Life cycle simulation support for functional products

Abstract: Business to business cooperation is undergoing large changes results in new requirements on how to develop products. This will force companies to optimize their part of the product system relating to the total product system. Aerospace business agreements are being made on a life cycle basis where the actual product ownership often remains with the manufacturer. The revenue for aero engine manufacturers and their engine programs appear late in the engine life cycle, not during market introduction where large discounts are common. An engine developed for the sale of spare parts is not optimized for the owner. The key when owning and producing engines is to develop engines with minimum life cycle cost. As the development of functional (Total Care) products both includes the development of the hardware and accompanying services, people from all areas and their knowledge will be needed to take decisions. This will especially be important in the conceptual engineering design phases where knowledge of the design requirements and constraints usually is imprecise and incomplete and that there exist few support tools that can support this phase. Knowledge Enabled Engineering include Knowledge Based Engineering and other knowledge rich strategies and aim to support or perform engineering activities with the help of available techniques and methods. The purpose of Knowledge Enabled Engineering is to allow automation of engineering work. The Knowledge Enabled Engineering approach presented embeds methods used later (downstream) to simulate effects making information not readily available early on. There exist a number of decision support systems where knowledge from a few disciplines has been modelled. With a life cycle focus this is not enough. The basis needed to make early decisions needs knowledge from all phases of the products life cycle. The work presented shows how a decision support system can be used to capture and present knowledge extracted from performance, manufacturing and maintenance activities creating a better foundation for decisions regarding life cycle issues. The method described shows a way to simulate business scenarios and there product solutions based on a technical basis normally found later (downstream) in the product development process. It is shown how a decisions support system can be used to capture downstream knowledge from design, manufacturing and maintenance activities allowing life cycle effects to be simulated already in the conceptual phase. Engineers can then change the design and directly assess the life cycle cost already in the conceptual phase allowing fast iterations and thereby design the life cycle of a product based on knowledge from design, manufacturing and maintenance disciplines. Optimization in a global perspective will allow the right decision to be made in early phases with a clear understanding of how life cycle issues is affected depending on choices made.