Abstract: In response to the issues of the disposal of waste equipment in colleges and universities and the cultivation of students’ practical abilities, this paper proposes a teaching design based on “waste equipment disassembly, image recognition, and reassembly and innovation”. This design aims to make full use of the residual value of waste equipment and enhance the practical operation, theoretical application, and problem-solving abilities of engineering students. The teaching is divided into three stages: “Disassembly”, “Observation”, and “Innovation”, “Disassembly” allows students to gain a deep understanding of its internal structure and principles. “Observation” uses artificial intelligence technology to assist in fault identification, cultivating students’ ability to quickly and accurately locate faults and master diagnostic methods. “Innovation” exercises students’ comprehensive application of knowledge, creative thinking, and practical operation, achieving the transformation from theory to application. Compared with traditional equipment disassembly and assembly teaching methods, this design, by incorporating image recognition technology, accomplishes dynamic fault categorization, creates an iteratively updatable cloud-based image library, and motivates cross-system reconfigurative innovation, thereby enhancing the efficiency of practical operations. This teaching method uses waste equipment to improve students’ operation and innovative thinking abilities.