Determination of optimal order-up to level quantities for dependent spare parts using data mining

• Association rule technique is used for finding dependency among spare parts.
• Developed a two item periodic review inventory policy considering dependency.
• Shortage of one spare can cause decline in the demand rate of other spare parts.
• Shortage of one spare can affect the holding and shortage of cost of the other spare parts.

Consumable spare parts play an important role during regular and periodic maintenance activities depending on equipment criticality of a manufacturing firm. Usually, these spare parts are consumed together on a regular basis to different equipment with a high percentage of commonality. Complete or partial shutdown of maintenance activity may happen if there is shortages in any of these common parts and at the same time, maintaining a high inventory of these parts lead to more cost. If there is a shortage of a spare part, then there is a chance that other dependent spares may remain as idle inventory and incur the opportunity cost. In this paper, a noble approach is adopted to incorporate dependency of items in periodic review (T, S) policy to determine the optimal stock of dependent spare parts considering common cycle time and fill rate for each spares. Our results show that there is considerable reduction of stock level and total cost of inventory when associated spares are considered together for management of inventory instead of considering them individually. Finally, the developed model is applied to a case company.