Preventive Maintenance Manager design pattern for component based machine tools

2011 ◽  
Author(s):  
F. Serna ◽  
C. Catalan ◽  
A. Blesa ◽  
J. M. Rams ◽  
J. M. Colom
Keyword(s):  
Preventive Maintenance ◽  
Machine Tools ◽  
Design Pattern

“Predictive maintenance surveyor” design pattern for machine tools control software applications

ETFA2011 ◽  
2011 ◽  
Author(s):  
Felix Serna ◽  
Carlos Catalan ◽  
Alfonso Blesa ◽  
Jose Manuel Colom ◽  
Josep M. Rams
Keyword(s):  
Machine Tools ◽  
Design Pattern ◽  
Predictive Maintenance ◽  
Control Software ◽  
Software Applications

Frühzeitige Detektion von Oberflächenzerrüttungen/Premature detection of surface disruption – Deep Learning-based method for classification of damage on ball screw drives

2020 ◽  
Vol 110 (07-08) ◽  
pp. 501-506
Author(s):  
Peter Ruppelt ◽  
Tobias Schlagenhauf ◽  
Jürgen Fleischer
Keyword(s):  
Deep Learning ◽  
Early Detection ◽  
Preventive Maintenance ◽  
Machine Tools ◽  
Industry 4.0 ◽  
Industrie 4.0 ◽  
Ball Screw ◽  
Camera System ◽  
Ball Screw Drives

Die Zustandsüberwachung von Anlagen, Maschinen und deren Bauteilen ist eine zentrale Thematik von Industrie 4.0. Unvorhergesehene Ausfälle von Werkzeugmaschinen sind häufig auf den Verschleiß und das daraus resultierende Versagen von Kugelgewindetrieben zurückzuführen. Aufgabe dieser Arbeit ist die frühzeitige Detektion von Oberflächenschäden auf der Kugelgewindetriebspindel mit einem elektromechanischen Kamerasystem in Kombination mit Deep-Learning-basierten Modellen, um entsprechende Wartungsmaßnahmen abzuleiten.   Condition monitoring of plants, machines and their components is a central topic of Industry 4.0. Unforeseeable failures of machine tools are often caused by wear, resulting in failure of ball screws and subsequent surface disruptions. This article describes how image-based monitoring of ball screws by an electronic camera system in combination with deep learning-based models enable the early detection of surface disruptions and to derive appropriate and preventive maintenance measures.

scholarly journals Development of Sensing Interface for Preventive Maintenance of Machine Tools

Procedia CIRP ◽  
2017 ◽  
Vol 61 ◽  
pp. 796-799 ◽  
Author(s):  
Makoto Fujishima ◽  
Masahiko Mori ◽  
Kimiyuki Nishimura ◽  
Masakazu Takayama ◽  
Yasutaka Kato
Keyword(s):  
Preventive Maintenance ◽  
Machine Tools

Sensitivity Analysis of Cost Parameters of Sequential Imperfect Preventive Maintenance Model and Applications

2011 ◽  
Vol 480-481 ◽  
pp. 1210-1214 ◽  
Author(s):  
Zhi Ming Wang
Keyword(s):  
Sensitivity Analysis ◽  
Preventive Maintenance ◽  
Machine Tools ◽  
Optimal Number ◽  
Cost Ratio ◽  
Nc Machine ◽  
Nc Machine Tools ◽  
Cost Parameters ◽  
Maintenance Model ◽  
Weibull Process

Maintenance intervals and the optimal number of maintenance N*of NC machine tools in infinite time horizon are presented using a hybrid sequential imperfect preventive maintenance (PM) model. The failures of NC machine tools are described using Weibull process. Sensitivity analysis of cost parameters is given to show how the optimal results depend on the different cost parameters. The results show that when the shape parameter β of Weibull process within the range of [1.1,1.3], N* is slightly affected by β and cost ratio cr /cp. However, when the value of β is greater than 1.4, the effect of β and cr /cp to N* is significance. If an equipment is in wear later stage or PM actions are not too effective to it, it is not suitable to add the number of maintenance.

The Chatterbox: A Device for Hearing Chatter as Sections are Cut

1973 ◽  
Vol 31 ◽  
pp. 360-361
Author(s):  
C. W. McCutchen ◽  
Lois W. Tice
Keyword(s):  
Machine Tools ◽  
Cutting Tool ◽  
Guerilla Warfare ◽  
History Of ◽  
Chatter Marks

Ultramicrotomists live in a state of guerilla warfare with chatter. This situation is likely to be permanent. We can infer this from the history of machine tools. If set the wrong way for the particular combination of cutting tool and material, most if not all machine tools will chatter.In more than 100 years since machine tools became common, no one has evolved a practical recipe that guarantees avoiding chatter. Rather than follow some single very conservative rule to avoid chatter in all cases, machinists detect it when it happens, and change conditions until it stops. This is possible because they have no trouble telling when their cutting tool is chattering. They can see chatter marks, and they can also hear a sometimes deafening noise.

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