, covid-19 caused the global trade to a standstill and price of oil to fall unprecedently. Contrary to the common belief, people are concerned about the severity of the disease and started wearing gloves. The demand for glove has increased. This study focuses on selected factories which uses existing technologies to produce gloves. Owing to the demand, gloves are exported, thus ensuring sustainable business growth. These factories use their existing machines to produce gloves. It is noted that inhouse mechanical and chemical engineers are working around the clock to innovate the existing machineries. Also, employees are encouraged to spearhead innovative ideas into the production lines. The qualitative analysis is used for this study. The finding of this paper reveals that during unprecedented times, the demand of gloves has increased globally, which concomitantly allowed locally owned companies to increase the production gloves. Ultimately, these companies are having a good time in harvesting profit and maintaining a sustainable business growth. These companies fully adhere to sustainable product and eco-friendly

Advancing Circular Economy: Research Roadmap for Circular Integrated Production Systems

The coronavirus crisis had a critical impact on supply chains and production worldwide. In particular, closed borders often prevented companies from obtaining the components required for their production. Such disruptions are the results of globalization, with suppliers spreading all over the world. The circular economy is an opportunity to overcome this challenge since components from end-of-life items may substitute supplies from afar. However, many barriers exist in the implementation of circular processes, as manufacturers perceive it as a radical change to their procedures. Therefore, we propose not to use completely new lines for the circular economy, but to use already existing systems. This paper presents the definition of circular integrated production systems (CIPS) and suggests a research roadmap for such to investigate what challenges and potentials arise, and what future research will be needed. © 2021, IFIP International Federation for Information Processing.

Optimal Product Substitution and Dual Sourcing Strategy considering Reliability of Production Lines.

Most of the supply chain literature assumes that product substitution is an effective method to mitigate supply chain disruptions and that all production lines either survive or are disrupted together. Such assumptions, however, may not hold in the real world: (1) when there is a shortfall of all products, product substitution may be inadequate unless it is paired with other strategies such as dual sourcing; and (2) production lines do not survive forever and may fail. To relax such assumptions, this paper therefore investigates the situations that the manufacturer may optimize substitution policy and dual sourcing policy to cope with supply chain disruptions. The paper obtains and compares the optimal policies for both deterministic and stochastic demands. A real-world case is also studied to verify the effectiveness of the proposed model.