Abstract
Predictive maintenance techniques can determine the conditions of equipment in order to evaluate when maintenance should be performed. Thus, it minimizes the unexpected device downtime, lowers the maintenance costs, extends equipment lifecycle, etc. Therefore, this article developed a predictive maintenance mechanism with the construction of a test platform and data analysis along with machine learning. The information transmission of sensors was based on Raspberry Pi via the TCP/IP (Transmission Control Protocol/Internet Protocol) communication protocol. The sensors used for environmental sensing were implemented on the programmable interface controller and the data were stored in time sequence. A statistical analysis software platform was adopted for data preprocessing, modelling, and prediction to provide necessary maintenance decision. Using multivariate analysis users can obtain more information about the equipment’s status, and the administrator can also determine the operational situation before unexpected device anomalies. The developed modules are decisively helpful in preventing unpredictable losses, thus improving the quality of services.
Highlights
Interest in innovative processes such as predictive maintenance is growing rapidly
Experimental platform is imported into the model, the load estimation can be performed in real we experimented by providing a new set of data as input to verify the model containing different sets time
Technology continues to change at the end-to-end of the business, optimizing its operations and considering preventive maintenance and considering advantage of predictive maintenance tools to reduce down time, improve safety, and increase profits
Summary
Due to the fierce competition among manufacturing industries, an increasing number of manufacturing companies are gradually expanding their business by selling products and providing good service to maintain a leading position. Maintaining the scheduling of service resources is a key step in the provision of product services. Reducing maintenance costs and improving service quality has become an important problem for industries. If the failure of the machine can be predicted in time, as per the failure prediction information, the company can provide requisite service to solve the problem reasonably, the possibility of failure can be eliminated which ensures the guarantee of a working machine. Predictive maintenance is considered an appropriate approach to ensure the healthy functioning of a device as it allows preventative detection of failure and avoidance of the breakdown of a device
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
