# Research on Reliability Assessment of Mechanical Equipment Based on the Performance-Feature Model
## 1 Introduction  
Reliability assessment for mechanical equipment is important in condition-based maintenance to lower cost and improve equipment reliability, thus, it emerges repeatedly and has become an important research area for mechanical equipment reliability analysis and life prediction [1; 2; 3]. [PERSON] [4] proved that the bounded intensity process was suitable for reliability assessment of deterioration in machine tools with frequent maintenance actions. How to assess reliability is also helpful for predictive life [5] and maintenance time [6]. Performance degradation is one of the most important elements during machining, which has a close relationship with product precision, by influencing the total manufacturing effectiveness and stability of machine tools. In most circumstances, performance degradation is the main failure for mechanical equipment and leads to the waste of product and time. In addition, equipment condition is closely related to a machine's efficiency and productivity, therefore, research on reliability assessment of mechanical equipment is important, based on performance degradation analysis [7].  
As an important concern during processing, several studies are being conducted by many researchers for reliability assessment. The traditional reliability evaluation method is usually based on the failure life data [8], and the failure life time is obtained through the life test and accelerated life test. The main function of the reliability life test is to process indiscriminate failure life data andrealize the reliability evaluation of the product through the test, which cannot effectively understand product failure process and failure mechanism and cannot contribute to product reliability growth. Traditional reliability analysis is based on the probability statistics method for the failure data from a large sample, so failure data with a small sample is difficult to effectively analyze. For high reliability and long-life products, it is difficult to get failure life time through the life test and accelerated life test. Therefore, there are many new reliability evaluation methods. [PERSON] [9; 10] proposed a new reliability evaluation model based on quality loss and quality characteristics evolution. [PERSON] [11] studied the tool reliability evaluation based on acoustic emission signals. Meanwhile, this equipment performance degradation data can provide important information for reliability evaluation, thus, two reliability evaluation methods based on performance degradation data were presented, i.e., reliability evaluation method based on degradation path and reliability evaluation method based on performance degradation distribution [12; 13]. The reliability estimation approaches of mechanical equipment are based on the historical performance degradation data, amongst which statistical distribution models [14] have been used in this area, such as the regression model [15], exponential distribution, and Weibull distribution [8; 16; 17; 18]. In this research, a novel method for reliability assessment of mechanical equipment based on process signals and degenerate data was developed. Performance degradation data and process signals for mechanical equipment were used fit the degradation path for reliability assessment. This kind of method depended on sizable historical data and sensor signals from related equipment, and an experiment data set of tool wear was used to verify the effectiveness of the method. The results showed that this method could benefit reliability assessment. This paper was structured as follows. Section 2 introduced some basic theories of this method and the flow path in detail. Section 3 provided a general process of reliability assessment based on degradation paths. Section 4 used experimental data to verify the method. In this section, the feasibility and practicability of this method were proved. Concluding remarks were given in Section 5.