Challenges and opportunities of complex equipment operational reliability technology in industrial big data age

Abstract

Large and complex equipment reliability evaluation is extremely dependent on equipment reliability experiment data, maintenance records, and failure data. With the informationalization and intellectualization of equipment (such as CNC machine tools, shield machines, and weaponry), large amounts of data (big data) will be produced during the equipment's operation. Abundant data provide a strong support for equipment operational reliability analysis in the industrial big data age, but also pose a huge challenge for reliability analysis. This paper first explores the opportunities provided by big data to promote the reliability analysis and assessment of complex equipment. Then, we mainly focus on the remaining challenges of equipment operational reliability assessment using the industrial big data method, such as the fact that most of the data reflect an intermediate state (incomplete failure state) of the equipment. We also consider a way to analyze the multiple-states of the equipment operation and correlate the multiple failure modes of the equipment operation using the big data. Moreover, a big data analysis method for calculating the reliability and predicting the residual life of gradual systems is discussed, along with a method for combining the traditional reliability calculation theory with the big data theory. All of these issues provide a significant challenge for the reliability analysis of complex equipment in the big data age.