Sustainable spare parts inventory stock control management at macro level, using linear programming: perspective to petroleum and fertiliser industries

The goal of the study is to manage the problem in the petroleum and fertiliser sectors by optimising the overall spare parts inventory. To solve the issue, the proposed framework employs the linear programming model (LPM) and TORA software to optimise the entire spare parts inventory. This research offers petroleum and fertiliser industries a clear and straightforward way for the spare parts management. Results show improved cost and stock management that promotes sustainability with optimised data set of total spare parts inventory as 40,000 numbers and US$65.5 million. Additionally, it eliminates the excessive stock due to exaggerated risk with traditional practices and reduces deterioration by lowering long-stay of items in the warehouse. Validation of model is done using classified data sets (as HML and FSN) that are based on previous factual six years' cumulative consumption and acquired from an Indian fertiliser industry.