## 1 Introduction  
Interactive systems are closely related to people's lives. Designing interactive systems involves many different types of products, such as software systems, interactive products, and environments. The goal of designing interactive systems is to make them enjoyable to use, enable them to perform useful tasks, and improve the quality of life for those who use them. In other words, interactive systems should provide a good user experience (UX). UX involves developing high-quality interactive systems that fit with people and their ways of living [1]. Designers need to place users at the center of the design process and eliminate the failure modes that harm users the most. Generally, a failure mode in UX is an action that causes a user to stray from the path to successful completion. To enhance UX, a systematic approach to prioritizing the failure modes related to UX is needed. Several studies have been conducted on prioritizing failure modes related to UX. [PERSON] [2] used severity to rank the failure modes, and the failure modes were rated as high, medium, or low. The failure modes were prioritizedbased on severity level. Besides severity, there are other factors affecting the risk of failure models. [PERSON] and [PERSON] [3] used criticality, which was the combination of severity and probability, to rank the failure modes related to UX, and categorized the failure modes into seven levels. [PERSON] and [PERSON] [4] employed a decision tree that was constructed by using three questions (What is the impact of the failure mode? How many users are affected by the failure mode? Will users be bothered by the failure mode repeatedly?) to rank the failure modes and categorize them as low, medium, serious, and critical. These studies all focused on prioritizing failure modes related to UX; however, they did not systematically consider the risk factors that affect the priorities of failure modes. Failure mode and effect analysis, commonly referred to as FMEA, is a meticulously systematic approach that is utilized for the identification and prevention of potential product or process failure modes before they even have a chance to occur [5]. FMEA is a proactive risk management tool that concentrates on preventing defects, enhancing safety, and boosting customer satisfaction [6]. Using FMEA, the risk priority number (RPN) that involves the severity, occurrence, and detection of failure modes can be determined, and the failure modes can be prioritized through the RPN. However, if two failure modes have the same RPN, it is not possible to distinguish between the prioritizations of the two failure modes [7]. For the UX of interactive system design, the failure modes under consideration are human errors or difficulties rather than mechanical or electronic component failure modes, and thus the risk factors including occurrence, severity, and detection are subjective and even subconscious, making them difficult to use exact numbers for estimation [8]. To deal with these situations, FMEA needs to be combined with other methods. Several studies have combined fuzzy logic with FMEA for the assessment of risk factors [9; 10]. Compared with traditional FMEA, fuzzy logic-based FMEA has the following advantages: it allows the analyst to employ linguistic terms to evaluate the risk factors and can yield more accurate results [11]. Fuzzy logic-based FMEA has been studied in various fields, such as the aerospace industry, construction industry, and process industry [12; 13]. Nevertheless, to the best of our knowledge, very few studies have been devoted to employing fuzzy logic-based FMEA to improve the UX of interactive system design. When carrying out FMEA for the best results, a team is needed [14]. To aggregate the team members' opinions concerning risk factors of failure modes, many studies used average value [15]. However, when there exist extreme values, the extreme values can be averaged, and the preference values of experts could be diminished.