A Simulation-Based Process Model for Managing Complex Design Projects

Abstract

Abstract-This paper presents a process modeling and analysis technique for managing complex design projects using advanced simulation. The model computes the probability distribution of lead time in a stochastic, resource-constrained project network where iterations take place among sequential, parallel, and overlapped tasks. The model uses the design structure matrix representation to capture the information flows between tasks. We use a simulation-based analysis to account for many realistic aspects of design process behavior which were not possible in previous analytical models. We propose a heuristic for the stochastic, resource-constrained project scheduling problem in an iterative project network. The model can be used for better project planning and control by identifying leverage points for process improvements, and for evaluating alternative planning and execution strategies. An industrial example is provided to illustrate the utility of the model. Index Terms-Design iteration, design structure matrix, process modeling, project management, project simulation.

Design Structure Matrix and Project Management: bibliometric analysis

“…Chen, Ling and Chen (2003) present a scheduling and rescheduling framework based on Design structure Matrix to deal with the difficult to scheduling and managing the global collaborated new product development process for large projects, especially in sequencing, monitoring and controlling de NPD process. Cho and Eppinger (2005) present a process modeling and analysis technique for managing complex design projects using advanced simulations computing. It computes the probability distribution of lead time in a stochastic, resource-constrained project network where iterations take place among sequential, parallel and overlapped tasks.…”

Process models in design and development

“…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).…”

Structure-based System Dynamics analysis of engineering design processes

“…Additionally, uncertainties associated with events can be modeled explicitly and their collective consequences in the system are analyzed statistically. (Moon, 2015) Cho & Eppinger (2005) expand DSMs by Discrete-event approaches for the field of complex engineering design processes. However, their approach cannot simulate influences of uncertainty on the process duration.…”

“…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).…”