Incorporating New Considerations for Platform Selection in Product Family Design: Connectivity and Security

Product Family Design;Platform Selection;Modularity;Security;Genetic Algorithms

Rojas Arciniegas, Alvaro J. ; Kim ; Harrison H.M.

关键词: Product Family Design;    Platform Selection;    Modularity;    Security;    Genetic Algorithms;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/18299/RojasArciniegas_Alvaro.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

The research presented in this work entails the incorporation of connectivity and security as criteria to select the platform for a family of products (components to share) while optimizing the component arrangement of the individual products. The first part introduces a framework to find the optimal set of components to share across multiple products based on the connectivity between components. Simultaneously, each product architecture is defined and optimized with the consideration that the components to share should be excluded from the modules to facilitate sharing and should cause the least impact if it needs to change. This approach was validated using an illustrative example with three digital cameras in which the similarities between the products are exploited.The second part is a logical progression from the first framework and introduces the consideration of the security of the products into the criteria to determine the components to share. In this case, the security of a product is understood as the ability to protect the sensitive information that product contains, or in other words, makes it as difficult as possible to extract the sensitive information from reverse engineering the product. This framework was applied to a set of inkjet printers and cartridges which exemplify three different architectures while providing the same basic functionality. A summary of the algorithms implemented in Matlab is presented in the appendix, providing the details of the calculation of the different metrics and the implementation of the optimization of the individual product architecture using Genetic Algorithms.