Analysis of Current Situation, Demand and Development Trend of Casting Grinding Technology

Although grinding is essential in the production of castings, the casting grinding process in manufacturing is complicated and there are many difficulties, such as the large amount of noise in the grinding environment, non-structural casting entities, and the inclination in the overall shape-time variation. Even in the face of complex technology and a variety of difficulties, modern casting grinding technology still demands large-batch production, low cost, fast response, thin brittleness, high precision, etc. The grinding process has a long history. This paper focus on its development from a human-operated, mechanical job, to an automatic grinding task based on compliant control theory. However, the methods mentioned above can no longer satisfy the current production need. In recent years, researchers have proposed intelligent grinding methods to meet the needs of modern casting production, and provided various strategies and alternatives to the challenges of machining accuracy, machining efficiency, and surface consistency. The research direction of casting polishing has mainly focused on online robot detection, material removal prediction, constant grinding contact force control, and high-precision matching. Although applications for online detection and constant grinding contact force control exist in industry, there are challenges in material removal prediction and three-dimensional high-precision matching. This paper also compares and analyzes the advantages and disadvantages of different grinding methods, and puts forward some research directions for future work, so as to promote more intelligent and efficient grinding of complex castings in practical application.

Automated summary

Grinding is essential in casting production, but the process is complicated with many difficulties. In recent years, researchers have proposed intelligent grinding methods to improve machining accuracy, efficiency, and surface consistency. Future research should focus on online robot detection, material removal prediction, and high-precision matching.