A dynamic model for engineering change propagations in multiple product development stages

Abstract

To accurately predict propagation dynamics for single or multiple change propagations across different product development stages in a sequential or concurrent way is critical for decision-making of implementing change requests. In this paper, a change propagation dynamic model is built based on the compartmentalization of engineering entities into susceptible engineering entities and affected engineering entities (SA), the ordinary differential equations for describing the rate of affected entities with respect to the total ones and the duration for resolving all the changes for every moment are presented by combining the calculations of change impacts with different split and joint junctions. Considering the difficulty of finding analytical solutions to the differential equations, algorithms for sequential and concurrent simulations of change propagations across different development stages, and random and GA (Genetic Algorithm)-based optimal selections of feasible propagation paths are developed to obtain numerical solutions for single and multiple change requests. Simulation results show that change ripples and blossoms can be observed in both sequential and concurrent change propagations, and these propagation patterns are not sensitive to the initial change effect and the threshold value for propagations, while critical change propagation paths and the number of initiated changes have important effects on both concurrent and sequential change propagation process. It is also demonstrated that concurrent propagation strategy is advantageous for processing single or few of initiated changes since it can shorten product redevelopment time, sequential propagation strategy has an advantage of robustness for handling multiple initiated change requests.

Research and Application of the Simulation Method for Product Development Process Based on System Dynamics

“…This method is not suitable for processes involving multiple activities. Li et al (2022) established a dynamic model based on ordinary differential equations to address the issue of engineering change propagation across multiple product development stages [16]. Mallek-Daclin et al (2023) proposed the application of digital twin technology to real-time check the deviation between product development models and reality, in order to quickly predict otherwise unforeseeable events [40].…”

“…Various scholars have conducted research on the dynamic nature of the development process from perspectives such as resource allocation [15], engineering change propagation [16], and workforce management [17]. Dynamic complexity refers to the evolution of the product design process over time.…”

Combining System Models and CAD for Change Scenario Management

“…Engineering changes are common throughout different stages of a product´s development (Li et al, 2022b). The nature of the changes is manifold as a change request can have different origins e.g., customer or production, with different implications and priorities (Li et al, 2022a).…”

“…The analysis and propagation of change impacts in different areas of development require a thorough assessment (Eltaief et al, 2022;Jarratt et al, 2011). Several approaches exist to cope with those engineering changes at different stages of the system development process, such as Li et al (2022b), Tang et al (2008) or Germani et al (2007). For complex systems, those change impacts and propagations are not limited to an individual model, such as a single CAD component model.…”