Investigation of joint decision making in fleet system reliability design and maintenance planning

Abstract

Present thesis aims to investigate the joint decision making for fleet system reliability design and maintenance planning. Optimal reliability design and efficient maintenance planning are important aspects for capital-intensive industrial equipment/systems such as wind turbines, aircrafts, mining earth movers and defense systems, in which the unexpected failure creates massive repair and downtime costs. The selection of an optimal reliability design configuration and maintenance decisions are major constituent of the Life Cycle Cost (LCC) of these systems. Users of these industrial systems know this, and they increasingly take the LCC and availability into account in their purchasing decisions. As a consequence, Original Equipment Manufacturer (OEM) is now liable not only to deliver an optimal reliable design but also associated optimal maintenance decisions under Contractual Service Agreement (CSA). Mostly, OEM has multiple alternatives for various components of these systems at the early design decisions process. Designer’s job is to choose the optimal reliability design for components from the available alternatives that meets user’s budget constraints while minimizing LCC of the system. These systems are operated and maintained as a fleet and also known as fleet systems.The fleet system is generally consists of multi-indenture (i.e. assembly, module and part) equipments. These types of equipments are supported by the multi-echelon maintenance network of base, depot and OEM. This multi-echelon and the multiindenture system is known as a fleet maintenance system. In the fleet maintenance system, corrective maintenance decisions are taken based on the Level of Repair (LOR) analysis. Now, under the CSA, OEM decides optimal LOR decisions like; where i.e. at which echelon (base or depot or OEM) to perform maintenance action; at which indenture level (i.e. assembly or module or part) to perform the maintenance action and what maintenance actions (i.e., repair or move or discard) to perform on the selected indenture level. The LOR analysis is generally done to decide these variables such that the LCC of the fleet maintenance system is minimized. Moreover, for the effective maintenance planning, the availability of the spare parts plays a significant role in makingeffective LOR decisions. Besides of that, industries also perform preventive maintenance to reduce the failure rate of the components and increase the life of such industrial system. Therefore, the LOR, PM and the spare level are important decisions in fleet maintenance planning.Usually, optimal reliability design and LOR decisions are taken sequentially or independently, i.e., first design is selected, and then the LOR is decided. On the other hand, maintenance planning aspects i.e. spare parts stocking and preventive maintenance, the degree of restoration also have interdependencies with LOR decisions. Additionally, simplistic assumptions are taken during the LOR optimization in the existing literature. Such as, the constant failure rate assumption is used during LOR optimization. It does not allow consideration of the degree of repair during the LOR decisions such as repair/discard. Also, it does not reflect the actual life behavior of the components. The consideration of time-dependent failure rate of the components while optimizing the level of repair and spare parts stocking decisions is not done in the available literature. Besides, such equipment also receives preventive maintenance during the useful life of the equipment. However, the effect of PM during LOR decisions is not studied in the literature. This is mainly due to constant failure rate assumption and complexities to estimating the number of failures of the multi-indenture systems with time dependent failure rate of parts. In existing literature no work is found that considers the effect of preventive maintenance while optimizing the LOR decisions. While optimizing the LCC of the fleet maintenance system, a detailed LCC model to investigate the effect of various costs parameters i.e. maintenance facility cost, consumable cost, downtime cost, transportation cost and spare holding cost and stock-out cost is required. Such models are not elaborated adequately in literature.