Research On Halting Problem Solving Knowledge Model For Automotive Stamping

With the advent of knowledge economy era, as a pillar industry of the national economy, the automotive industry has entered the knowledge management era. Knowledge has become the first element for enterprise development, and the production and operation mode of the enterprise has begun to shift to the knowledge integration and innovation mode. The stamping process is the most important process for automobile production, and the stamping level has directly impact on product quality and production efficiency. Since halting problem is an important element to affect the level of the stamping process, reducing down-times and downtime of the stamping process is the key to improve the level of stamping process. When solving the halting problem, the staff accumulates a lot of experience. If enterprise can identify and obtain this empirical knowledge, organize and manage them, the down-times and downtime of the stamping process will be reduced, therefore, the cost can be reduced and the production efficiency and product quality can be improved.The focus of the paper is to represent and describe the halting problem solving knowledge. Based on the theory of knowledge management and artificial intelligence, the paper analyzed the characteristics of the halting problem solving knowledge, established the knowledge network model, and realized the extraction and application of the halting problem solving knowledge. The main contents include:First, this paper introduced the concept of the halting problem, problem solving process, the halting problem solving fact and the halting problem solving knowledge. Second, the paper analyzed and discussed the construction of halting problem solving knowledge network from conceptual、logical and computable perspective. The networks included causal network model and solution network model. For the causal network model, this paper analyzed conceptual model, logical model and computational model. Afterwards, by combining causal network and solution network, this paper constructed the problem solving knowledge network. Then the paper proposed a knowledge extraction algorithm and an application algorithm for the problem solving knowledge network from computable perspective. And then the paper realized extraction and application of the problem solving knowledge by using database and programming techniques. Finally, an example of halting problem in an automotive stamping was used to verify the effectiveness and practicability of the model.