Predictive Maintenance and part quality control from joint product-process-machine requirements: application to a machine tool

Manufacturing companies faces today production quality issues widely tackled with Statistics Process Control (SPC) but presenting some limits since it is performed a posteriori. One interesting way is to anticipate deviation of part quality rather than to suffer it. These deviations result from machine performance, process parameters and part material. The two last items are well mastered, and only the machine performance is not completely under control due to the degradation of its components and their evolution. A challenge is to follow machine degradation in order to anticipate product quality deviations. This originality is integrated in the scope of predictive maintenance. However, the relationship between machine monitoring and product requirements is not yet well founded within this strategy. To face this challenge, the paper proposes an innovative approach based on machine degradation monitoring to anticipate part quality deviation from the consideration of joint product-process-machine requirements. The feasibility and interest of the approach are shown on the case of machining tool GROB BZ560 located in RENAULT Cleon Factory. (C) 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licencses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the 7th International Conference on Through-life Engineering Services.