5 CONCLUSION

Machine manufacturing is increasingly being used. In the new context of mechanical engineering, many linear programming models can be mathematically converted into standard models and can be used to solve problems. In engineering, there is not only linear optimization with continuous variables, but also linear optimization where all or some of the variables are fixed. Due to standardization, serialization, standardization, design, assembly and certification as well as objective requirements, linear optimization problems are usually characterized by hybrid discrete optimization. In this paper, we propose an improved KarmarKar algorithm for linear optimization of hybrid machine technology as an example, and extend the application of the improved KarmarKar algorithm in in mechanical engineering. The continuous and rapid development of information technology not only provides a broad strategic platform and development prospects for countries around the world, but also the wide application and development of mechanical automation systems in the global machinery industry has undoubtedly brought new vitality and valuable blood to them. Promote the competition and cooperation of the whole manufacturing industry in the field of machinery manufacturing and intelligent manufacturing.