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Smart Maintenance

Al-Shami, Mohamad
Master thesis
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no.ntnu:inspera:78072655:8508153.pdf (9.325Mb)
URI
https://hdl.handle.net/11250/2787196
Date
2021
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  • Institutt for maskinteknikk og produksjon [3194]
Abstract
 
 
The rapid growth in industry 4.0 globally made smart maintenance an exciting topic in recent years. Moreover, there is a need in the industry for a new concept for smart maintenance that leads to optimal outcomes. This paper provides a unique perspective of how the smart maintenance process may look like in the future and its implementation challenges. Moreover, it demonstrates tools, technologies, and solutions in which could be deployed currently in smart maintenance. As well, the work illustrates the role of artificial intelligence and machine learning in smart maintenance. It has been presented the critical role of augmented reality in smart maintenance. The paper aims to provide the readers with some insights about smart maintenance definitions, development, and its challenges and impacts.

It has been searched in and read previous and latest works regarding smart maintenance. Moreover, it has been developed a new smart maintenance concept. Furthermore, it has demonstrated two scenarios about how smart maintenance may be implemented on an actual physical asset.

It was found that smart maintenance is still in the development phase. And smart maintenance has many different definitions and challenges. It is found that the primary keys in smart maintenance are AR, IoT, CPS, and machine learning. The newly developed concept consists of four essential elements are smart fault detection system, smart prognostic system, smart inspection tools, and smart communication, and planning tools. This new concept may lead to promising outcomes and impacts on safety and costs.
 
Publisher
NTNU

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