Chaoan Lai, Xingbin Guan and Xionghui Wen Pages 75 - 82 ( 8 )
Background: Due to the recent surge in high-rise buildings and airport truss, demands for high-altitude cleaning have become more and more strident, bringing many opportunities and much potential for the development of the industry. The technology insufficient of current patents of high-altitude cleaning robot causes difficulty in obstacle climbing and balance adjusting, and generates high costs. Patent analysis is an important tool for industry planning and technique forecasting. As one of the methods of patent analysis, data mining will be of high priority.Objective: The purpose of this study is to find out potential high-altitude cleaning techniques and products, to point out the direction of innovation for general enterprises. Methods: In this paper, first, data mining is used for patent analysis. An analysis framework with the combination of basic patent analysis and knowledge map is constructed. Multi-dimension analysis and TRIZ knowledge base are integrated into the knowledge map in order to analyze the competition status, development trajectory and technique opportunities of high-altitude cleaning industry. Results: According to the directions in the knowledge map, eight technology evolution rules and inventive principles of TRIZ and a new scheme of air cleaning robot with the advantages of light weight, flexibility and self-adaption are created in this paper. Conclusion: The future techniques and products include ultrasonic cleaning, visual real-time remote control, double-face or multi-face cleaning, tracks with variable structures and cleaning head based on the effect of “rotating double curved surface”. Through vacuum chamber, the goals of automatic absorption, dust collection and cleaning, and self-balancing can be achieved.
Data mining, high-altitude cleaning, knowledge map, multi-dimension analysis, patent analysis, TRIZ.
School of Business Administration, South China University of Technology, Guangzhou, 510640, School of Business Administration, South China University of Technology, Guangzhou, 510640, School of Business Administration, South China University of Technology, Guangzhou, 510640