Optimizing Performance-Allocation Trade-Off: The Role of Human-Machine Interface Technology in Empowering Multi-skilled Workers in Industry 4.0 Factories.

Companies today face growing demands for customization, necessitating the maintenance of high quality, low cost, and short lead times. Workload management plays a crucial role in achieving these objectives, and it primarily involves two forms: input control and output control. Existing literature has significantly focused on input control while often overlooking output control. This research focuses on the critical lever of workers’ flexibility as an essential output control element and investigates its impact on lead time performance. This research focuses on recognizing workers’ flexibility as a key competitive opportunity for companies, allowing them to cope effectively with temporary job demand imbalances. Companies can optimize direct labor utilization and production lead times by reallocating workers from underloaded stations to overloaded ones, thereby driving higher profit margins and customer satisfaction. To evaluate the benefits of increased flexibility, we employ discrete-event simulation techniques demonstrating a significant reduction in lead time. Additionally, we examine the impact of limiting workers’ movement across workstations. Surprisingly, These results demonstrate that, despite reducing the number of workers’ relocations, the advantages outweigh the negative effect on lead time. Companies can achieve optimal output control strategies that enhance their overall performance by improving the trade-off between lead time and the number of workers’ relocations. Overall, this research underscores the importance of output control in workload management and highlights workers’ flexibility as a critical lever to improve lead time performance. By adopting effective output control strategies, companies can efficiently align capacity and orders, enhancing operational performance and customer satisfaction. This study provides valuable insights into the dynamics of workload management and offers practical recommendations for manufacturing organizations seeking to optimize their processes.