# Smart Product Design Process through the Implementation of a Fuzzy Kano-AHP-DEMATEL-QFD Approach
## Literature Review  
### Quality Function Deployment  
QFD, as well as the continuous improvement philosophies, has been developed to address manufacturing companies' problems, specifically new product development [15; 16; 17; 18]. These processes have been very tortuous, considering that the customer needs have not been properly identified nor prioritize, and the connection of those needs with the design and production factors has not been established either. This misconnection has avoided also the identification of how each one of the design or production factors has contributed to fulfilling each customer need. Therefore, QFD aims to provide a methodology that takes costumers' requirements as the main driver in the design process [15; 16; 19]. The problem lies in the existing misconnection between the what's and the how's. This misconnection can be found in all the company's processes, and it causes a waste of money and delays in product development and project implementation. Therefore, it is important for companies the implementation of a tool, which can help them to do the link between what's and the how's whether the application is a quality system or a product. This tool is Quality Function Deployment (QFD), also known as the House of Quality (HoQ) [20]. QFD can help companies and processes to close the gap between what is required and how to achieve those requirements. In the specific case of SAD, QFD will be a great approach to achieve proper product quality. Usually, QFD starts by collecting the costumers' needs or the Voice of the Customer (VOC). These customer needs are identified through surveys and are correlated with the design factors or specifications. This correlation process is performed in a matrix with the shape of a house [15]. When developing a new product, QFD has to be applied successively, to define the required process technology, specifications, and materials, for example [20; 21]. QFD, like many other methodologies, in which people must rank or weigh a particular group of aspects, has suffered from a lack of consistency when assigning weights, whether to the customer requirements or the design factors/actions (QFD in a design process). The opinions or preferences of the clients are presented in terms of numerical or linguistic scales, which are subjective, vague, and imprecise, and QFD does not perform in the best way if these aspects are not considered adequately [22]. Original QFD has been considered a manual approach and has also been known for having several limitations, such as long implementation time and subjective decision aid [22]. The weight given to each need by the customer gains reliability when estimated with AHP, considering that AHP has a consistency index that helps in identifying when corrupt data is going to be introduced to the model. In this way, it is possible to eliminate such data from the decision process, assuring the fact that data is trustable [23]. QFD's lack of consistency related to the translation of linguistic expressions of the customer needs into numeric satisfaction influence values has been also tackled integrating QFD with the Kano model. The importance of this integration is that though customer can assign a particular weight to a need (scoring, AHP, among others), customer is not truly aware of the type of need he/she is weighing, and, therefore, customer is not truly aware of the impact the absence or presence of the need in the product will have on its overall satisfaction. Kano model classifies each customer need in one of five main categories. Depending on which category the particular need is classified, it will have a particular influence on customer satisfaction [24; 25]. This situation is related to the fact that customers take some features for granted, and others are not even expressed, so the impact that each Kano category has on customer satisfaction or dissatisfaction will differ from the other categories. Some of these disadvantages have been identified by [PERSON] [12].