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Heavy Equipment Handling-Industrial Internet of Things Sensors, Data & Predictive Maintenance

Heavy Equipment Handling-Industrial Internet of Things Sensors, Data & Predictive Maintenance
重型设备搬运-工业物联网传感器、数据
批准号:
544864-2019
负责人:
Hassan, Esteve
金额:
$1.55万
依托单位国家:
加拿大
项目类别:
Applied Research and Development Grants - Level 1
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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英文摘要
Handling Specialty is a Grimsby and Hamilton Ontario-based manufacturer that designs, manufactures and provides support for materials handling heavy equipment, which includes lifting, tilting, rotating, and traversing equipment. Handling Specialty is successful in servicing their client industries, including advanced manufacturing, aerospace & defence, automotive, energy, entertainment, process industries, and rail/transportation since 1963. Made-to-order heavy equipment needs to have consistent reliability, and planned/minimal failure-related downtime. The equipment they manufacture for their clients has downtime (like all equipment) that results from unexpected issues causing the need for repair or unplanned maintenance. According to Accenture, predictive maintenance can save up to 12% over scheduled repairs, reducing overall maintenance costs up to 30% and eliminating breakdowns up to 70% (2014). Deloitte found that poor maintenance strategies can reduce a plant's capacity between 5-20% (2017).To reduce downtime and to strategically schedule maintenance, the project will develop Industrial Internet of Things (IIoT) sensor platforms to monitor key equipment parameters. The IIoT sensors will be connected with software to produce analytics that will notify Handling Specialty and their clients when issues are anticipated to schedule preventative maintenance. Mohawk College has the expertise to develop IIoT sensor packages, create software to use the sensor data, and to analyze the data to provide actionable information. Mohawk College's recently approved Industrial Research Chair for Colleges (IRCC), Dr. Esteve Hassan, and his IIoT expertise is a great fit to support Handling Specialty. The project will test industrial sensor packages and their optimal locations on heavy equipment; data analytics of equipment parameters to produce a baseline of operations, and develop predictive analytics. The work will customize and advance equipment analytics based on Handling Specialty's goals and their client's needs.
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