Quality function deployment approach based on hesitant fuzzy multi criteria decision making methods and an application in embroidery production

The importance of embroidery production has increased with the emergence of new markets in the textile industry. Embroidered fabrics used in outerwear, fancy clothing, and home textiles bring along customer expectations throughout the processes from design to production, in line with the increasing demand. Since embroidered fabrics are custom-made for customers, meeting their expectations is crucial. In this study, the Quality Function Deployment (QFD) method was used to investigate the characteristics of technical requirements and determine their priorities in order to provide customer-oriented and result-focused responses to customer demands in the shortest possible time. QFD is an important tool used in many manufacturing industries for planning management and transforms customer demands into technical requirements within the structure of the quality house. In doing so, it aims to determine the relationship between technical requirements and customer demands, taking into account the correlation that can be established among technical requirements. However, the traditional QFD method has been criticized for its shortcomings in gathering expert opinions, determining the weights of customer demands, and ranking technical requirements. QFD is a method that helps translate customer voice into engineering characteristics for a product or service, thus assisting in the development of the product or service and determining its features. In this study, in order to overcome the mentioned shortcomings and increase the effectiveness of this method, the integration of Multi-Criteria Decision Making (MCDM) techniques with the QFD method was implemented. Additionally, the Hesitant Fuzzy Linguistic Term Sets (HFLTS) were used to manage the uncertainty in the evaluation process. HFLTS is used to define decision-makers' preferences and transforms linguistic terms into mathematical forms. Triangular fuzzy numbers (TFN) are more commonly preferred due to their ease of use. It is possible for experts to express different opinions when evaluating the same alternative. This situation, which arises from their knowledge, experience, environment, problem solving approaches, cannot be ignored. If they are completely confident in their opinions, they can make an evaluation using a single linguistic term such as "the degree of occurrence of defects on the product surface is an important indicator." On the contrary, when they have doubts in their opinions, they can specify a range by saying "the degree of occurrence of defects on the product surface is between important and moderate" or they can make an evaluation with an open-ended statement by saying "the degree of occurrence of defects on the product surface is more than important". Based on this idea, the study is built on the foundation of the Hesitant Fuzzy Linguistic Term Sets (HFLTS) that have a flexible structure, which enables us to achieve the most suitable result and allows decision-makers to make multiple choices and describe their preferences. During the application, a group of experts consisting of knowledgeable individuals in the field was formed to determine the criteria and alternatives. These experts were selected from employees of the company where the study was conducted. These individuals, referred to as decision-makers, contributed to the study by utilizing their knowledge, expertise, and experience in the industry and production. In order to better manage the uncertainty that may arise when determining the opinions of experts during the evaluation process and when they have doubts or hesitation, hesitant fuzzy linguistic expressions were utilized. Additionally, the OWA operator was used to aggregate hesitant fuzzy linguistic expressions. Linguistic expressions are transformed into Hesitant Fuzzy Linguistic Term Sets (HFLTS). The Ordered Weighted Aggregation (OWA) operator is used to obtain the fuzzy envelope of HFLTS by considering the opinions of all decision-makers. In this study, an analytical model was presented by integrating the SWARA (Step-wise Weight Assessment Ratio Analysis), DEMATEL (Decision-Making Trial and Evaluation Laboratory), and MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) methods into the QFD method within the hesitant fuzzy environment. The importance values of customer requirements in the formation of the quality house structure were obtained using Hesitant Fuzzy SWARA, thus ensuring the weighting of customer requirements. The main difference between the hesitant fuzzy SWARA method and the traditional SWARA method lies in the use of hesitant fuzzy linguistic term sets. With using HFLTS, decision-makers can evaluate criteria using several linguistic terms to eliminate uncertainties they face during evaluation. Subsequently, the Hesitant Fuzzy DEMATEL method was used to determine the relationship between the identified technical requirements to meet customer demands. The key feature of the DEMATEL method is to propose the most influential alternative among the alternatives. Hesitant fuzzy sets are used to cope with uncertainties arising from human judgments during the evaluation of these alternatives. Therefore, in this study, the Hesitant Fuzzy DEMATEL method was employed to determine the relationship between technical requirements. Finally, the Hesitant Fuzzy MOORA methods were applied to evaluate the impact of technical requirements on customer requirements. This method supports the solution of decision-making problems by prioritizing and ranking alternatives. It is recommended to use hesitant fuzzy sets in conjunction with it to cope with uncertainties that may arise during decision-making. In this study, the Ratio Method and Reference Point approach of the Hesitant Fuzzy MOORA technique were utilized. The proposed model was implemented in a factory that manufactures embroidery in the textile sector to identify technical requirements that can meet customer demands and to prioritize them. The use of HFLTS allows decision-makers to express their evaluations more flexibly under uncertainty. Based on this, the aggregation of hesitant fuzzy linguistic evaluations with OWA was achieved. The Hesitant Fuzzy SWARA technique has the ability to evaluate decision-makers' linguistic expressions in calculating the weights of customer requirements, as it is an expert-oriented method that allows prioritization under uncertainty. The Hesitant Fuzzy DEMATEL technique was used to obtain the impact weights of technical requirements. It also has the ability to demonstrate the cause-effect relationship of technical requirements in the cause-effect diagram. The MOORA technique is a developed method for determining the prioritization of alternatives. The Hesitant Fuzzy MOORA technique has been an effective tool in determining the impact of technical requirements on customer requirements in hesitant situations in this study. This thesis aims to fulfill ten different customer demands with fifteen specified technical requirements. It includes an applicable method for businesses engaged in embroidery production in the textile sector. It enables the management of uncertainties on decision-makers through hesitant linguistic expressions. Its flexibility in usage allows for easy integration with decision-making techniques. Furthermore, the utilization of the OWA operator in the study contributes to the effective management of decision-makers preferences in evaluation input data. The integrated QFD methodology with decision-making techniques in the hesitant fuzzy environment, presented in this thesis, provides researchers with a comprehensive and systematic approach that can be applied to enhance product performance and customer satisfaction.