Detecting emergence in engineered systems: A literature review and synthesis approach

IF 1.6 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL Systems Engineering Pub Date : 2023-02-07 DOI:10.1002/sys.21660
Rune Andre Haugen, Nils-Olav Skeie, G. Muller, Elisabet Syverud
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引用次数: 0

Abstract

Modern product development often generates systems of high complexity that are prone to emergent behavior. The industry has a need to establish better practices to detect inherent emergent behavior when engineering such systems. Philosophers and researchers have debated emergence throughout history, tracing to the time of the Greek philosopher Aristotle (384–322 B.C.) and current literature has both philosophical and practical examples of emergence in modern systems. In this review paper, we investigate the phenomenon of emergent behavior in engineered systems. Our aim is to describe emergence in engineered systems and propose methods to detect it, based on literature. Emergence is in general explained as dynamic behavior seen at macro level that cannot be traced back to the micro level. Emergence can be known or unknown in combination with positive or negative. We find that best practices to engineer complicated systems should contain a sensible suite of traditional approaches and methods, while best practices to engineer complex systems need extensions to this considering a new paradigm using incentives to guide system behavior rather than testing it up‐front.
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在工程系统中检测突现:文献综述和综合方法
现代产品开发通常会产生高度复杂的系统,这些系统容易出现紧急行为。该行业需要建立更好的实践,以在设计此类系统时检测固有的紧急行为。哲学家和研究人员在整个历史上一直在争论出现,可以追溯到希腊哲学家亚里士多德(公元前384年至公元前322年)的时代,当前的文学既有现代系统出现的哲学例子,也有实践例子。在这篇综述文章中,我们研究了工程系统中的紧急行为现象。我们的目的是描述工程系统中的出现,并根据文献提出检测方法。紧急情况通常被解释为宏观层面的动态行为,无法追溯到微观层面。紧急情况可以是已知的或未知的,也可以是阳性或阴性。我们发现,设计复杂系统的最佳实践应该包含一套合理的传统方法和方法,而设计复杂系统最佳实践需要扩展到这一点,考虑到一种新的范式,使用激励来指导系统行为,而不是预先测试。
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
Systems Engineering
Systems Engineering 工程技术-工程:工业
CiteScore
5.10
自引率
20.00%
发文量
0
审稿时长
6 months
期刊介绍: Systems Engineering is a discipline whose responsibility it is to create and operate technologically enabled systems that satisfy stakeholder needs throughout their life cycle. Systems engineers reduce ambiguity by clearly defining stakeholder needs and customer requirements, they focus creativity by developing a system’s architecture and design and they manage the system’s complexity over time. Considerations taken into account by systems engineers include, among others, quality, cost and schedule, risk and opportunity under uncertainty, manufacturing and realization, performance and safety during operations, training and support, as well as disposal and recycling at the end of life. The journal welcomes original submissions in the field of Systems Engineering as defined above, but also encourages contributions that take an even broader perspective including the design and operation of systems-of-systems, the application of Systems Engineering to enterprises and complex socio-technical systems, the identification, selection and development of systems engineers as well as the evolution of systems and systems-of-systems over their entire lifecycle. Systems Engineering integrates all the disciplines and specialty groups into a coordinated team effort forming a structured development process that proceeds from concept to realization to operation. Increasingly important topics in Systems Engineering include the role of executable languages and models of systems, the concurrent use of physical and virtual prototyping, as well as the deployment of agile processes. Systems Engineering considers both the business and the technical needs of all stakeholders with the goal of providing a quality product that meets the user needs. Systems Engineering may be applied not only to products and services in the private sector but also to public infrastructures and socio-technical systems whose precise boundaries are often challenging to define.
期刊最新文献
Systematic approach to a government‐led technology roadmap for future‐ready adaptive traffic signal control systems Emergent knowledge patterns in verification artifacts On reference architectures Requirements engineering in industry 4.0: State of the art and directions to continuous requirements engineering Enhancing conceptual models with computational capabilities: A methodical approach to executable integrative modeling
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