DETECTION OF WEAR PARAMETERS USING EXISTING SENSORS IN THE MACHINES ENVIRONMENT TO REACH HIGHER MACHINE PRECISION
Journal Title: Journal of Machine Engineering - Year 2018, Vol 18, Issue 2
Abstract
This paper presents methods to plan predictive maintenance for precision assembly tasks. One of the key aspects of this approach is handling the abnormalities during the development phase, i.e. before and during process implementation. The goal is to identify abnormalities which are prone to failure and finding methods to monitor them. To achieve this, an example assembly system is presented. A Failure Mode and Effects Analysis is then applied to this assembly system to show which key elements influence the overall product quality. Methods to monitor these elements are presented. A unique aspect of this approach is exploring additional routines which can be incorporated in the process to identify machine specific problems. As explained within the paper, the Failure Mode and Effects Analysis shows that the resulting quality in a case study from a precision assembly task is dependent on the precision of the rotational axis. Although the rotational axis plays a significant role in the resulting error, it is hard to explicitly find a correlation between its degradation and produced parts. To overcome this, an additional routine is added to the production process, which directly collects information about the rotational axis. In addition to the overall concept, this routine is discussed and its ability to monitor the rotational axis is confirmed in the paper.<br/><br/>
Authors and Affiliations
Ricarda Regina SCHMITT, Robert DECRESSIN, Franz DIETRICH, Klaus DRÖDER
Keywords
Related Articles
- EP ID EP346533
- DOI 10.5604/01.3001.0012.0935
- Views 54
- Downloads 0
DEVELOPMENT OF AN AUTOMATED ASSEMBLY PROCESS SUPPORTED WITH AN ARTIFICIAL NEURAL NETWORK
A central problem in automated assembly is the ramp-up phase. In order to achieve the required tolerances and cycle times, assembly parameters must be determined by extensive manual parameter variations. Therefore, the d...
MACHINE TOOL DISTORTION ESTIMATION DUE TO ENVIRONMENTAL THERMAL FLUCTUATIONS ― A FOCUS ON HEAT TRANSFER COEFFICIENT
Thermally induced errors have been approached in multiple ways due to the influence these have over the positional accuracy of a machine tool. Here, approaches regarding environmental thermal fluctuations surrounding a...
APPLICATION OF COMPLEX GAME-TREE STRUCTURES FOR THE HSU GRAPH IN THE ANALYSIS OF AUTOMATIC TRANSMISSION GEARBOXES
In the article was discussed the possibility of structures and information systems complex game trees for the analysis of automatic gearboxes. The purpose of modelling an automatic gearbox with graphs can be versatile,...
Cutting layer and cutting forces in a 5-axis milling of sculptured surfaces using the toroidal cutter
The purpose of this article was to evaluate the significance of the influence of five- axis orientation parameters of a toroidal cutter axis and the geometrical parameters of the machined sculptured surface on the inters...
AUTOMATED ROOT CAUSE ANALYSIS OF NON-CONFORMITIES WITH MACHINE LEARNING ALGORITHMS
To detect root causes of non-conforming parts - parts outside the tolerance limits - in production processes a high level of expert knowledge is necessary. This results in high costs and a low flexibility in the choice o...