Predictive Maintenance in the<scp>IoT</scp>Era

Shetty, Rashmi B.

doi:10.1002/9781119515326.ch21

Cited by 6 publications

(1 citation statement)

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“…It is through these concepts that predictive maintenance was born, with the objective of monitoring the condition of a machine and applying predictive modeling techniques to predict the probability of machine failure and give a time estimate of its likely occurrence. Predictive maintenance in the age of the Internet of Things (IoT) can be summarized as a maintenance methodology that brings together the power of machine learning and sensor data streaming to maintain machines before they fail, optimize resources, and thus reduce unplanned downtime (Shetty 2018). Industry 4.0 becomes the goal of all industries that are increasingly Proceedings of the First Australian International Conference on Industrial Engineering and Operations Management, Sydney, Australia, December 20-21, 2022 © IEOM Society International in deficit because of traditional maintenance operations that are very expensive and penalize in most cases the production process, this concerns both SMEs and large companies.…”

Section: Introductionmentioning

confidence: 99%

Decision support for SME entrepreneurs to become SME4.0

Proceedings of the International Conference on Industrial Engineering and Operations Management

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In order to remain competitive in the long term and push the efficiency of the company to its limits, entrepreneurs are increasingly open to the idea of implementing Industry 4.0 in SMEs to envision a connected SME4.0. As the biggest challenge encountered is to get started, this article aims to make it easier for SME entrepreneurs to decide on the implementation of new technologies, mentioning the latest technological trends, the advantages of being SME4.0 and specifically process 4.0, listing the last major barriers that hinder the implementation of Industry 4.0, and which mainly reside in the lack of skills of employees on new technologies and predictive maintenance, high costs of setting up new technologies and long process of return on investment.

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Section: Introductionmentioning

confidence: 99%