Abstract

Offsite construction (OSC) is an innovative approach where building components (e.g., panels or modules) are manufactured in a shop floor environment, then transported to, and installed at the site. Although there are numerous benefits inherent to the OSC approach, practitioners still struggle to provide tailored projects to their clients due to the low level of flexibility in production caused by uncertainty, multiple projects, and variable market demands. Indeed, the lack of production flexibility limits shop floors to manufacture projects efficiently in an ever-changing environment, especially when processes are still labor-intensive and are not leveraged by autonomous systems, such as a digital twin (DT). Hence, this paper proposes the use of a DT to improve production on OSC shop floors by increasing flexibility, i.e., the ability to adapt to uncertainty, through the automated reassignment of multiskilled workers based on data pertaining to production status that are updated in near real-time. The present study presents key metrics adopting a lean thinking approach for waste identification that quantifies the improved production performance attributable to the proposed DT. Using simulation as a surrogate system, this research evaluates the production performance on the shop floor according to different simulated scenarios varying the number of interventions made by the DT and multiskilling configurations. Moreover, this research considers significant aspects of multiskilling such as reduced productivity, increased cost, and the time spent when moving between workstations during reassignment. The primary findings from the system’s practical application indicate a significant improvement in production due to the reduction of waiting waste, total production duration, and total production cost being reduced by 62%, 40%, and 25%, respectively. Finally, the present study presents a novel approach to increasing flexibility on shop floors while also demonstrating the benefits attributable to the use of a DT to manage multiskilled workers in OSC.

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