Estimating product lifecycle cost using a hybrid approach

Abstract

It becomes clear for manufacturing companies that product lifecycle 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 intelligent LCC estimation system that aims to overcome the drawbacks of existing systems. As a generic system, it allows users to alternatively apply the activity based costing (ABC) technique and state-of-the-art machine learning techniques to define and estimate various LCC elements depending on the information available in a product lifecycle database. Through the proposed hybrid approach, the system considers all 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.