Design of a Disinfection and Epidemic Prevention Robot Based on Fuzzy QFD and the ARIZ Algorithm

Abstract

In the present era, against the background of normalized measures of epidemic prevention and control, a multi-function intelligent robot that can completely replace human beings in disinfection and epidemic prevention work needs to be designed in order to contain the spread of viruses at the source, to efficiently and conveniently serve the controlled regions, and to meet the needs of the current context. Existing disinfection robot designs only address the problem of disinfection; there is no disinfection robot that can achieve full-domain and full-space disinfection (including stairs), as well as having multiple epidemic prevention functions. The fuzzy QFD tool and the ARIZ algorithm were used here to solve the problems related to disinfection robots. By using fuzzy QFD as the research framework and combining it with fuzzy AHP to calculate the weight of demand for the disinfection and epidemic prevention robot, the authors further translated the demand into the technical and part characterization of the robot. The conflicts in the fuzzy QFD model were solved using the ARIZ algorithm. Finally, based on the solving principle of the ARIZ algorithm and the qualitative and quantitative conclusions of fuzzy QFD, a robot for disinfection and epidemic prevention was designed in a comprehensive manner. A robot that can completely replace human beings in the tasks of disinfection and epidemic prevention was designed in this work, solving the problems associated with the robot’s ability to climb stairs and realizing the innovation of the robot’s comprehensive disinfection, distribution of materials, real-time monitoring, temperature measurement, and other functions. This study provides a theoretical reference for the design of related products.