Predictive maintenance of heavy equipment in the context of Industry 4.0

点击翻译按钮获取中文摘要

Siemens Canada Limited Aero-Derivative Gas Turbines (SCLAGT) is a leading aero-derivative industrial gasturbine OEM for the Industrial Trent and the Industrial RB211 turbines, and carries out research, developmentand production at its site in Montreal, QC, Canada. Its primary objective is the advancement of gas turbinetechnology for the next generation of gas turbines. The experimental work is supported by fit for purpose testrig equipment and test bed facilities that are continuously being upgraded to the latest available technology.The proposed research project falls within the remit of the Aero-Derivative Gas Turbines Productiondepartment of continuously seeking to advance its manufacturing capabilities to maintain and increase theirposition in the turbine OEM market. Most processes at SCLAGT require heavy equipment such as liftingplatforms, cranes, balancing machines, ovens and drills.To continue their leading position in this market it is key to maintain custom delivery at high level e.g. byreducing the plant's equipment downtime. The proposed project aims to support this mission by developingadvanced Predictive Maintenance (PM) tools for their key heavy equipment. Main objective is to go towards anovel Industry 4.0 approach for PM, making use of sensors, data acquisition systems, algorithms and big data.Results of the proposed study on PM will be transferred to SCLAGT. This will help to secure the strong marketposition of this Canadian company across North America. Since SCLAGT is based in Montreal, increasingtheir plant operation efficiency will secure their jobs and market position in OEM turbine technology and couldlead to the creation of new jobs, thereby providing a benefit to Canada overall. In the long term, SCLAGT isevaluating to build a new modern factory in the Montreal area where they will incorporate the Industry 4.0principles resulting from this study right from the start.