Modeling and managing engineering changes in a complex product development process

Abstract

Today's hyper-competitive worldwide market, turbulent environment, demanding customers, and diverse technological advancements force any corporations who develop new products to look into all the possible areas of improvement in the entire product lifecycle management process. One of the areas that both scholars and practitioners have overlooked in the past is Engineering Change Management (ECM). The vision behind this dissertation is to ultimately bridge this gap by identifying main characteristics of a New Product Development (NPD) process that are potentially associated with the occurrence and magnitude of iterations and Engineering Changes (ECs), developing means to quantify these characteristics as well as the interrelationships between them in a computer simulation model, testing the effects of different parameter settings and various coordination policies on project performance, and finally gaining operational insights considering all relevant EC impacts. The causes for four major ECM problems (occurrence of ECs, long EC lead time, high EC cost, and occurrence frequency of iterations and ECs), are first discussed diagrammatically and qualitatively. Factors that contribute to particular system behavior patterns and the causal links between them are identified through the exploratory construction of causal/causal-loop diagrams. To further understand the nature of NPD/ECM problems and verify the key assumptions made in the conceptual causal framework, three field survey studies were conducted in the summer of 2010 and 2011. Information and data were collected to assess the current practice in automobile and information technology industries where EC problems are commonly encountered. ased upon the intuitive understanding gained from these two preparation work, a Discrete Event Simulation (DES) model is proposed. In addition to combining essential project features, such as concurrent engineering, cross functional integration, resource constraints, etc., it is distinct from existing research by introducing the capability of differentiating and characterizing various levels of uncertainties (activity uncertainty, solution uncertainty, and environmental uncertainty) that are dynamically associated with an NPD project and consequently result in stochastic occurrence of NPD iterations and ECs of two different types (emergent ECs and initiated ECs) as the project unfolds. Moreover, "feedback-loop" relationships among model variables are included in the DES model to enable more accurate prediction of dynamic work flow. Using a numerical example, different project-related model features (e.g., learning curve effects, rework likelihood, and level of dependency of product configuration) and coordination policies (e.g., overlapping strategy, rework review strategy, IEC batching policy, and resource allocation policy) are tested and analyzed in detail concerning three major performance indicators: lead time, cost, and quality, based on which decision-making suggestions regarding EC impacts are drawn from a systems perspective. Simulation results confirm that the nonlinear dynamics of interactions between NPD and ECM plays a vital role in determining the final performance of development efforts.

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