Product architecture portfolio decision framework
Abstract/Contents
- Abstract
- Product design has evolved considerably over the past few decades with the ongoing maturation of a truly global economy and the associated demands of a diverse and geographically distant customer base. This has resulted in shorter product life cycles while dealing with ever more demanding customer requirements. Industry response has been to develop and adopt architecture based design to share design costs over various products, buy more engineering time for critical component design; while maintaining a large variety that the customer base expects. An architecture is defined as a set of large subsystems that come together with smaller, distinctive variant-defining options to create a set of discrete, complete, functional variants. The architecture is typically formed of the major functional subsystems of the final product that have limited influence in differentiating the final product in the consumer marketplace. As a consequence, the variant-defining options are eminently distinctive in function and/ or performance, becoming an important purchase decision factor for the customer. There is a well-established literature legacy on the benefits of architecture based product design and the characteristics of a product that suit it to such a strategy. Multiple approaches are defined to assess whether a component is suitable for architecture based design or not. By definition an architecture comprises of a portfolio of individual variants that are focused to satisfy smaller customer requirement spans within the larger parent architecture customer requirement span. The proposed framework is based on the need for a systematic way to define and evaluate a successful portfolio for a given architecture. This extends the architecture design methodology from an assessment phase into implementation phase. The framework begins by requiring the user to define a span of customer requirements an architecture is expected to cover and then define the important performance metrics for the product. The architecture and the variant-defining options are then combined to generate a matrix of all possible outcomes for the portfolio, i.e, the solution space. Engineering performance is estimated for each combination using either estimator or physics based models. This enables the use of a market outcome simulator to understand how each potential variant will perform in a defined market space. An optimization routine then picks the portfolio which maximizes the desired market outcome, such as profit, contribution margin, sales volumes. This dissertation establishes a math based approach to architecture portfolio decisions. The framework enables the complete evaluation of the product space to pick the best portfolio less susceptible to human tendencies to pick 'what has worked before' and makes the handover of architecture design decisions easier across or within organizations. The dissertation illustrates the framework through a case study of a mid-sized vehicle architecture at a large US based automotive manufacturer. In conclusion, the framework also presents future research opportunities in defining the performance metrics for each product category and in studying the effects of time of release of product variants into the market.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2011 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Manohar, Karthik |
|---|---|
| Associated with | Stanford University, Department of Mechanical Engineering |
| Primary advisor | Waldron, Kenneth J |
| Thesis advisor | Waldron, Kenneth J |
| Thesis advisor | Abell, Jeff (Jeffrey) |
| Thesis advisor | Leifer, Larry J |
| Advisor | Abell, Jeff (Jeffrey) |
| Advisor | Leifer, Larry J |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Karthik Manohar. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Karthik Manohar
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