This study optimizes labor allocation in automotive mold repair using an environmental-integrated Work Sampling method, addressing gaps in conventional time studies that often ignore contextual variables. Data were collected through 210 observations (42 per day over five days) at MWT, Ltd., incorporating environmental factors such as temperature (31°C) and vibration (0.5 m/s²). The analysis included adequacy testing (N’=168.42), uniformity checks, and standard time calculation using a Westinghouse rating factor of +0.24 and a site-specific allowance of 80.5%, validated against historical data. The results indicate a standardized repair time of 53.16 min/mold at 90% productivity, which is approximately 18% higher than values reported in previous studies due to the inclusion of environmental and competency-related factors. Simulation results suggest that implementing a two-worker shift system could potentially reduce backlog risk by 22% and improve lead time performance from 3.2 to 2.6 days. Environmental factors contributed to 30% of allowance time, revealing a previously unquantified impact. This study introduces a hybrid model integrating environmental ergonomics into non-repetitive task analysis, offering a practical framework for improving productivity, resource allocation, and maintenance efficiency in manufacturing environments.
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