Inventory Optimization Using FSN Analysis in Spare Parts Planning

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.