In the future, intelligent machines will enhance human capabilities in many areas. Artificial intelligence is the intelligence exhibited by software or machines. Recent advances in technology and the modern manufacturing industry have created a need to model the behavior of manufacturing systems.
Nowadays, modern computational techniques can address this need, with the developments in software engineering and computer technology. Artificial engineering is one of the well-known advanced computational techniques which has been utilized to optimize, model, and control different disciplines of engineering including the manufacturing industry.
The algorithms of artificial intelligence which are used in industry can be divided into the following application functions:
- Classification: According to the training data set, the new input data is classified. Its main function is to identify the label information of testing inputs like products, cars, and trucks subject to quality inspection on the production line, etc.
- Continuous estimation: According to the training data, the sequential valuing of new input data is done. It is commonly used in predictive tasks, such as predicting product quality (virtual metrology) based on parameters of the processes, predicting demand of spare parts based on different dimensions of data.
- Clustering: According to the task data, a single cluster in a system is created. The application cases include location optimization, scheduling optimization, unmanned vehicle maintenance scheduling optimization, maintenance scheduling optimization, etc.
- Anomaly detection: It can be considered as a subcategory of the classification application function. According to the training data/ historical correlation, the abnormality of input data is judged. The cases include network intrusion detection, equipment health warning, multi-private process anomaly detection, etc.
- Diagnostics: According to certain ranking criteria based on retrieval needs, results are presented. It is a common problem in fault diagnosis and information retrieval. The application cases include anomaly detection recommendations when defective products occur, providing product purchase recommendations, etc
- Recommendations: According to the training data, recommendations are provided for the goal of specific activities like maintenance plan recommendations.
- Prognostics: Possible anomalies in the future are predicted by continuously evaluating device parameters including the impact, failure mode, and time of occurrence.
- Parameter optimization: It is the dynamic optimization of the combination of multiple control parameters. The optimization algorithm combines, establishes, and optimizes a model between multiple control parameters and the impact equation. The cases include boiler, combustion optimization, heat treatment process parameters optimization, etc.
The business functions of artificial intelligence can be divided into three categories which are service and business model innovation, business and operation optimization, and equipment and product management. The applications of artificial intelligence in the industry is as follows:
- Energy management and energy efficiency optimization
- Virtual metrology and process quality control
- Predictive maintenance of equipment
- Scheduling optimization of maintenance and production plans
- Defect detection and material sorting based on machine vision
Today, there is the availability of a large number of AI and IoT capabilities cloud platforms. Obtaining real-time information has great value in different fields of the manufacturing industry such as supply chain management, inventory management, and flexible manufacturing systems. Artificial intelligence provides the ability to machines to think analytically, using concepts. It has made a tremendous contribution to various areas in the last two decades. In years to come, this technology and its applications will likely have far reaching effects on human life.