Condition based predictive maintenance of worm gearbox using DR ferrography. (2022)

• Record Type: Journal Article
• Authors: Bhat, Jitendra; Bhapkar, Udaysinh; Desai, Milind
• Is Part Of: Materials today. Volume 52:Part 4(2022)
• Page Start: 2210
• Page End: 2212
• Publication Date: 2022
• Subjects: Worm gearbox -- Oil analysis -- Condition monitoring -- Direct reading ferrography -- Predictive maintenance; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2021.07.353
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Due to inadequate and incorrect information about the state of the equipment, the maintenance person may be unable to make maintenance decisions. Modern maintenance ideas are focused on the implementation of equipment predictive maintenance to address this problem. DR Ferrography is a predictive maintenance technique which provides the data of condition of the lubricants and also the condition of the equipment elements that interacted with oil during normal operation. A case study of a worm gearbox is discussed to demonstrate the usefulness of a DR Ferrography technique. An experimental test rig is used to model the worm gearbox. The worm gearbox operates under normal operating conditions as per industrial practice. DR Ferrography is a useful method for detecting wear particles in lubricating oil. According to the findings, wear debris indicates device performance based on wear debris concentration and wear severity index, leading to early component breakdown detection and prediction.