Abstract
A key requirement, in a distributed product development environment at General Motors, was to provide a series of quantitative and qualitative mechanisms for integrating competing information from distributed agents. Such mechanisms must also account for provisions for combining different opinions, for resolving conflicts, and for finding a feasible or optimal solution at the end. We, at Electronic Data Systems (EDS), General Motors Account, developed a Decisionβbased Integrated Product Development (DIPD) methodology to capture a systemβlevel optimization formulation as part of a product design, development and delivery (PD^3^) process. The paper describes this methodology in the context of systemβlevel optimization. DIPD employs the inputs, requirement, constraints, and output conventions to formulate the product realization problem in a distributed manner. The purpose of this DIPD methodology is to improve the performance characteristics of the product, process, and organization (PPO) relative to automobile consumer needs and expectations. DIPD builds the theory through a systematic revision and extension of the paradigms introduced earlier by optimization experts and practitioners including this author [Prasad, 1996]. The eight parts of this DIPD methodology, called building blocks, are discussed at length in this paper. The first four blocks, 1β4, provide a conceptual framework for understanding the challenges and opportunities in DIPD. The last four parts, 5β8, of this methodology provide the building blocks for an analytical and conceptual framework for decisionβmaking, PPO improvements, and a largeβscale system optimization. Β© 2002 Wiley Periodicals, Inc. Syst Eng 5: 123β144, 2002