3.8 Proceedings Paper

Building Blocks for Adopting Smart Manufacturing

Publisher

ELSEVIER
DOI: 10.1016/j.promfg.2019.06.098

Keywords

Smart Manufacturing; Building Blocks; Industry 4.0; Intelligent Control; Data Analytics; Additive Manufacturing; IoT

Funding

  1. J. Wayne & Kathy Richards Faculty Fellowship in Engineering at West Virginia University

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Smart Manufacturing (SM) enables companies to perform processes more effectively and efficiently, ensuring faster demand fulfillment on the one hand, and a reduction of production costs on the other hand. Thus, SM can provide a competitive edge for manufacturers that successfully adopt it. In the process of adopting SM, building blocks play a critical role and can be seen as prerequisites. Managers of manufacturing companies are interested in learning what building blocks are relevant and can help make their operations smarter and more competitive. Our paper is a first attempt to answer this question through presenting the most frequently used building blocks for SM adoption. In order to achieve this objective, we conducted a systematic mapping review to identify both building blocks as well as current methods for adopting SM. In a next step, we matched the building blocks with the adoption methods. This matching of building blocks with the adoption methods helped in determining whether a building block actually recommended in the methods for adopting SM. We found that intelligent control, data analytics, IT-based production management systems (e.g., ERP, CAx, etc.), smart products/parts/materials, interoperability, data sharing systems and standards are the most commonly used building blocks for manufacturers that are aligned towards adopting SM. As a consequence, the future manufacturing workforce needs to be prepared to understand analytics, sensors, etc. The results also showed that, although building blocks such as blockchain, robots, visual technology, and 3D printing may find their application in specific manufacturing sectors, overall, they are less commonly associated with SM adoption compared to the other building blocks. (C) 2019 The Authors. Published by Elsevier B.V.

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