Complexity drivers in engineering design: Toward a decision support system based on an organizational perspective

Abstract

Purpose

In the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS) perspective. Therefore, this paper aims to explore how we may deepen our understanding of the design process as a CAS. In this respect, the key complexity drivers of the design process are discussed and an organizational decomposition for the simulation of the design process as CAS is conducted.

Design/methodology/approach

The proposed methodology comprises three steps. First, the complexity drivers of the design process are presented and are matched with those of CAS. Second, an analysis of over 111 selected papers is presented to choose the appropriate model for the design process from the CAS theory. Third, the paper provides methodological guidelines to develop an organizational decision support system that supports the complexity of the design process.

Findings

An analysis of the key drivers of design process complexity shows the need to adopt the CAS theory. In addition to that, a comparative analysis between all the organizational methodologies developed in the literature leads the authors to conclude that agent-oriented Software Process for engineering complex System is the appropriate methodology for simulating the design process. In this respect, a system requirements phase of the decision support system is conducted.

Originality/value

The originality of this paper lies in the fact of analysing the complexity of the design process as a CAS. In doing so, all the richness of the CAS theory can be used to meet the challenges of those already existing in the theory of the design.

Citation

Benabdellah, A.C., Benghabrit, A. and Bouhaddou, I. (2020), "Complexity drivers in engineering design: Toward a decision support system based on an organizational perspective", Journal of Engineering, Design and Technology, Vol. 18 No. 6, pp. 1663-1690. https://doi.org/10.1108/JEDT-11-2019-0299