Effective spare parts inventory management is a cornerstone of operational efficiency in service-intensive industries. In the elevator and lift sector, the availability of the right spare part at the right time directly determines service continuity, customer satisfaction, and maintenance cost. This study investigates the application of FSN (Fast, Slow, and Non-Moving) Analysis as a systematic inventory classification technique for optimizing spare parts planning in the Indian elevator industry. Drawing on secondary inventory data comprising 329 stock-keeping units (SKUs) collected over a twelve-month period from a pneumatic vacuum home-lift manufacturer based in Chennai, the research classifies spare parts into three movement-based categories and derives category-specific inventory control policies. Complementary ABC and VED analyses are also employed to provide value-based and criticality-based perspectives. The FSN classification reveals that 46 items (13.98%) are Fast-Moving, 67 items (20.36%) are Slow-Moving, and a striking 216 items (65.65%) are Non-Moving, indicating significant capital blockage in idle inventory. The ABC analysis identifies 23 high-value Class A items driving approximately 70% of annual consumption, while the VED analysis highlights several safety-critical Vital components requiring zero stock-out tolerance. The integrated FSN–ABC–VED framework provides a robust, multi-dimensional foundation for spare parts inventory optimization. The study contributes to the under-researched domain of inventory management in the Indian home-lift and elevator sector, offering practical, implementable recommendations for reducing inventory carrying costs, improving warehouse utilization, and strengthening service reliability.
G et al. (Tue,) studied this question.
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