Human-centered design in production aims at improving efficiency, safety, and user satisfaction by designing work environments integrating human requirements. To provide these improvements, worker assistance systems are deployed at manual workstations but there remains a gap in understanding how these systems can be effectively tailored to the diverse needs of workers. This paper presents a study on the impact of various worker assistance functions on both productivity and human-centeredness in manual assembly using a streaming analytics framework to acquire key performance indicators. The findings provide valuable insights into the effective configuration of worker assistance systems.
Hock et al. (Thu,) studied this question.
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