Availability optimization using spares modeling and the six sigma process

This paper discusses applying reliability modeling as an integral part of the six sigma improvement process for the purpose of balancing long term cost of ownership and productivity improvement within the petro-chemical industry. This is a practical yet scientific approach which has reduced the risk (production losses) caused by inadequate spare equipment stocking strategies while also considerably reducing the overall spare equipment stocking level at many of the company's facilities. The Six Sigma process also has been applied not only to "fix it right but fix it right once" to sustain the gains through the use of the MAIC (Measure, Analyze, Improve and Control) process. The paper does not discuss in detail the complexities of building and applying the simulation models which are developed to support reliability and storage optimization decisions. It does address how the simulation process is tied with the six sigma process in providing the efficiencies discussed. It is the goal of this process to have zero productivity losses with the lowest spare equipment inventories. This is the essence of the spare equipment risk equation