4.6 Article

Low-Cost Digitalization Solution through Scalable IIoT Prototypes

期刊

APPLIED SCIENCES-BASEL
卷 12, 期 17, 页码 -

出版社

MDPI
DOI: 10.3390/app12178571

关键词

industrial IoT; Industry 4; 0; prototyping; retrofitting solutions; embedded solutions; low-cost

资金

  1. EU [814225]
  2. Marie Curie Actions (MSCA) [814225] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

Industry 4.0 is a mainstream goal, but small and medium-sized enterprises face challenges in adopting new technology due to a lack of motivation among key personnel. The authors propose a rapid, low-cost solution to help manufacturing companies adopt the Industry 4.0 paradigm.
Industry 4.0 is fast becoming a mainstream goal, and many companies are lining up to join the Fourth Industrial Revolution. Small and medium-sized enterprises, especially in the manufacturing industry, are the most heavily challenged in adopting new technology. One of the reasons why these enterprises are lagging behind is the motivation of the key personnel, the decision-makers. The factories in question often do not have a pressing need for advancing to Industry 4.0 and are wary of the risk in doing so. The authors present a rapid, low-cost prototyping solution for the manufacturing companies with legacy machinery intending to adopt the Industry 4.0 paradigm with a low-risk initial step. The legacy machines are retrofitted through the Industrial Internet of Things, making these machines both connectable and capable of providing data, thus enabling process monitoring. The machine chosen as the digitization target was not connectable, and the retrofit was extensive. The choice was made to present the benefits of digitization to the stakeholders quickly and effectively. Indeed, the solution provides immediate results within manufacturing industrial settings, with the ultimate goal being the digital transformation of the entire factory. This work presents an implementation cycle for digitizing an industrial broaching machine, supported by state-of-the-art literature analysis. The methodology utilized in this work is based on the well-known DMAIC strategy customized for the specifics of this case study.

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