Engineers and designers consider many aspects surrounding a product's life in order to meet safety, reliability, quality, manufacturing, and cost requirements. Most of the time this is done in an excellent way and the resulting products offers broad functionality with high quality and reasonable price. However serious considerations of integration of environmental requirements are often missed in the early product development. All products contribute to a range of environmental problems. These problems arise through the entire life cycle of products from the creation to the disposal of products. Design for environment (DfE) is the systematic consideration of design performance with respect to environmental, health, and safety objectives over the full product and process life-cycle. It takes place early in a product's design or upgrade phase to ensure that the environmental consequences of a product's life cycle are understood before manufacturing decisions are committed. DfE requires the coordination of several design- and data-based activities, such as environmental impact metrics, data and data management, design optimization, and others. The key issue to success is how to select the most appropriate and effective strategy for a particular product to reduce environmental impacts without disregarding the business strategies in the decision making process. Most of the DfE guidelines specify the importance of integrating business and environmental criteria into the product design stage but there are few methodologies that integrate both qualitative and quantitative aspects into multi criteria decision making process together. In this work, a new approach is proposed to integrate the life cycle assessment and decision analysis for selecting the optimized design for environment strategy by considering uncertainty issues which exist in the decision making process. The LCA model provided quantitative measurement of the environmental performance of a specific product through the entire life cycle. The result from the LCA model was utilized to select the product life cycle stage that has the highest priority to be solved for DfE practice. One of the multi criteria decision making methodologies, Analytic Hierarchy Process (AHP), was then introduced to prioritize the optimized design for environmental strategies. By using the AHP approach, the criteria for strategy selection are clearly defined and the problem is structured systematically. This enables decision-makers to examine the strengths and weaknesses of each strategy by comparing appropriate criteria. Although AHP is useful for a number of reasons, it forces decision makers to converge vague judgements into single numeric preferences in order to construct the pairwise comparisons of all pairs of objectives and decision alternatives. The resultant ranking of alternatives cannot be tested for statistical significance and variation due to several kinds of uncertainties are involved in the decision making processes. Therefore, the incorporation of uncertainty in the decision analysis is performed to test the statistical significance of the final rankings. New challenges and areas of further research will be identified, including opportunities for designing a computer based tool for practitioners.

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