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Publication
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Research Title |
The Predictable Maintenance 4.0 By Applying Digital Technology : A case study of Heavy Construction Machinery |
Date of Distribution |
5 July 2018 |
Conference |
Title of the Conference |
SIBR 2018 CONFERENCE ON INTERDISCIPLINARY BUSINESS & ECONOMICS RESEARCH, 5th - 6th July 2018, Osaka, Japan. |
Organiser |
Society of Interdisciplinary Business Research |
Conference Place |
Ark Hotel Shinsaibashi, Osaka, Japan |
Province/State |
โอซาก้า ประเทศญี่ปุ่น |
Conference Date |
5 July 2018 |
To |
6 July 2018 |
Proceeding Paper |
Volume |
7(2018) |
Issue |
3 |
Page |
5 |
Editors/edition/publisher |
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Abstract |
This research aimed 1) to classify the heavy machinery working process, and 2) to analyze the vibration of the heavy machinery working process (Vibration Monitoring and Analysis) in order to apply the result for planning the predictable maintenance using heavy machineries as a case study. The data were collected from grouping engines by analyzing its life expectancy, duties, importance and vibration from 14 heavy machineries. The study observed the value changes which were the cause of deterioration to synthesize the data for predicting the maintenance by applying 4.0 digital technology from the smartphone application, data on machine status is continuously acquired by sensors and shared online with smartphone application, and analyzed the forecast by finding the appropriate time to inspect the heavy machinery in the construction. The study found the heavy machineries could be categorized by their working process into three groups. After analyzing the machineries’ vibration, it also found that the frequency and the vibration were higher when the time increased. Based on the synthesis, it was discovered that every 15 days and 30 days were the appropriated time for checking the conditions. Therefore, after keeping machines in good condition as scheduled, it had a categorized by their working process different lengths of time and more accurate preventive schedule will be constructed by using data from condition based machine checking rather than average number of machine breakdowns. However, the policy was set to maintain the heavy machineries by evaluating the result of the process from Mean Time between Failure (MTBF) values together with Mean Time to Repair (MTTR) values as to reduce damage by applying 4.0 digital technology for predicting the maintenance in heavy machineries.
Keywords: The predictable maintenance applying 4.0 digital technology, Heavy Machinery, Vibration Monitoring and Analysis
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Author |
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Peer Review Status |
มีผู้ประเมินอิสระ |
Level of Conference |
นานาชาติ |
Type of Proceeding |
Full paper |
Type of Presentation |
Oral |
Part of thesis |
true |
ใช้สำหรับสำเร็จการศึกษา |
ไม่เป็น |
Presentation awarding |
false |
Attach file |
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Citation |
0
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