Abstract

Manufacturing companies worldwide have recently experienced challenging times due to a lack of staff, materials, and components. This has mainly been caused by abrupted logistics chains and collateral effects of the last pandemic situation. Ideally, resilience engineering systems, systems that have recovery capacity from difficulties, are prepared to overcome changes in demand and disruption in production. However, lack of flexibility, adaptability, and available digital data limit the implementation of resilience systems. To overcome this problem with a high number of interrelations considering human-machine interactions, a methodology including Discrete-Event Simulation, Work Domain Analysis, and Functional Resonance Analysis Method is proposed to design, analyze, and improve complex manufacturing systems. These tools allow deeper analysis of the interrelations of the system at different abstraction levels and both with quantitative and qualitative perspectives. Going through an industrial case study, the aim is to increase the capacity and resilience of a leisure-boat manufacturing company producing highly-customized large-size products, which adds additional constraints to the problem. The objectives are to increase flexibility and productivity at the same time as maintaining high-quality product standards. The results highlight the identification of some constraints of the system such as the main production bottleneck, lack of space, and a limited number of transports, molds, and skilled personnel. The implementation and results of the methodology have proved to serve as a decision-support tool, providing insight about limitations of the system to managers and stakeholders, as well as a guideline for increasing capacity and resilience of the manufacturing process.

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