İşletmelerin kendilerini farklılaştırarak rekabet ortamında ayakta kalabilmeleri; kalitenin yaratılması, korunması, geliştirilmesi ve iyileştirilmesi gibi konulara eğilmeleri ile mümkün olmaktadır. Bu amaçla birçok kalite iyileştirme yöntemi geliştirilmiştir. Bu yöntemlerin başında Kalite Fonksiyon Göçerimi (KFG) ve Hata Türü ve Etkileri Analizi (HTEA) gelmektedir. Yöntemlerin bazı eksiklikleri bulunmaktadır. Literatürde bu eksiklikleri gidermek için KFG ve HTEA, bulanık mantık ve bulanık küme teorisi ile birleştirilerek bulanık HTEA ve bulanık KFG olarak düzenlenmiştir. Bu çalışmada da bulanık KFG ve HTEA’nın kablo sektöründe uygulanabilirliği gösterilmeye çalışılmış, bulanık KFG ile bir kablo işletmesi için ürün geliştirilmiş ve bu ürünün gerçekleşmesi esnasında çıkabilecek hata türleri, bulanık HTEA ile belirlenmiş ve risklerine göre sıralanmıştır. Tüm değerlendirme süreçlerinde karar vericiler, doğal dile dayanan sözel terimleri kullanmıştır.

The survival of the companies by differentiating themselves in a competitive market is only possible by tending the issues such as creation, protection, development and improvement of the quality. That requires the quality to be measured and analyzed. With this aim many quality improvement methods have been developed. Quality Function Deployment (QFD) and Failure Mode and Effects Analysis (FMEA) come at the beginning of these methods. Quality Function Deployment (QFD) is a customer-driven quality management and product development system for achieving higher customer satisfaction. The basic concept of QFD is to translate the customer requirements into product design or engineering characteristics and subsequently into parts characteristics, process plans and production requirements. Each translation uses a matrix, called the house of quality (HOQ) which provides a conceptual map for the design process, as a construct for understanding customer requirements and establishing priorities of engineering characteristics to satisfy them. Decision making process of QFD is based on subjective judgments and evaluations and linguistic terms such as ‘low importance’, ‘high importance’, ‘strong relationship’ and ‘weak relationship’ are usually used by decision makers. Most of these linguistic input variables are assumed to be precise and treated as numerical data. And also the data available for product design is often limited and may be inaccurate because of the uncertainties in the design process especially when a new product is developed, a certain degree of vagueness is often inevitable. Failure Mode and Effects Analysis (FMEA) is a powerful method for system safety and the reliability analysis of products and processes in a wide range of industries. FMEA is a method that determines current or possible failure modes in the product, the process or the system as well as the causes, the effects and the occurrence frequency of these failure modes. FMEA also ranks the failure modes according to their risks as a result of these determinations. So the main objective of FMEA is to determine and prioritize the potential failure modes that could have a detrimental effect on the system and its performance. FMEA uses the risk priority number (RPN) while ranking the failure modes. The RPN is obtained by multiplying of three factors, which are the probability of failure, the severity of the failure and the probability of not detecting the failure. Some drawbacks have emerged as a result of increasing industrial applications of FMEA. The main drawback of RPN is various sets of probability of failure, the severity of the failure and the probability of not detecting the failure may produce same value of RPN, however, the risk implication may be totally different and may result in high-risk events going unnoticed. The other important drawback of the RPN ranking method is that it neglects the relative importance among probability of failure, the severity of the failure and the probability of not detecting the failure. The three factors are assumed to have the same importance but this situation is not suitable real life practical applications. And also FMEA has inability of modeling the qualitative data applied during evaluation period as well as the ambiguity of expert judgements used in the case of inadequate historical data regarding the product and process under examination. In order to eliminate these drawbacks of QFD and FMEA, in the literature these methods have been combined with fuzzy logic and fuzzy set theory and organized as fuzzy QFD and fuzzy FMEA. Fuzzy sets and fuzzy logic are powerful mathematical tools for modeling uncertain systems in many areas while making decisions in the absence of complete and precise information. A fuzzy set is an extension of a crisp set and it is characterized by a membership function which assigns to each object a grade of membership ranging between zero and one. In this study efforts have been made in order to indicate the feasibility of fuzzy FMEA and fuzzy QFD in the cable production sector. These methods have been applied to a real industrial case, which refers to one of the biggest cable company operated in Denizli, Turkey. A product for a cable company has been developed using fuzzy QFD. In this study the four-phase decision process has been considered. First of all the house of quality has begun with the customer attributes about the cable and then engineering characteristics have been defined by the company. The body and the roof of the house have been filled and the most important engineering characteristic has been found. In the next phase of this method, part matrix has been organized with the result of the first phase and the most important part characteristic of the cable has been found. In the third phase process matrix has been organized and the most important process during producing the cable has been found. And finally the production matrix has been organized and the most important production requirement or control action which is needed during the design and production processes for the cable has been found. After defining the most important engineering characteristic, part, process and control action of the cable, potential failure modes which might occur in the engineering and part characteristic, production process and the control action have been determined and evaluated in terms of occurrence of failure, the internal severity of the failure, the external severity of the failure and not detecting the failure by the decision makers. The decision makers in the cable company have used linguistic variables during evaluation process. Finally the determined failure modes have been ordered using fuzzy FMEA according to their riskiness. So the difficulties like the lack of enough information during the product development process or problems regarding the non-assignment of precise values for the risk factors concerning failure modes have been eliminated via fuzzy logic approach. From now on, the company will get a new ranking for every new product by adding new failure modes and be careful against the unexpected situation during the new product development. It’s thought that these methods will serve as early warning system for the company.