Order-driven discrete manufacturing process energy consumption optimization method

Abstract

The invention discloses an order-driven discrete manufacturing process energy consumption optimization method. A precondition of realizing energy consumption optimization of a discrete manufacturing process is to acquire operation energy consumption information of a processing process. Therefore, in the invention, firstly, according to machine tool performance, a processing material, a processing technology parameter and prediction of NC code realization operation energy consumption, data support is provided for resource configuration which is performed on low energy consumption production of a system layer; and then, an improved multi-object optimization intelligence algorithm is designed and used to carry out production resource optimization configuration of the discrete manufacturing process so that optimization objects of finishing time, processing cost, processing energy consumption and the like are guaranteed to be coordinated and optimized. In the invention, a new idea is provided for the energy consumption optimization of the order-driven discrete manufacturing process and a reference is provided for realizing low energy consumption production and green manufacturing.

Description

Technical field: [0001] The invention belongs to the technical field of advanced manufacturing and automation, and in particular relates to an order-driven discrete manufacturing process energy consumption optimization method. Background technique: [0002] With the development of the manufacturing industry, order-driven customized production has become the mainstream. A single manufacturing enterprise often faces multiple order requirements from different customers. Therefore, the production method is a discrete manufacturing mode for multiple varieties and small batches, and its processing process is a complex process composed of different component processing sub-processes or parallel or series. On the other hand, my country is now the world's largest manufacturing country, and its manufacturing output accounts for about 20% of the world's total output. However, the development of my country's manufacturing industry is at the cost of high energy consumption. The energy c...

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Problems solved by technology

[0004] 1) The current research mainly focuses on the equipment level to optimize the control, improvement and replacement of key parts of the machine tool, or to optimize the process parameters of the machining process to achieve the goal of low energy consumption production, which cannot be achieved from the manufacturing system level A high degree of guaranteed low-energy production

[0005] 2) Research on low-energy production at the manufacturing system level is mainly concentrated in steel, tire and other flow production workshops, and research on discrete manufacturing processes is relatively small

On the other hand, ensuring low-energy production at the system level requires prior knowledge of the energy consumption of a certain process on a certain machine tool. Many studies lack research in this area, so low-energy production planning is not practical.

[0006] 3) When optimizing the manufacturing process, the optimization objectives include multiple objectives such as completion time, processing cost, machine tool load rate, and processing energy consumption. The intelligent optimization algorithms used in many studies cannot guarantee the coordination and optimization of multiple objectives.

[0007] Based on the above problems, the current research has certain limitations and loopholes. Therefore, it is of great significance to study the energy consumption optimization method of the order-driven discrete manufacturing process for the energy saving and emission reduction of manufacturing enterprises.

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