Integrated autonomous monitoring of ball screw drives

Möhring, Hans‐Christian; Bertram, Oliver

doi:10.1016/j.cirp.2012.03.138

Cited by 33 publications

(13 citation statements)

References 14 publications

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“…Taking this into consideration, the DiaForce ® coating by the Fraunhofer Institute for Surface Technology was chosen. A similar sensor was already successfully used by [25]. There it was used on a pin in a double nut arrangement to monitor preload.…”

Section: Resultsmentioning

confidence: 99%

Load Measurement in Linear Guides for Machine Tools

Krampert

Unsleber²,

Janssen³

et al. 2019

Sensors

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Process force determination in machine tools is an important topic for both optimization of manufacturing processes as well as predictive maintenance purposes. This work aims at providing a short overview of existing methods, motivating the integration of sensors into a linear guide, and then showing the results of an implemented new method for capturing the load on a rolling element linear guide by measuring the stresses resulting from the rolling element contact at the side of the runner block. The implementation of the approach is based on the piezoresistive diamond like carbon (DLC) coating DiaForce® provided by the Fraunhofer Institute for Surface Engineering and Thin Films (IST), Braunschweig, Germany. Good agreement of measurements with analytical and finite element method simulation results promises a stable modeling and load estimation process. Nevertheless, non-idealities due to high temperature dependency and cross-sensitivity to non rolling element contact related stresses could be shown, but also an efficient approach to diminish these effects is included.

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Section: Resultsmentioning

confidence: 99%

Load Measurement in Linear Guides for Machine Tools

Krampert

Unsleber²,

Janssen³

et al. 2019

Sensors

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“…Model based maintenance has also supported the planning and prognostics research along with a life cycle management perspective [31,77,163,164]. In recent years, study of degradation, automation of maintenance-repair-overhaul (MRO) and virtual reality applications to support maintenance has gained significant interest [78,111,115,122,129,156]. This keynote focuses on the recent technological knowledge challenges at the component and system level and presents major research trends inside and outside the CIRP community.…”

Section: Introductionmentioning

confidence: 98%

Continuous maintenance and the future – Foundations and technological challenges

et al. 2016

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“…Piezoresistive thin films ( Biehl, Staufenbiel, Recknagel, Denkena & Bertram, 2012 , Möhring & Bertram, 2012 )…”

Section: Introductionunclassified

A Sensor-based Method for Diagnostics of Geometric Performance of Machine Tool Linear Axes

Vogl

Calamari

et al. 2016

Procedia Manufacturing

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A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a ‘sensor box’ to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality.

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Integrated autonomous monitoring of ball screw drives

Cited by 33 publications

References 14 publications

Load Measurement in Linear Guides for Machine Tools

Load Measurement in Linear Guides for Machine Tools

Continuous maintenance and the future – Foundations and technological challenges

A Sensor-based Method for Diagnostics of Geometric Performance of Machine Tool Linear Axes

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