The problem addressed in this paper is that design decisions can have a propagation effect spanning multiple life-phases influencing life-cycle metrics such as cost, time, and quality. It introduces a computational framework of a `Knowledge of life-cycle Consequences (KC) approach' aimed at allowing designers to foresee and explore effectively unintended, solution specific life-cycle consequences (LCCs) during solution synthesis. The paper presents a phenomena model describing how LCCs are generated from two fundamentally different conditions: noninteracting and interacting synthesis decision commitments. Based on this understanding, the KC approach framework has been developed and implemented as a Knowledge-Intensive CAD (KICAD) tool named FORESEE. The framework consists of three frames: an artefact life modelling frame, an operational frame, and an LCC knowledge modelling frame. This paper focuses on the knowledge modelling frame, composed basically of synthesis elements, consequence inference knowledge, and consequence action knowledge. To evaluate the influence of design decision consequences on artefact life-phases, cost, time and quality performance measures are used within the frame. Using these metrics, the life-cycle implications of a decision can be instantly updated and fully appreciated. An evaluation of the approach was carried out by applying FORESEE to thermoplastic component design. The results provide a degree of evidence that the approach integrates the activity of component design synthesis with the activity of foreseeing artefact life issues including fluctuations in life-cycle metrics. This makes the approach fundamentally different from the conventional approach in which first a candidate design solution is generated and then, at a penalty of extra time, an analysis of the solution for conflicts with artefact life issues is carried out. The framework thus provides a significant step towards the realization of a `Design Synthesis for Multi-X' approach to component design, although further work is required to exploit practically its utilization.
|Number of pages||23|
|Journal||Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM|
|Publication status||Published - 1 Apr 2000|
- life-cycle modelling
- life-cycle metrics