Abstract
The rise of automation in the manufacturing sector and the transition from traditional role-based to activity-based shop floor management systems have brought greater flexibility and skill utilisation among shop floor workers. The vast array of task choices in activity-driven environments can overwhelm employees, potentially leading to sub-optimal decisions. Moreover, determining the optimal tasks in such a dynamic environment is complicated, and there is a risk that lower-priority tasks will be neglected. In this circumstance, it is crucial to impart knowledge to the workers about the value of a task through rewards. This study advocates for using simulations to assess the impact of various reward systems on worker performance in activity-based shop floor management systems. Simulations offer a cost-efficient and risk-averse means to explore scenarios, enabling organisations to make informed decisions about reward strategies. The paper aims to compare two reward systems based solely on worker skills and another incorporating historical skill utilisation and task unacceptance ratios. The simulation results demonstrate that the reward system considering unacceptance ratios leads to reduced unacceptance of tasks and a decrease in the number of open tasks compared to the skill-based reward system. The findings of this simulation could assist manufacturing sectors in selecting the most effective reward system for their employees and could act as a preliminary investigation to understand the reward system before testing it in the real world on the shop floor.