Goal modelling in aeronautics: Practical applications for aircraft and manufacturing designs

IF 2.7 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Data & Knowledge Engineering Pub Date : 2024-11-05 DOI:10.1016/j.datak.2024.102375
Anouck Chan , Anthony Fernandes Pires , Thomas Polacsek , Stéphanie Roussel , François Bouissière , Claude Cuiller , Pierre-Eric Dereux
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Abstract

Traditional aircraft development follows a sequential approach: the aircraft is designed first, followed by the industrial system. This approach limits the industrial system’s performance due to constraints imposed by the pre-defined aircraft design. Collaborative approaches, however, advocate for simultaneous design of different products to create new opportunities. Within a project focused on co-designing aircraft and their industrial systems, we put goal modelling into practice to gain a comprehensive understanding of the objectives driving each system’s design and their interdependencies. The intention was to develop an approach for actively involving domain experts, even those lacking prior knowledge of Goal-Oriented Requirements Engineering (GORE).
This paper provides a detailed account of the iterative process employed to develop and refine our approach. For each iteration, we describe the organisation of modelling sessions with experts, the resulting models, and the collected feedback. We also report on the overall approach’s reception from both industry experts and academic participants. Furthermore, we highlight recommendations and research challenges that emerged from the encountered difficulties during the iterative process, suggesting avenues for further investigation and improvement.
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航空目标建模:飞机和制造设计的实际应用
传统的飞机研发采用顺序式方法:首先设计飞机,然后设计工业系统。由于预先确定的飞机设计所带来的限制,这种方法限制了工业系统的性能。而协作式方法则主张同时设计不同的产品,以创造新的机遇。在一个专注于飞机及其工业系统协同设计的项目中,我们将目标建模付诸实践,以全面了解驱动每个系统设计的目标及其相互依存关系。本文详细介绍了开发和完善我们的方法所采用的迭代过程。对于每一次迭代,我们都描述了与专家一起组织建模会议的情况、所产生的模型以及收集到的反馈。我们还报告了行业专家和学术参与者对整个方法的接受程度。此外,我们还强调了在迭代过程中遇到的困难所带来的建议和研究挑战,提出了进一步调查和改进的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data & Knowledge Engineering
Data & Knowledge Engineering 工程技术-计算机:人工智能
CiteScore
5.00
自引率
0.00%
发文量
66
审稿时长
6 months
期刊介绍: Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.
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