Abstract
Engineering change is a significant cost sink in many projects. While avoiding and mitigating the risk of change is the ideal approach, mistakes and improvements are recognized inevitably as more is learned over time about the quality of the decisions made in a product's design. This paper presents a feasibility and performance analysis of automating engineering change requests to demonstrate the promise for increasing speed, efficiency, and effectiveness of product-lifecycle-wide engineering-change-request processes. To explore this idea, a comparatively simple case study is examined both to mimic the reduced set of alterable aspects of a typical change request and to highlight the need of appropriate search algorithms as brute force methods quickly prohibitively resource intensive. Although such cases may seem trivial for human agents, with the volume of expected change requests in a typical facility, the potential opportunity gain by eliminating or reducing the amount of human effort in low level change requests accumulate into significant returns for industry on time and money. Within this work, the genetic algorithm is selected to demonstrate feasibility due to its broad scope of applicability and low barriers to deployment. Future refinement of this or other sophisticated algorithms leveraging the nature of the standard representations and qualities of alterable design features could produce tools with strong implications for process efficiency and industry competitiveness in the execution of its projects.