Design of a sweeping robot based on fuzzy QFD and ARIZ algorithms

Abstract

The design of a multifunctional intelligent robotic vacuum cleaner is essential for meeting user needs and replacing human cleaning tasks, thereby improving the effectiveness and convenience of human-robot interaction. Existing robotic vacuum cleaners can address the issues of small dust and hair accumulation; however, a comprehensive and integrated solution for sweeping, mopping, sanitizing, and general waste cleaning remains necessary. This paper employs the Fuzzy Quality Function Deployment (FQFD) tool and the Algorithm for Inventive Problem Solving (ARIZ) algorithm to address these challenges. The research framework integrates FQFD with the Fuzzy Analytic Hierarchy Process (FAHP) methodology to evaluate the weights of user requirements for a robotic vacuum cleaner. Subsequently, these requirements were translated into technical specifications, thus establishing a link between user needs and technical requirements. The ARIZ algorithm is subsequently employed to resolve conflicts and inconsistencies within the FQFD model. Finally, an innovative design for a robotic vacuum cleaner was proposed by utilizing the ARIZ algorithm's problem-solving principles and qualitative and quantitative insights derived from the FQFD. The design is evaluated using the Fuzzy Order Preference Technique (FTOPSIS) method, which resembles the ideal solution. Furthermore, the operational dynamics of the critical components of the design solution that navigate obstacles are analyzed to ensure their effectiveness. The final product can effectively replace humans in complex cleaning tasks while navigating obstacles during sweeping, mopping, and sanitizing for comprehensive space cleaning. The results of this study provide valuable insights for designers to enhance user experience, improve customer emotional satisfaction, and guide future product designs in related product development initiatives.