A medical device manufacturer facing macroeconomic headwinds realized that they needed to be more efficient in production else they would be put out of business by their competition. They had already invested in sensors to capture machine data so that they could calculate Overall Equipment Efficiency. However, when it came to their workforce, they relied on time clocks and their industrial engineers to perform time and motion studies in an attempt to know their Overall Labor Efficiency.
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.
This manufacturer deployed i-5O in their production facility to continuously monitor the cycle time of the manual processes performed by their workforce to get a better & more granular understanding of their Overall Labor Effectiveness in real-time. With data driven insights, the manufacturer was able to streamline production processes, resulting in lower rework and scrap rates. Precise knowledge empowered them to reduce labor costs significantly, maximizing efficiency and profitability.
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