| In this dissertation a framework for more effective realization of large and complex made-to-order systems is developed. This framework is coined the Hierarchical Product Platform Realization Method (HPPRM and is founded on Decision-Based Design acknowledging that humans are at the center of decision making, and an Evolutionary Approach acknowledging the importance of historicity (heredity), variation (population thinking), and probabilistic decisions (natural selection) in product development.; Framing the human decisions, the Evolutionary Approach suggests to adapt large and complex made-to-order systems by “ stabilizing the product” and “changing the product realization processes”. In response to this, we propose to “stabilize the produce” through Product Platform Design, and to “change the process” by including the effects of Organizational Learning. Based on this we organize the HPPRM in three phases. (1) In the first phase designers establish the ‘structure of the past’, i.e., acknowledging historicity, by means of Numerical Taxonomy , a stand-alone method hypothesized as a viable approach to analyze what standardization potential is present in an existing design portfolio. (2) In the second phase designers are ‘ bridging the past and the future’ by modeling the effect of standardization and technology changes, i.e., acknowledging the need for variation. The latter is done by means of Technology Diffusion to account for learning. (3) In the third phase designers decide on the ‘direction into the future’ by means of solving a compromise DSP, a multi-objective decision model, acknowledging that the model is incomplete and that the assumptions are uncertain, i.e., the probabilistic nature of the decision.; The research is anchored in problems occurring when marginal offshore oil fields are developed in traditional ways, namely, with one complete system for each field. Reuse of major system components between several fields is introduced to address this problem, and the development of the HPPRM framework is based on (1) utilizing observed similarities in the current offshore product portfolio, and (2) utilizing observed similarities between product development and biological evolution. |
