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.

This paper presents a product development process modeling and analysis technique using advanced simulation. The model computes the probability distribution of lead time in a 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. In each simulation run, the expected durations of tasks are initially sampled using the Latin Hypercube Sampling method and decrease over time as the model simulates the progress of dynamic stochastic processes. It is assumed that the rework of a task occurs for the following reasons: (1) new information is obtained from overlapped tasks after starting to work with preliminary inputs, (2) inputs change when other tasks are reworked, and (3) outputs fail to meet established criteria. The model can be used for better project planning and control by identifying leverage points for process improvements and evaluating alternative planning and execution strategies. An industrial example is used to illustrate the utility of the model.

Given the crucial role of process modeling in product development (PD) project management research and practice, and the variety of models proposed in the literature, a survey of the PD process modeling literature is timely and valuable. In this work, we focus on the activity network-based process models that support PD project management and present a comprehensive survey of the literature published in the last decade. To organize our survey, we use a framework based on the

Regular Paper This paper provides a foundation for modeling the set of activities and their relationships by which systems are engineered, or, more broadly, by which products and services are developed. It provides background, motivations, and formal definitions for process modeling in this specialized environment. We treat the process itself as a kind of system that can be engineered. However, while product systems must be created, the process systems for developing complex products must, to a greater extent, be discovered and induced. Then, they tend to be reused, either formally as standard processes, or informally by the workforce. We distinguish and clarify several important concepts in modeling processes, including: product development versus repetitive business processes, descriptive versus prescriptive processes, activities as actions versus deliverables as interactions, standard versus deployed processes, centralized versus decentralized process modeling, “as is ” versus “to be ” process modeling, and multiple phases in product development. We also present a basically simple yet highly extendable and generalized framework for modeling product development processes. The framework enables building a single model to support a variety of purposes, including project planning (scheduling, budgeting, resource loading, and risk management) and control, and it provides the scaffolding for knowledge management and organizational