06-03-2013, 11:38 AM
Machine Tool Failure Data Analysis For Condition Monitoring Application
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ABSTRACT
With the development of modern manufacturing technology, Flexible Manufacturing Systems (FMSs) have become key equipment in factory automation. Machine tools are heart of the Flexible Manufacturing Systems. Lathe, milling and grinding machines are the general type of machine tools used by almost all the FMSs. During the operation of these machine tools, different kinds of failures are faced by the industry. A systematic study of such failures can help in identifying the critical sub-system of these machine tools. This will be useful for identifying the condition monitoring needs of the machine tools. This paper deals with the identification of critical sub-system based on the failure data analysis for different type of machine tools.
INTRODUCTION
Technologies have been developed rapidly in recent years and in due course the manufacturing environment is also changing its features rapidly. In machining activities, the traditional role of machine tool operators is being replaced more and more by the intelligent controllers. With the developments in manufacturing technology, FMSs have become key equipment in factory automation. This kind of manufacturing method is being used more and more widely because of its potential to improve the strategic and competitive position of firms. For advanced supervisory tasks, people usually staying away from the real machining spots, control and monitor the machining processes by means of computer terminals. However, such manufacturing environment is dependent upon the trouble-free operation of all its component parts. In order to reduce maintenance time detecting and diagnosing process failures quickly becomes a crucial task. Upto 80% of the downtime is spent locating the source of fault [1].
FAILURE DATA COLLECTION AND ANALYSIS
Failure is defined as the termination of the ability of an item to perform its specified function. Data on failures are considered as a health report of any machine tool system. It was difficult to collect field failure data on machine tools several years ago, because users hardly kept adequate and complete maintenance records beyond the warranty period. In this computerized maintenance environment, users feel encouraged to keep the systematic maintenance records of their machineries. Failure data were collected for a period of five years on several conventional machine tools such as lathe, milling and grinding machines. It contained the following information:
o Product name, model and size
o Product code
o Reported time & date of failure
o Failure phenomena
Failure Data Analysis of Lathe
Initially lathe has been classified into various sub-systems as shown in Fig. 1. In an earlier study [4] the frequency of failures for each sub-system and failure modes have been considered for finding out the weakest sub-system. In the present analysis, failure frequency and downtime have been taken into consideration for deciding critical sub-systems of machine tools. It can be seen from the Fig. 2 that the maximum failures took place in headstock and carriage sub-systems. These sub-systems face failures in components like gear, gearbox bearing, spindle bearing, clutch and cross-slide jib. Here it could be observed that the bearing failures cause longer downtime.
CONCLUSION
The failure data have been collected and analysed systematically for several commonly used machine tools like lathe, milling and grinding machines. The critical sub-system has been identified for each type of machine tool based on number of failures and downtime hours.