TY - JOUR

T1 - Failure sensitivity and similarity of process signals among multiple machine tools

AU - Denkena, Berend

AU - Klemme, Heinrich

AU - Stiehl, Tobias H.

N1 - Funding Information: The authors acknowledge the financial support from the Federal Ministry for Economic Affairs and Climate Action of Germany (BMWK) in the project IIP-Ecosphere (project number 01MK20006A). Also, the authors are grateful for the support of the “Sieglinde Vollmer Stiftung”.

PY - 2023

Y1 - 2023

N2 - For a monitoring system to provide considerable performance, it usually requires machine- and process-specific information. This includes information about which process signals are sensitive to failures and which signal behavior indicates these failures. However, this information is mostly unavailable when monitoring the manufacturing of individual parts or small series. The transfer of process-specific information among similar machine tools can provide the required information, thereby improving monitoring performance. Nevertheless, no systematic research exists on what process signals are best suited for such an information transfer. This paper investigates a) whether information about the sensitivity of a signal to failures is transferrable among multiple machine tools and b) whether the behavior of these signals, modelled as probability distributions, is similar among multiple machine tools. Initially, a measure is introduced that quantifies the capability of a signal to separate two process conditions, the signal overlap factor SOF. It is then demonstrated how the SOF can be calculated for transient process conditions. The SOF is then empirically determined for a set of process signals for three different machine tools, individually, to assess failure-sensitivity of the signals for slot milling in steel. Additionally, the SOF is calculated for the union of the data of the machine tools to assess the similarity of signals among machine tools. The set of evaluated process signals includes process forces, the torque of the main spindle, and the torque and position control deviation of the feed axes. All machine tools were operated with identical instructions, tools, and materials. Bores were machined in workpieces to simulate material anomalies. Results suggest that low-pass filtered process forces or position control deviations, if sensitive to failure in a machine tool with linear direct drives, are also sensitive to failure in other machine tools. Also, low-pass filtered process forces were the most similar signals among the investigated machines. Possible causes that impair the similarity of signals among machine tools are discussed.

AB - For a monitoring system to provide considerable performance, it usually requires machine- and process-specific information. This includes information about which process signals are sensitive to failures and which signal behavior indicates these failures. However, this information is mostly unavailable when monitoring the manufacturing of individual parts or small series. The transfer of process-specific information among similar machine tools can provide the required information, thereby improving monitoring performance. Nevertheless, no systematic research exists on what process signals are best suited for such an information transfer. This paper investigates a) whether information about the sensitivity of a signal to failures is transferrable among multiple machine tools and b) whether the behavior of these signals, modelled as probability distributions, is similar among multiple machine tools. Initially, a measure is introduced that quantifies the capability of a signal to separate two process conditions, the signal overlap factor SOF. It is then demonstrated how the SOF can be calculated for transient process conditions. The SOF is then empirically determined for a set of process signals for three different machine tools, individually, to assess failure-sensitivity of the signals for slot milling in steel. Additionally, the SOF is calculated for the union of the data of the machine tools to assess the similarity of signals among machine tools. The set of evaluated process signals includes process forces, the torque of the main spindle, and the torque and position control deviation of the feed axes. All machine tools were operated with identical instructions, tools, and materials. Bores were machined in workpieces to simulate material anomalies. Results suggest that low-pass filtered process forces or position control deviations, if sensitive to failure in a machine tool with linear direct drives, are also sensitive to failure in other machine tools. Also, low-pass filtered process forces were the most similar signals among the investigated machines. Possible causes that impair the similarity of signals among machine tools are discussed.

KW - fleet monitoring

KW - machine tools

KW - process monitoring

KW - similarity measure

UR - http://www.scopus.com/inward/record.url?scp=85184593718&partnerID=8YFLogxK

U2 - 10.1016/j.procir.2023.09.101

DO - 10.1016/j.procir.2023.09.101

M3 - Conference article

AN - SCOPUS:85184593718

VL - 120

SP - 922

EP - 927

JO - Procedia CIRP

JF - Procedia CIRP

SN - 2212-8271

T2 - 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023

Y2 - 24 October 2023 through 26 October 2023

ER -