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In response to the new industrial revolution, General Electric (GE) developed the first industrial Internet platform, Predix, to meet its large-scale industrial analytics (Chen et al., 2018). Subsequently, more and more industry Internet platforms have been produced, such as Bosch IoT Suite, Kaa IoT Platform, and COSMOPlat. However, as industry Internet platform is a new product, most research mainly focuses on opportunities, challenges, factors, etc. (Chen et al. 2018; Sisinni et al. 2018). However, the research on the risk management of the industrial Internet platform is limited. Therefore, in this paper, we will introduce the framework of FMEA to reduce the problems and challenges.
FMEA, developed by NASA in the 1960s, is a useful risk management tool and engineering technique to manage the quality and reliability of products (Baykasoglu et al., 2020; Liu et al., 2018). FMEA was introduced into the automobile industry in the 1970s (Zhou et al., 2016). After many standardization efforts, such as International Organization for Standardization (ISO) 9000 series, FMEA has become one of the most important risk management and reliability analysis tools (Baykasoglu et al., 2020). Nowadays, it has been widely utilized in industrial systems, designs, and production to identify and solve potential failures (Kutlu et al., 2012). Unlike other reliability management tools that look for solutions after failures occurred, FMEA can previously identify and eliminate known or potential failures in a system and prevent them from happening (Huang et al., 2017; Liu et al., 2018b). Owing to its advantages, FMEA has been widely applied to various fields, such as marine (Bashan et al., 2020; Chang et al., 2021), aircraft (Daneshvar et al., 2020), cold-chain logistics management (Wu et al., 2021), healthcare services (Liu et al., 2018c), new energy resources (Duan et al., 2019; Karatop et al., 2020), and semiconductor manufacturing (Jee et al., 2015; Kerk et al., 2017).
The traditional FMEA mainly includes the following several stages: (1) Identify known or potential Failure Modes (FMs); (2) Confirm the cause and effect of every FM by DMs; (3) Calculating the Risk Priority Numbers (RPNs) of FMs, the product of three RFs: Occurrence (O), Severity (S) and Detection (D); (4) Rank the FMs according to the RPNs by descending order; (5) Take remedial actions for the high-risk FMs (Liu et al., 2018c; Huang et al., 2020; Liu et al., 2015).