Life cycle assessment (LCA) is a fundamental tool used in eco-design. However, it can be costly and resource intensive. We take steps toward the automation of the inventory and impact analyses stages of LCA via the proposal and development of a case-based reasoning (CBR) procedure to estimate the ecological effects of a product. The case memory in CBR, which contains representations and ecological effects of known products, is organized using an extension of the function-behavior-structure (FBS) representation for products. The extension includes ecological characteristics and values. We develop similarity metrics to measure the distance between cases in the case memory and the new product. The k-medoids algorithm is used to cluster the case memory, our metrics enable cluster retrieval and case selection, and multiple linear regression analysis is employed for adaptation. Using a database of 100 fans, we test the accuracy of the proposed approach on a cross flow fan not in the database. The method gives ecological effect estimates within 3% of the true values when there are similar fans in the retrieved cluster and about 7% when the retrieved cluster does not contain similar fans.

Supporting different stakeholder viewpoints across the product lifecycle requires semantic richness to represent product-related information and enable multiview engineering simulations. This paper proposes a multilevel product modeling framework enabling stakeholders to define product models and relate them to physical or simulated instances. The framework is defined within the Model-Driven Architecture using the multilevel (data, model, metamodel) approach. The data level represents real-world products, the model level describes models (product models) of real-world products, and the metamodel level describes models of the product models. The metamodel defined in this paper is specialized from a web ontology language enabling product designers to express the semantics of product models in an engineering-friendly way. The interactions between these three levels are described to show how each level in the framework is used in a product engineering context. A product design scenario and user interface for the product metamodel is provided for further understanding of the framework.

This paper considers a tool provisioning problem in a flexible manufacturing system (FMS) with an automatic tool transporter. The problem considered here is that of determining the number of copies of each tool type for a limited budget with the objective of minimizing makespan. This problem should be solved to decide the (additional) purchase of required tools when the FMS should be reconfigured due to change of part mix. To solve the problem, two heuristic algorithms are proposed. One is a composite search algorithm based on two greedy search methods, and the other is a search algorithm in which numbers of tool copies are determined based on tool groupings. In both algorithms, simulation results are used to find search directions. Computational experiments show that the latter search algorithm gives better results.