Method of Forming an Updated List of Technical Products Fuzzy Quality Indicators Based on Fuzzy Clustering

At the stage of the technical products’ production planning, the key point of the success for meeting the customer’s expectations is to determine customer’s needs and to convert these needs into product characteristics, which are eventually reflected in the formed product quality indicators list. To monitor quality indicators at the production stage manufacturers often use the theory of fuzzy sets to combine several groups of quality indicators into one indicator, which simplifies the process of monitoring and evaluating product quality, but complicates the process of interpreting these indicators on the principle of “acceptable – not acceptable”. To solve the problem of interpretation, an updated list based on fuzzy sets should contain not only information about the types of quality indicators, but also information on evaluation or measurement scales for each product quality indicator. In this paper, we propose a method for forming a gradations scale for product quality indicators based on fuzzy clustering. A method for forming a rank scale used for particular indicators in a two-level product quality optimization model is developed and justified. The proposed method of a fuzzy term set constructing allows to solve the problem of determining an updated list of fuzzy quality indicators.