A verification and validation planning method to address change propagation effects in engineering design and manufacturing

Abstract

In-production changes must be validated prior to implementation requiring robust planning. A seven-step verification, validation, and testing method is used to identify assembly variants that should be included in testing. The method is applied to a change request causing propagation effects from variants in an automotive manufacturer. In evaluations of the method, engineers used the method successfully to identify variant propagation pathways, reducing the time and cost requirements that typically result from engineering changes. Based on the feedback from this evaluation of the verification, validation, and testing method regarding intensive laborious documentation, a semi-automated support tool is developed in Excel and presented in this research article.

Characteristics of changeable systems across value chains

“…One of the most established is the change propagation method (CPM) that identifies indirect change relationships and determines the risk for change propagation (Clarkson et al, 2004;Keller et al, 2005;Koh, 2017;Schuh et al, 2017;Masood et al, 2017a). Similarly, a variety of other algorithms exist that identify the risk of indirect change relationships (Ullah et al, 2018;Li et al, 2017;Shankar et al, 2017). Delta DSMs identify the change propagation risk by overlaying the initial dependency DSM with higher order DSMs.…”

Integrated optimization of mixed-model assembly sequence planning and line balancing using Multi-objective Discrete Particle Swarm Optimization

“…It is crucially important to set-up the assembly line for a long-term period. Any changes in the existing assembly line will incur a lot of cost to the manufacturer (Shankar et al ., 2017). Therefore, by integrating the ASP and ALB optimization for mixed-model assembly, the benefits from integrated optimization and mixed-model assembly can be obtained.…”

Testing in the incremental design and development of complex products

“…The total cost of quality can be minimised by appropriate planning of VVT activities, which potentially impacts all three components described above. The planning can be assisted by methods such as Design of Experiments for micro-level planning of individual tests (e.g., Luna et al 2013), Design Failure Modes and Effects Analysis (DFMEA) to help identify, where testing may be useful (e.g., Shankar et al 2016), and methods to optimise the overall VVT strategy (e.g., Engel and Shachar 2006;Shabi and Reich 2012). These and other methods are discussed in greater detail in forthcoming sections.…”

“…Engel and Barad (2003) also formulate VVT planning as a decision problem, placing greater emphasis on eliciting the risks that VVT is intended to avoid, and arguing that the ideal VVT strategy is strongly dependent on the project context (for example, the number of units produced). Shankar et al (2016) develop a test planning method focusing on the need to systematically generate and prioritize test activities following design change in a product that can be assembled in different configurations. The key issue is that potential failure modes differ according to the configuration at hand.…”

“…Regardless of how a change is triggered, because every part of a design is connected at least to one other part, a change in one part can propagate and require changes in others, so that the parts can continue to work together . Change propagation may need to be considered when creating or revising a testing plan, to ensure that all potentially impacted parts and interactions are appropriately tested (Shankar et al 2016). …”