Feasibility Study for an Automated Engineering Change Process

Area of Science:

• Engineering Management
• Computational Engineering
• Product Lifecycle Management

Background:

• Engineering changes represent a substantial cost in project management.
• While change mitigation is ideal, design decisions evolve, necessitating change management.
• Current processes for engineering change requests can be inefficient and resource-intensive.

Purpose of the Study:

• To analyze the feasibility and performance of automating engineering change requests.
• To demonstrate the potential for increased speed, efficiency, and effectiveness in product-lifecycle-wide change processes.
• To highlight the need for advanced search algorithms over brute-force methods for change request management.

Main Methods:

• A case study was used to mimic a typical change request scenario.
• Genetic algorithms were selected to demonstrate the feasibility of automation.
• The performance of the genetic algorithm was analyzed for efficiency and effectiveness.

Main Results:

• The study confirmed the feasibility of using genetic algorithms for automating engineering change requests.
• Analysis indicated that automation can significantly reduce the human effort required for low-level changes.
• The genetic algorithm approach proved more efficient than brute-force methods for the examined case.

Conclusions:

• Automating engineering change requests shows promise for substantial industry gains in time and cost.
• Genetic algorithms offer a viable and deployable solution for enhancing change request processes.
• Further development of sophisticated algorithms could greatly improve process efficiency and industry competitiveness.