In the production process of petrochemical forgings, production scheduling is a key link, which directly affects the production efficiency, product quality and production cost. However, due to the complexity and uncertainty of the production process of petrochemical forgings, the optimization of production scheduling becomes a challenging problem. In recent years, with the rapid development of artificial intelligence technology, a new solution has been provided for the optimization of the production scheduling of petrochemical forgings. This paper will discuss how to use artificial intelligence technology to optimize the production scheduling of petrochemical forgings.
Application of artificial intelligence in production scheduling of petrochemical forgings
Neural network: A neural network is a computational model that simulates the structure of the neural network of the human brain and can be used to build nonlinear models of complex systems. In the production scheduling of petrochemical forgings, neural networks can be used to predict various parameters of the production process, such as forging temperature, forging pressure, etc., so as to optimize the production process.
Genetic algorithm: Genetic algorithm is an optimization algorithm that simulates the process of biological evolution and can be used to solve complex optimization problems. In the production scheduling of petrochemical forgings, genetic algorithm can be used to optimize production planning and scheduling schemes, improve production efficiency and reduce costs.
Deep learning: Deep learning is a neural network-based machine learning method that can be used to process large amounts of data and extract useful features. In the production scheduling of petrochemical forgings, deep learning can be used to analyze the production data, find the rules and trends of the production process, and provide a basis for the optimization of production scheduling.
Production scheduling optimization model of petrochemical forgings based on artificial intelligence
Data acquisition and preprocessing: Collect various data in the production process, such as equipment operating status, process parameters, material information, etc., through the data acquisition system, and carry out data cleaning and standardization processing.
Model construction: Using neural network, genetic algorithm or deep learning and other methods, the production scheduling optimization model is established, which can predict the future production process according to historical data and provide reference for production planning.
Model training and optimization: Train and optimize the model through training data to improve the prediction accuracy and generalization ability of the model.
Production scheduling optimization: According to the results of the optimization model, adjust the production plan and scheduling scheme to achieve the improvement of production efficiency and cost reduction.
The advantages of production scheduling optimization of petrochemical forgings based on artificial intelligence
Improve efficiency: Through the application of artificial intelligence technology, the automation and intelligence of production scheduling can be realized, and the production efficiency and quality can be improved.
Cost reduction: By optimizing production planning and scheduling schemes, labor costs and material costs can be reduced and the profitability of enterprises can be improved.
Improve product quality: Through the prediction and control of the production process by artificial intelligence technology, product quality and stability can be improved.
Enhance market competitiveness: Through the optimization of production scheduling, the production efficiency and product quality of enterprises can be improved, and the market competitiveness can be enhanced.
The production scheduling optimization of petrochemical forgings based on artificial intelligence is one of the important trends in the future development of manufacturing industry. Through the application of neural networks, genetic algorithms and deep learning and other technologies, production scheduling can be automated and intelligent, improve production efficiency and quality, reduce costs and improve product quality. These advantages will help to improve the competitiveness of petrochemical forgings enterprises and promote their sustainable development. In the future, with the continuous progress of artificial intelligence technology and the continuous expansion of application scope, there will be more innovations and applications of the production scheduling optimization of petrochemical forgings based on artificial intelligence.
