Fuzzy Reliability Research Of Machining Center

Machining Center is typical product which combines modern information science and technology with the traditional mechanical combination, to measure a country's degree of technological development and the development level of the manufacturing sector. Promotion of the machining center reliability of manufacturers has now become their key to survival and development. In an increasingly competitive market circumstances, only the machining centers which have high reliability can be the user's favorite. The reliability of machining centers becomes an important criterion for users. China in recent years in the field of production and application haves a rapid development, However, compared with the industrialized countries, there is still a wide gap between the machining centers, so improving the reliability of the machining center has become the major problem which machine tool manufacturer face. The purpose of this article is to improve the reliability of machining centers, and the structure shown in Diagram 11,Fuzzy reliability of Machining Center Mean time between failures (MTBF) is the main reliability index of machining center, conventional reliability theory has been not able to meet the practical requirements, And the ambiguity haves a wide range existence in machining, and when there are smaller samples, the fuzzy reliability analysis will play a decisive role in it. In this article, fault data of a certain series of machining center for analysis is collected in a domestic machine tool company. Combining conventional reliability theory and fuzzy theory, get the important indicator of reliability, that is the average time between failures of fuzzy, the process shown in Figure 2. By the analysis of the data failure of machining center, and the application of conventional machining center reliability, we know that the type of failure time distribution is Weibull distribution, and get the probability density function f(t) and distribution function F(t) about time between failures. Application of fuzzy reliability theory turns reliability of machining center to be fuzzy and get eight fuzzy sets. And through membership function get fuzzy reliability function, and get important reliability index-the average time between failures fuzzy.2,Failure Mode Effect and Criticality AnalysisAccording to the collected machining center failure data, I use method of failure mode effect and criticality analysis, the overall failure analysis as shown in table 1. Tool storage of the machining center is the most frequent failure site, and its failure rate was significantly higher than other parts or subsystems. Mainly performance: the tool storage could not change tools, tools changing time is too long, tool changing arm can not come back original location and can not open the doors, and the tools have vibration when rotating. Secondly, electrical system failures are also more. Mainly performance: components damaged, short circuit, the fixture can not open, the fixture do not release, the lights damage, etc. the main reason is the components damaged (35.48%), Loosening (22.58%), these two causes the total failure of more than 40% was significantly higher than other reasons, so they must be given sufficient attention. And fault-prone parts of FMECA analysis also. In addition, through machining center criticality analysis we known tool storage is the highest base system, is also the key components affecting the reliability of machining center. Secondly, the criticality of electrical system is at a high degree, so these two parts of the machining center can be said that the weak links. In addition, the feed system is also relatively weak compared to other parts, thus we can make sure the main direction that improving their reliability, and give the improvement of the machining center reliability a basis.3,Machining Center Allocation of fuzzy reliabilityThe reliability of the traditional allocation method or the reliability of the distribution does not take into account the impact of factors, or reliability of the distribution, taking into account the impact of factors, but not comprehensive enough. Thus, for the machining centers that the integration of complex mechanical and electrical equipment, when we take reliability of machining centers distribution, these traditional methods are not well marked completion. This complex distribution of system reliability, now there is no more appropriate way, but methods that combines the traditional theory of reliability distribution with fuzzy theory method can achieve good results. This machining center as series system divided into CNC system, tool storage, electrical systems, feed systems, the main transmission and spindle system, hydraulic systems, servo systems, lubrication systems, Chip system and cooling system, because only the various subsystems are normal working hours, the entire system to work properly. This article combines fuzzy theory, uses the expert fuzzy evaluation method, and consider the judgment of human brain about all aspects of the complex factors that affect machining center, the various factors and their evaluation criteria as shown in table 2.Deals with fuzzy information, and get machining center distribution coefficient by calculating, then gets the reliability of each subsystem, so completes the distribution of fuzzy reliability for machining center. The process will give knife Treasury, which haves very bad working environment, the higher complexity, longer working hours, lower reliability. While the process will give less complex, less maintenance and more importantly cooling system higher reliability, and the process is fully in line with the principle of distribution. Table continued:...