Abstract
In modern manufacturing, the product architecture design options are usually restricted to those that can be produced with 100% confidence using those proven technologies to satisfy the existing customer requirement. As a result, the inefficiencies of architecture design are considerable due to such limitations. This issue is of particular interests in cyber manufacturing when exploring the tradeoff between generality and feasibility in product design and manufacturing. It can be expected that the improvement and extension of the existing product architecture may be required to meet new customer requirement when new technologies become available. An effective system performance assessment algorithm is necessary to facilitate the extension of existing product architecture. Though there has been a lot of research on architecture assessment, there is no well-defined model for level by level architecture assessment considering architecture extension. In this paper, we propose a general architecture assessment model considering the integration of additional functionality requirements and performance metrics to evaluate the architecture performance along its value pathway to meet stakeholder's requirements. A numerical case study focusing on a hypothetical auto cooling system is used to validate the effectiveness of the proposed model.
Recommended Citation
M. M. Islam et al., "A General Algorithm for Assessing Product Architecture Performance Considering Architecture Extension in Cyber Manufacturing," Procedia Computer Science, vol. 114, pp. 384 - 391, Elsevier B.V., Nov 2017.
The definitive version is available at https://doi.org/10.1016/j.procs.2017.09.052
Meeting Name
Complex Adaptive Systems Conference with Theme: Engineering Cyber Physical Systems, CAS 2017 (2017: Oct. 30-Nov. 6, Chicago, IL)
Department(s)
Engineering Management and Systems Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Architecture Assessment; Automobile Cooling System; Extended Architecture; Multiple Fuzzy Model; Renewable Sources
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2017 The Authors, All rights reserved.
Publication Date
01 Nov 2017
