Productivity improvement remains a critical concern for manufacturing organizations facing increasing competition, cost pressures, and demand variability. Work measurement and time study techniques have long been recognized as systematic approaches to identifying inefficiencies, standardizing operations, and improving overall productivity. This study aims to analyze the effectiveness of work measurement and time study methods in improving productivity across manufacturing environments. A case-based analytical approach was employed, integrating direct observation, stopwatch time study, work sampling, and motion analysis. Standard times were calculated using performance rating and allowance factors, while bottlenecks and non-value-added activities were identified through detailed process mapping. The results indicate that the application of work measurement and time study techniques can reduce cycle time by 15–35%, improve labor productivity by 10–30%, and enhance line balance and workflow efficiency. Comparative analysis with previous empirical studies confirms the robustness of these methods across diverse industrial contexts, including machining, assembly, furniture, forging, and process industries. The study concludes that systematic work measurement and time study analysis provide practical and theoretically grounded tools for sustainable productivity improvement and operational excellence in manufacturing systems.
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