For an automotive manufacturer utilizing u-shaped assembly cells, production planning based on client demand presented ongoing challenges. As client requests fluctuated, the need for frequent reconfiguration of cells and operator schedules arose. Traditionally, industrial engineers conducted time studies—lasting an hour each—on assembly cells to optimize configurations and staffing. However, with a 3-shift operation, this hour-long data sampling failed to accurately represent their complex processes. This either led to understaffing and missed production goals or overstaffing and excessive labor costs.
Enter i-5O, revolutionizing the manufacturer's approach. Continuous visibility into assembly operations became a reality. Precise capacity per process per operator emerged as a strategic advantage. Armed with this granular insight, the manufacturer could streamline production planning with newfound precision.
Time and motion studies, despite their intent, yielded inaccurate and skewed data due to their infrequency and the inherent performance bias introduced when operators were observed. At best they would conduct time studies for 1 hour per week and they noticed that the operators would improve their performance when they were being watched (indicated by significant differences in production output when time studies were performed versus when they were not). The problem was exacerbated by the industry's cyclical nature, which demanded precise staffing to mitigate headcount fluctuations.
Schedule your 1st Free Consultation and Start your AI Journey Today