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The design and operation of complex engineering systems such as an aircraft or a refinery require substantial planning and flexibility in delivery of services and logistics support. Classical services and maintenance plans are designed on the principle that mean time between failure is a constant and hence the focus is to replace components before it is expected to fail (Armstrong, 1997). Service activities including inspection, adjustment and replacement are scheduled in fixed intervals (Chan et al, 2005). These intervals, which are prescribed by the Original Equipment Manufacturer (OEM), are often suboptimal because of deviations in the multifaceted relationship between the operating context and expectations on the complex system’s performance from the intended circumstances (Tam et al, 2006). The rigid maintenance plans are unable to unveil inherent issues in complex systems. To improve this situation, Reliability Centred Maintenance (RCM) regime has been developed to focus on reliability and safety issues (Moubray, 1997; Abdul-Nour et al, 2002). However, the process tended to ignore some secondary issues and rendered the system in sub-optimal operating conditions (Sherwin, 2005). Modern machine systems are of increasing complexity and sophistication. Focussing only on system reliability does not meet the demand on the performance of complex engineering systems due to business requirements and competitions. From the point of view of the engineering system’s owner, the system is an expensive asset that is required to fulfil certain business functions. For the purpose of discussions in this chapter, the term asset is used as synonym of a complex engineering system rather than the common understanding of a static investment. In maintenance oriented service regime, many factors are governing the operations of the asset (Colombo and Demichela, 2008). The consequences of system failures can cause losses in opportunity costs. Unfortunately, these losses are often difficult to quantify and measure. Many service decisions on assets are therefore made on rules of thumbs rather than using analysed system performance data. Replacement of assets should be made at the time when the asset is about to fail so that the value of the asset over its usable life can be utilised (Huang, 1997). The strategy is to minimise expenditure that should be spent on the asset. Many complex systems are therefore left vulnerable with high risks of failure. The performance of the asset will degrade over time as the asset gets old and technologically out-of-date. However, an expensive engineering system is expected to be in service for years. In addition, due to technology improvement, capability of the system should keep increasing in order to meet functional demand by end users (Fig. 1).

Services and Support Supply Chain Design for Complex Engineering Systems