Prognosis of Behaviour of Machine Tool Spindles, Their Diagnostics and Maintenance

Training and Practice to Ensure Implementation of the TPM System

“…A substantial number of employees are not familiar with the principles and functioning of the TPM system, and therefore any implementation and subsequent functioning of TPM will require the introduction of an education process. [Mosyurchak 2017] When doing so, it should be recognised that it is not only maintenance workers who need to have knowledge of how the principles TPM operate -all positions involved in TPM teams must be included in the education process -see figure 3.…”

Improving predictive maintenance benefits from online monitoring of spindles: case study in woodworking machine tool

“…All are moving in the same direction of using network data to understand the behavior of machines, making it possible to make decisions quickly or even to make predictions based on online data. Mosyurchak, Veselkov, Turygin and Hammer (2017) understand this fact as digitalization, in which we will have several machines connected in a cyber-physical system generating data that will be shared in a network environment at all levels. Nagy, Olah, Erdei, Mate and Popp (2018) consider that for a factory to be totally intelligent, it is necessary that the entire plant, not just a product line, remains digitally connected.…”

“…To Sadasivam, Archenti and Sandberget (2018), the spindle is a highly precise system composed of several components that perform their functions within the pre-established limits for their work capacity. Mosyurchak, Veselkov, Turygin and Hammer (2017) mention that the spindle is one of the critical items of any machine tool, and the costs involved in its maintenance cannot be neglected. Ziada, Yang and DeGroat-Ives (2017) explain that obtaining data from the inside of a spindle is extremely complex and occurs only with its disassembly of the set or with the support of manufacturers.…”

“…Other similar concepts are PHM (Prognostic and Health Management) found in Liu and Xu (2017), Machine Healthy Management discussed by Lee, Kim, Quan, Kim, Kim, Yooh et al (2018), Machine Healthy presented by Lee, Kao and Yang (2014) and SMTS (Smart Machine Tool Systems) discussed by Jeon, Yoon, Um and Suh (2020) which presented an architecture seeking to avoid machine failure and zero defect. Thyago Bachim, Mauro Luiz Martens, Salvatore Digiesi, Douglas Favero Trindade, Bruno Ricci Considering that companies in this sector of woodworking machine tools use few predictive maintenance systems, the use of prognostic maintenance or condition-based maintenance is currently a challenge because if the normal condition of the spindle during an empty test for offline vibration data collection is not known, then its operation with online monitoring as referenced by Mosyurchak, Veselkov, Turygin and Hammer (2017) is also unknown. These authors believe that it is important to differentiate between the types of collections performed for later determination of failures.…”

“…On the other hand, new technologies do tend to solve difficulties faced by maintenance teams by building a history of failure analysis that, in the long or medium term, presents a positive result. This becomes more complicated with Improving predictive maintenance benefits from online monitoring of spindles: case study in woodworking machine tool complex equipment, such as the spindle, a component of a machine tool, whose complexity is detailed in the studies of Sadasivam, Archenti and Sandberget (2018), Abele, Altintas and Brecher (2010) and Mosyurchak, Veselkov, Turygin and Hammer (2017). According to these authors, it is necessary to develop methodologies for identifying flaws and coherent action plans so that the maximum life of the equipment is reached to ensure smooth progress from production to delivery to the final customers.…”