Based on revenue, Intel is one of the world's largest and highest valued makers of semiconductor chips.
Intel factories used a particular type of equipment that often broke down, which caused capacity constraints. If the equipment was repairable, it would be fixed by Intel factory technicians or, if the problem was too complex, it was sent to the supplier’s repair center. These expensive parts were used in critical factory operations, and the repairs took significant time, so it was necessary to have extra spare parts on hand to avoid downtimes. Broken parts caused constraints at some of the factories while other factories over purchased spares.
Intel’s commodity managers worked to determine the root cause of the problem and ways to solve it. They needed data to understand how many spare parts the company needed to keep the factories running without overbuying them.
To support the negotiation process with the equipment supplier, they built a simple simulation model. The model was a standalone application with a user interface that could be utilized to input various parameters and test “what-if” scenarios.
The model helped the managers understand how many spare parts had to be purchased to avoid equipment downtime due to lack of these parts, as well as to avoid significantly overbuying the spares, while taking into account various failure rate scenarios.
As the repair centers sometimes got overwhelmed with incoming orders, the managers were also able to understand how changing local and at-supplier repair center staffing and capacity helped solve the problem.
This simple model was built and used for only a few days. It was used to support negotiations with the equipment vendors to convince them to provide Intel with additional spare parts’ consignments at no cost. This allowed Intel to achieve significant savings with little effort.