Modelling of Asset Health and Risk Matrix for Rotating Assets in Sawmill

Weyerhaeuser Drayton Valley Lumber Mill has employed continuous monitoring of vibration for all the critical rotating assets in the mill to detect failures in early stage and prevent failures. Continuous monitoring is achieved through sensors mounted on the equipment and each sensor collects real-time vibration data of the equipment. Real-time vibration data give an understanding of the condition/health of the rotating asset. If the asset’s vibration goes above a certain limit (typically the limits are called as “warning” or “alarm”), then maintenance actions are initiated to prevent the failure. To reduce the overall vibration and prevent failures, Weyerhaeuser wants to better use the asset’s vibration information to represent asset health as very healthy, healthy, approaching warning, warning, and alarm. In this project, interns will work on developing an Asset Health Model to classify the asset condition/health using vibration information and build a risk matrix to prioritize maintenance activities. This will help maintenance team at Weyerhaeuser to take the appropriate actions to prevent failures, run the mill reliably, and achieve planned production.

Faculty Supervisor:

Zhigang (Will) Tian

Student:

Partner:

Weyerhaeuser

Discipline:

Engineering

Sector:

Agriculture; Manufacturing

University:

University of Alberta

Program: