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.

When a parallel computation is represented in a formalism that imposes series-parallel structure on its task graph, it becomes amenable to automated analysis and scheduling. Unfortunately, its execution time will usually also increase as precedence constraints are added to ensure series-parallel structure. Bounding the slowdown ratio would allow an informed tradeoff between the benefits of a restrictive formalism and its cost in loss of performance. This dissertation deals with series-parallelising task graphs by adding precedence constraints to a task graph, to make the resulting task graph series-parallel. The weak bounded slowdown conjecture for series-parallelising task graphs is introduced. This states that the slowdown is bounded if information about the workload can be used to guide the selection of which precedence constraints to add. A theory of best series-parallelisations is developed to investigate this conjecture. Partial evidence is presented that the weak slowdown bound is likely to be 4/3, and this bound is shown to be tight.

We study the problem of the manager of a project consisting of two sub-projects or tasks which are outsourced to different subcontractors. The project manager earns more revenue from the project if it is completed faster, but he cannot observe how hard subcontractors work, only the stochastic duration of their tasks. We derive the optimal linear incentive contracts to offer to the subcontractors when the tasks are conducted in series or in parallel. We compare them to the fixed-price contracts often encountered in practice, and discuss when incentive contracts lead to bigger performance improvement. We characterize how the incentive contracts vary with the subcontractors ’ risk aversion and cost of effort, the marginal effect of subcontractor effort, and the variability of task durations. We find that this dependence is sometimes counter-intuitive in nature. For instance, for parallel tasks, if the first agent’s task is on the critical path and his variability increases, the project manager should induce the first agent to work less hard and the second agent to work harder.

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

for all their love and sacrifice for me iii ACKNOWLEDGEMENTS This dissertation would not be possible without the immense support and encouragement from various people. First of all, I would like to thank my Ph.D. advisors Farrokh Mistree and Chris Paredis for their continuous support over the past few years. I am very fortunate to have both Farrokh and Chris as my advisors. Their different personalities and perspectives have not only provided me a broader understanding of various research topics, but also provided me reasons to think critically. It is difficult to overstate the gratitude of my mentor, Farrokh, who has been like a father for me. His enthusiasm and love for students is truly remarkable. He has a unique ability to help students realize their full potential. Farrokh has helped me by setting high goals and providing support thoughout the journey to achieve those goals. His visionary ideas and invaluable insights have always challenged me to go beyond the ‘low hanging

Using recent empirical studies, we formulate a general framework of the hierarchical control processes needed for managing a new product development (NPD) project with a high technological uncertainty, under tight time constraints. Considering the project delivery time and resources as given, the project and its control are organized to solve the uncertainty in the new product specifications through repeated internal adjustments and interactions with customers. Our framework integrates the uncertainty regarding both the market requirements and technological uncertainties. They lead to the addition/deletion of design tasks, and to a stochastic solving time of the design tasks. The paper contributes to the area of NPD work organization models, and to the development of management-related NPD project control concepts, both areas presenting research opportunities according to Brown, Eisenhardt (1995).

this paper, we discuss modelling aspects of introducing work patterns.

The work was carried out with support provided by the

An activity network (AN) is a directed acyclic graph with n nodes and A arcs. The nodes are numbered from 1 to n so that an arc always leads from a smaller numbered node to a higher numbered node. The graph has only one node with no incident arcs, which is called the starting node and numbered 1. Node n is the only node with no emanating arcs and is named the terminal node. An arc represents an activity and a node the start or the culmination of that activity. The terminal node represents the end of the project. These kinds ofgraphsarealsoreferredtoasActivity on Arc (AoA) representation of AN. In DiAN the process represented by the arcs is a diffusion process, the state of which is identified with the remaining work content (rwc). The process starts at time ‘0 ’ at rwc = 1 with a negative drift coefficient. An absorbing barrier is placed at rwc = 0 to identify with the end of the process. The completion time of an activity is thus the first passage time of such a diffusion process. The paradigm of DiAN, while offering an enhanced modeling concept, raises many questions regarding computational challenges, definition of project management metrics and applicability of such a tool in areas beyond project management. The thesis primarily focuses