A method is introduced to incorporate sustainability considerations in the early design stages, while simultaneously accounting for supply chain factors, such as cost and lead time. Overall, this work is our first step in understanding the trade-offs between sustainability metrics and more traditional supply chain performance metrics (i.e., cost and lead time). Based on our understanding of these trade-offs, we intend to help build computational artificial intelligence tools that can exploit these trade-offs for improved customization in produc
Product environmental impact reduction efforts largely focus on incremental changes during detailed design. Application of automated concept generation using a design repository and integral life cycle assessment approach is explored to evaluate and reduce environmental impacts in the conceptual phase of product design.
In recent years, numerous methods to aid designers in conceptualizing new products have been developed. These methods intend to give structure to a process that was, at one time, considered to be a purely creative exercise. Resulting from the study, implementation, and refinement of design methodologies is the notion that both the structure of the development process and the structure of the developed product are key factors in creating value in a firm’s product line. With respect to the latter key factor, product architecture, but more specifically, modular product architecture has been the subject of much study. This research is focused on two tasks: advancing the notion of a modular product architecture in which modules can be incorporated into a product ‘post-market,’ and creating a method that aids designers leverage knowledge of natural symbiotic relationships to synthesize these post-market modules. It adds to prior work by first, defining the terms ‘derivative product’ and ‘host product’ to describe the post-market module and the product that the module augments, respectively. Second, by establishing three guidelines that are used to assess the validity of potential derivative products, giving the newly termed host and derivative product space defined boundaries. And lastly, by developing a 7-step, biomimetic-based methodology that can be used to create derivative product concepts (post-market modules). By using this methodology, the engineered products are designed on symbiotic principles found in nature.
Developing new approaches to aiding computational synthesis of modern electromechanical systems is a major need. Current techniques use product representations that reason with single abstractions such as either geometry or physical dynamics. Further, these techniques are utilized in the context of static design processes. This article proposes the development of computational frameworks wherein both the process of design along with the product being designed are reasoned with in an integrated manner. Developing such a framework would require advances in product models that integrate geometric and behavioral abstractions. Further, development of new process models would require integration of planning and machine learning techniques that reason with these new product representations. An integrated framework would aid in the development of better cost-effective synthesis tools and allow for assimilating and reusing many kinds of design knowledge. Potential approaches towards developing such a synthetic framework are outlined.
This article introduces the challenge of digital preservation in the area of engineering design and manufacturing and presents a methodology to apply knowledge representation and semantic techniques to develop digital engineering archives. This work is part of an ongoing, multiuniversity effort to create cyber infrastructure-based engineering repositories for undergraduates (CIBER-U) to support engineering design education. The technical approach is to use knowledge representation techniques to create formal models of engineering data elements, work flows, and processes. With these techniques formal engineering knowledge and processes can be captured and preserved with some guarantee of long-term interpretability. The article presents examples of how the techniques can be used to encode specific engineering information packages and work flows.