Due to the outbreak of the COVID-19 pandemic, the manufacturing sector has been experiencing unprecedented issues, including severe fluctuation in demand, restrictions on the availability and utilization of the workforce, and governmental regulations. Adopting conventional manufacturing practices and planning approaches under such circumstances cannot be effective and may jeopardize workers' health and satisfaction, as well as the continuity of businesses. Reconfigurable Manufacturing System (RMS) as a new manufacturing paradigm has demonstrated a promising performance when facing abrupt market or system changes. This paper investigates a joint workforce planning and production scheduling problem during the COVID-19 pandemic by leveraging the adaptability and flexibility of an RMS. In this regard, workers' COVID-19 health risk arising from their allocation, and workers' preferences for flexible working hours are incorporated into the problem. Accordingly, first, novel Mixed-Integer Linear Programming (MILP) and Constraint Programming (CP) models are developed to formulate the problem. Next, exploiting the problem's intrinsic characteristics, two properties of an optimal solution are identified. By incorporating these properties, the initial MILP and CP models are considerably improved. Afterward, to benefit from the strengths of both improved models, a novel hybrid MILP-CP solution approach is devised. Finally, comprehensive computational experiments are conducted to evaluate the performance of the proposed models and extract useful managerial insights on the system flexibility.

• Klíčová slova
• COVID-19 pandemic, Constraint programming, Reconfigurable machine tool, Reconfigurable manufacturing system, Scheduling, Workforce planning,
• Publikační typ
• časopisecké články MeSH

Combating the COVID-19 pandemic has raised the demand for and disposal of personal protective equipment in the United States. This work proposes a novel waste personal protective equipment processing system that enables energy recovery through producing renewable fuels and other basic chemicals. Exergy analysis and environmental assessment through a detailed life cycle assessment approach are performed to evaluate the energy and environmental sustainability of the processing system. Given the environmental advantages in reducing 35.42% of total greenhouse gas emissions from the conventional incineration and 43.50% of total fossil fuel use from landfilling processes, the optimal number, sizes, and locations of establishing facilities within the proposed personal protective equipment processing system in New York State are then determined by an optimization-based site selection methodology, proposing to build two pre-processing facilities in New York County and Suffolk County and one integrated fast pyrolysis plant in Rockland County. Their optimal annual treatment capacities are 1,708 t/y, 8,000 t/y, and 9,028 t/y. The proposed optimal personal protective equipment processing system reduces 31.5% of total fossil fuel use and 35.04% of total greenhouse gas emissions compared to the personal protective equipment incineration process. It also avoids 41.52% and 47.64% of total natural land occupation from the personal protective equipment landfilling and incineration processes.

• Klíčová slova
• CAPEX, Capital expenditure, Fossil fuel reduction, GAO US, Government Accountability Office, GHG emissions, GHG, Greenhouse gas, GWP, Global warming potential, HEPA, High-Efficiency Particulate Arrestance, HEX, Heat exchangers, HP, High-pressure steam, LCA, Life cycle assessment, LCI, Life cycle inventory, LP, Low-pressure steam, Life cycle assessment, MEA, Monoethanolamine, MILP, Mixed-integer linear programming, MINLP, Mixed-integer nonlinear programming, MP, Mid-pressure steam, MSDS, Material Safety Data Sheet, NMVOC, Non-methane volatile organic compound, NPV, Net present value, NYS, New York State, O&M, Operation and maintenance cost, OPEX, Operating expenditure, PPE processing system, PPE, Personal protective equipment, PSA, Pressure-swing adsorption, Process design, SD, Solid waste disposal fee MUSD, TEA, Techno-economic analysis, Techno-economic analysis, fec, Feedstock cost MUSD, inc, revenue from downstream products MUSD, obj, Annualized cost MUSD, omc, Operation and maintenance cost MUSD, stor, The total storage cost MUSD, tci, Total capital cost MUSD, tran, Total transportation cost MUSD, uc, Total utility cost MUSD,
• Publikační typ
• časopisecké články MeSH