Survey of life-cycle measures and metrics for concurrent product and process design

被引:9
|
作者
Prasad, B [1 ]
机构
[1] Unigraph Solut, Dept Knowledge Based Engn, Tustin, CA 92781 USA
来源
AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING | 2000年 / 14卷 / 02期
关键词
concurrent engineering; life-cycle measures and metrics; knowledge-based systems; rule-based simulation; rule-based optimization;
D O I
10.1017/S0890060400142052
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Concurrent Engineering, needs a series of measures (or measurement criteria) that are distinct to each process, and a set of metrics to check land validate) the outcome when two or more of the life-cycle processes are overlapped or required to be executed in parallel. Because product realization involves concurrent processes that occur across multiple disciplines and organizations, appropriate measures and the methods of qualifying metrics are essential. Inevitably, such concurrent processes generate design conflicts among multiple life-cycle concerns. Individual assurances of satisfying life-cycle design criterion tone at a time) do not capture the most important aspect of Concurrent Engineering-the system perspective-meaning achieving a well-balanced trade-off among the different life-cycle design measures. While satisfying life-cycle design measures in a serial manner only those, which are not in conflict, are occasionally met. The paper first describes a set of life-cycle measures and metrics and explains how those could be used for gaining operational excellence. Second, this paper provides an insight into the mechanisms (such as knowledge-based systems, rule-based simulation, and rule-based optimization) to ensure an effective trade-off across different lift-cycle measures, customer requirements, and their inclusion into a product design, development, and delivery (PD3) process.
引用
收藏
页码:163 / 176
页数:14
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