Modeling impacts of process architecture on cost and schedule risk in product development

Abstract

Abstract-To gain competitive leverage, firms that design and develop complex products seek to increase the efficiency and predictability of their development processes. Process improvement is facilitated by the development and use of models that account for and illuminate important characteristics of the process. Iteration is a fundamental but often unaddressed feature of product development (PD) processes. Its impact is mediated by the architecture of a process, i.e., its constituent activities and their interactions. This paper integrates several important characteristics of PD processes into a single model, highlighting the effects of varying process architecture. The PD process is modeled as a network of activities that exchange deliverables. Each activity has an uncertain duration and cost, an improvement curve, and risks of rework based on changes in its inputs. A work policy governs the timing of activity execution and deliverable exchange (and thus the amount of activity concurrency). The model is analyzed via simulation, which outputs sample cost and schedule outcome distributions. Varying the process architecture input varies the output distributions. Each distribution is used with a target and an impact function to determine a risk factor. Alternative process architectures are compared, revealing opportunities to trade cost and schedule risk. Example results and applications are shown for an industrial process, the preliminary design of an uninhabited combat aerial vehicle. The model yields and reinforces several managerial insights, including: how rework cascades through a PD process, trading off cost and schedule risk, interface criticality, and occasions for iterative overlapping.Index Terms-Activity network, budgeting, cycle time, design iteration, design structure matrix, engineering design management, process architecture, process modeling, process structure, product development, rework, risk management.

Process models in design and development

“…Smith and Eppinger (1997a) show how eigenstructure analysis can be used to identify the drivers of iteration within a coupled task group if the WTM assumptions hold. Assuming instead that tasks are executed in sequence, such that each task might create rework for others already completed if a dependency exists between them, Browning and Eppinger (2002) build on the earlier work of Smith and Eppinger (1997b) to develop a Monte Carlo simulation model which they use to evaluate the cost and schedule risk associated with different task sequences and thereby identify the best sequence for a given task decomposition. These two models, respectively, described as parallel and sequential rework models, have influenced many other research articles (e.g., Bhuiyan et al 2004;Cho and Eppinger 2005).…”

Implementation of complex protection against risk in machine-building enterprise`s innovations

“…In [5] the influence of creative ideas on the product of competitive advantage is investigated as a strategic in novation result. [6] is devoted to the development and use of mathematical models that facilitate the design of innovation projects. Three types of destructive innovations that can have a negative impact on existing enterprises are considered in [7].…”

Structure‐Based System Dynamics Analysis of Engineering Design Processes

“…DSMs (Design Structure Matrices) are often applied in order to capture phase dependencies (Browning & Eppinger, 2002;Browning, 1998Browning, , 2001Cho & Eppinger, 2005;Eppinger et al, 1994;Yassine et al, 2001) and thus to establish the quantification of process concurrence relationships in System Dynamics models (Ford & Sterman, 2003;Kasperek et al, 2014;Le, 2013;Lin et al, 2008;Ruutu et al, 2011). Different quantification approaches for staff allocation are explored by Black & Repenning (2001); Joglekar & Ford (2005); Kasperek, Lindinger et al (2014); Repenning (2000) and Taylor & Ford (2006) For the quantification of the influences on productivity and thus, work rates, non-System Dynamics literature may prove helpful (Brunies & Emir, 2001;Kernan et al, 1994;Kvâlseth, 1978;Maynard & Hakel, 1997;Nepal et al, 2006;Rosenbaum & Rosenbaum, 1971;Thomas & Napolitan, 1995;Thomas & Raynar, 1997).…”