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2022 | OriginalPaper | Chapter

Predicting Remaining Useful Life of Capping and Filling Machine Using Exponential Degradation Model with Web Server Deployment

Authors: Devang J. Gajjar, Shrey A. Shah, Sneh Soni

Published in: Recent Advances in Manufacturing Modelling and Optimization

Publisher: Springer Nature Singapore

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Abstract

This paper demonstrates the deployment of predictive maintenance algorithm for capping and filling machine. The proposed work covers the predictive maintenance algorithm, machine operations, data analytics, user interface, and its implementation on the capping and filling machine. The explanation begins from fetching the sensor data stored in PLC, saving it to a SQL database via OPC server, and performing prognostics analysis on this data by extracting features, ranking those features, performing principal component analysis, and feeding obtained health indicator matrix to the exponential degradation model. As a result, the remaining useful life of the system is derived and plotted in the form of a probability distribution function along with the model itself. Real-time machine parameters along with plots are presented to the user in the form of a graphical user interface built as a MATLAB application, which is further deployed on a Web app server demonstrating the ease of local user accessibility in the form of a Web site.
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Metadata
Title
Predicting Remaining Useful Life of Capping and Filling Machine Using Exponential Degradation Model with Web Server Deployment
Authors
Devang J. Gajjar
Shrey A. Shah
Sneh Soni
Copyright Year
2022
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-16-9952-8_65

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