Antecedence and consequence in design rationale systems

Author:

Agouridas Vassilis,Simons Peter

Abstract

AbstractIdentification of latent or unarticulated customer and other stakeholder needs has been a significant barrier to improving the efficiency and effectiveness of the front-end phase of new product development processes. In-depth determination of stakeholder needs entails analysis of their intentions; the overall aim of the work reported in this article is to establish a framework of intentional analysis, and its associated methods and techniques for improving traceability of design practice during the early phases of the design process. The specific aim of this article is to present a conceptual framework for design rationale systems. The framework built upon the cross-fertilization of approaches and methods drawn from systems engineering and philosophy, focussing on the notions of antecedence and consequence. It was developed in the course of tackling design problems originating in industrial contexts. The methods developed were thus evaluated, updated, and refined in real applications. Two application cases are described that have been drawn from the aerospace and power sectors, respectively. The applications showed that the framework's central antecedent/consequent scheme provides a cell from which to develop either a history of actual successive changes, or a tree of alternative possible projected designs.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Bringing Stakeholders Along for the Ride: Towards Supporting Intentional Decisions in Software Evolution;Requirements Engineering: Foundation for Software Quality;2023

2. A Novel Patent Knowledge Extraction Method for Innovative Design;IEEE Access;2023

3. Design Rationale Knowledge Management: A Survey;Lecture Notes in Computer Science;2018

4. Facilitating design communication through engineering information traceability;Artificial Intelligence for Engineering Design, Analysis and Manufacturing;2013-04-18

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