ORIGINAL PAPER Peder Fitch Æ Joyce Smith Cooper Life-cycle modeling for adaptive and variant design. Part 1: Methodology Received: 9 October 2003 / Revised: 3 September 2004 / Accepted: 3 September 2004 / Published online: 28 January 2005 Ó Springer-Verlag London Limited 2005 Abstract Life-cycle modeling for design (LCMD) is a methodology for assessing the life-cycle impacts for a complex product with many individual components starting from initial design phases when few design specifications have been made. The methodology com- bines life-cycle assessment (LCA) with probabilistic design methods in a way that forecasts attributes of possible final designs yet reduces information needs. Specifically, LCMD is a methodology for generating arrays of design scenarios that communicate the range of designs being considered by a design team, and esti- mating missing data for those design scenarios. The main contribution to enhancing standard LCA is the incorporation of methods to estimate physical attributes of individual components for various design options and in four analyses for evaluating the arrays of design sce- narios. An automotive case study presented in part 2 of this work demonstrates one application of LCMD. Keywords Life-cycle assessment Æ Adaptive design Æ Variant design Æ Probabilistic design 1 Introduction Life-cycle modeling is the use of quantitative or quali- tative models to evaluate the performance of a product from materials extraction through product manufac- turing, use, recycling, and disposal. Performance can be measured by cost, manufacturing impact, or other con- sequences. In life-cycle assessment (LCA) (SETAC 1991; ISO 19971), life-cycle models are used to quantify materials and energy use and waste and ultimately environmental impact. In life-cycle costing, life-cycle modeling includes the use of production and service models (Brown and Yanuck 1985; Fabrycky and Blan- chard 1991). When the scope of a life-cycle model is broad (i.e., when processes from materials extraction through product retirement are considered), life cycle modeling finds limited use in the design of complex products with large numbers of subsystems and components (e.g., automobiles and airplanes). Data collection and mod- eling complexity are primary reasons for this lack of use in all different types of design: variant design, adaptive design, and original design (Pahl and Beitz 2001; as defined by Otto and Wood 2001). One specific reason related to data collection stems from the existence of design uncertainty—uncertainty related to knowledge of a product design’s final attributes (e.g., materials, geometries, manufacturing processes). As shown in Fig. 1, design uncertainty is largest for entirely original designs and decreases during product design. As a starting point, this research investigates the use of life- cycle modeling in adaptive and variant design, as fol- lows. 1.1 Existing life-cycle modeling methods Numerous authors have proposed methodologies for incorporating life cycle modeling into product design. Table 1 compares 11 existing methods identified in engineering and scientific literature. The methods differ in the motivation for modeling, the scope of the life cycle analyzed, the type of models used, the phase(s) of design they support, and the treatment of uncertainty. Specifi- cally, environmental assessment is the primary impetus for many of the design methodologies in Table 1, while analysis of production efficiency and cost, and concur- rent design motivate others. When environmental assessment is the motivation for modeling, one or more of five levels of appraisal that coincide with published LCA methodologies are included: P. Fitch Æ J. S. Cooper (&) Department of Mechanical Engineering, University of Washington, Box 352600, Seattle, WA 98195, USA E-mail: cooperjs@u.washington.edu Tel.: +1-206-5435040 Fax: +1-206-6858047 Research in Engineering Design (2005) 15: 216–228 DOI 10.1007/s00163-004-0055-7