Abstract
This paper presents an online simulation framework that can be used to support operational decisions within the context of Through-life Engineering Services. Acting as a closed-loop feedback control mechanism, the simulation model is physically coupled to the assets and will be triggered and automatically executed to assess a set of operational decisions related to maintenance scheduling, resource allocation, spare parts inventory etc. Experimental cases comparing the online simulation against the traditional approach will also be presented. The outcomes have demonstrated the prospects of the framework in enabling more effective/efficient operations of engineering services leading to high assets availability and reduced through-life costs.
Introduction
The last decade saw the emergence of a new manufacturing paradigm whereby many high-tech Original Equipment Manufacturers (OEMs) have shifted their business focus from offering high value products to offering an integrated products/assets and services. High value assets (e.g. aero engines, machines, trains, wind turbines, etc.) are typically technology intensive, reliability-critical and therefore require engineering services throughout their long life cycle. This new business model enables the customers to buy the ‘capability’ of the assets (typically) through a contractual agreement whilst the ownership of the assets remains within the OEM. The responsibility of the OEM is now extended beyond manufacturing of the assets to cover maintenance and services throughout the life cycle of the assets. The OEM is obliged to guarantee that the assets are always up and running or else the penalties might be imposed by their customers. The OEM must continuously monitor the condition of the assets being contracted out and take any necessary actions before the assets break down. Through-life engineering services are hereby defined as all the services related to engineering activities to ensure the assets are ‘healthy’, available and ready to operate in order to accomplish the mission. Although the engineering services typically include maintenance, repair and overhaul, their boundary naturally extends to embrace quality inspections, spare parts inventory, information systems, resource allocation etc. High quality provision of engineering services will therefore not only depend on the design of the service operations but also on the timely services required so as to minimize the total through-life costs. This paper presents an online simulation framework that can support more effective and efficient operational decision making in the context of through-life engineering services.
