Guiding Manufacturing Enterprises to Achieve Long-Term Business Sustainability Using the Collective System Design Approach

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Abstract

This paper addresses several issues discovered by working with different industries attempting to sustain their business enterprise and to become Lean. The three key points addressed by the paper are: 1) Designing a new system or re-designing an existing system should focus on collecting a complete set of customer needs and deriving functional requirements from those needs. 2) Illustrating the path-dependency or sequence of implementation of Physical Solutions (PSs) to achieve Functional Requirements (FRs) of partially coupled designs. 3) Lean is not what we implement as a system, rather lean is what we become as a result of meeting customer needs with the utilization of the least amount of resources possible in a sustained manner. When lean is viewed as a set of tools to implement, the people in an enterprise will face ever-increasing diffculty in long-term business sustainability. The primary problems arise early in the design/re-design phase due to the lack of a clear set of system functional requirements. Without clearly defined system FRs, driven by recognizing customer needs/concerns, an enterprise will implement point solutions in an attempt to improve part(s) of a system. The Manufacturing System Design Decomposition (MSDD), a product of Axiomatic Design (AD), illustrates the path-dependency among the solutions of the associated requirements of any manufacturing facility. The MSDD provides a system-wide view and a clear sequence for system design implementation. The Collective System Design approach is discussed to provide the steps for senior leadership to re-design an existing system or to design a new system that results in long-term sustainability and become lean.

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APA

Shah, S. A., Smith, J. J., & Cochran, D. S. (2018). Guiding Manufacturing Enterprises to Achieve Long-Term Business Sustainability Using the Collective System Design Approach. In MATEC Web of Conferences (Vol. 223). EDP Sciences. https://doi.org/10.1051/matecconf/201822301015

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