An intelligent system for estimating full product Life Cycle Cost at the early design stage
by Haifeng Liu, Vivekanand Gopalkrishnan, Wee-Keong Ng, Bin Song, Xiang Li
International Journal of Product Lifecycle Management (IJPLM), Vol. 3, No. 2/3, 2008

Abstract: It becomes clear for manufacturing companies that product Life Cycle Cost (LCC) is as crucial as product quality and functionality in deciding the success of a product in the market today. While LCC estimation has been seen as an aid to design decision making, the current cost estimating techniques suffer from drawbacks of low accuracy, restriction to specific lifecycle phases, and so on. We propose to build up an efficient and an intelligent LCC estimation system that aims to overcome the drawbacks of existing systems. As a generic system, it allows the users to alternatively apply the Activity-Based Costing (ABC) technique and state-of-the-art Machine Learning (ML) techniques to define and estimate various LCC elements depending upon the information available in a Product Lifecycle Database (PLD). The system consists of five major components: PLD, LCC template manager, ABC module, ML module and synthesiser. Through the proposed hybrid approach, the system considers all the aspects of the product lifecycle, and can be used at the very early stages of design and provide information to designers in a timely manner and in a form that can be understood and used.

Online publication date: Thu, 27-Nov-2008

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