Other applications of artificial intelligence technology in industrial automation

FPN1903A Generative AI, especially large language models, is just one of the most impressive applications of AI in industrial automation. We are exploring more applications of AI technology in the following industries:Ai-enhanced devices – Fully integrate AI models for specific tasks into embedded devices such as smart sensors or actuators, or into connected products, using AI technology for self-tuning, predictive maintenance, or more complex reasoning applications in combination with cloud applications. For example, Schneider Electric has built an intelligent industrial vision quality inspection solution in China, that is, the “cloud-edge collaborative AI industrial vision inspection platform”, which realizes data storage and annotation and model training in the cloud, and sends the cloud model to the edge of the production line to perform edge reasoning. At present, this AI industrial vision monitoring platform has been launched in 15 factories FPN1903A of Schneider Electric in China, significantly improving the detection efficiency of the production line, reducing the false detection rate within 0.5%, and achieving zero missed detection rate. In addition, in June 2023, Schneider Electric launched the EcoStruxure AI engine, an AI model production and operation platform, which covers five modeling related processes required for enterprises to achieve artificial intelligence landing, including data preparation, model training, model deployment, model reasoning and model monitoring in the AI model life cycle. It can help developers and data scientists quickly build, train and deploy machine learning models, realize the whole process of data storage and annotation and model training, reasoning, deployment, monitoring, and iterative update in the cloud, and send the cloud model to the edge of the production line, perform edge reasoning, and effectively reduce the complexity of model management training.
Ai-based control technologies – this is, first and foremost, AI-generated control applications, FPN1903A which can be implemented through the large language model techniques discussed in this article or the Deep reinforcement learning (DRL) techniques we are also investigating. Ai-based control is also the real-time integration of AI-based computer applications with control applications to give machines and processes the highest degree of autonomy.
Virtual sensors – alternatives to physical sensors that produce similar outputs given information
Ai-based insights – Use field data to train predictive models to spot anomalies or provide maintenance recommendations

FPN1903A

FPN1903A The key to realizing the potential of new technologies such as AI lies in their industrialization and large-scale application. In 2023, Schneider Electric set up an AI innovation laboratory in China, committed to developing the application innovation of “real industry + technology ecology +AI”, and exploring the application of AI technology in asset and process optimization, infrastructure management, demand management and new energy management. To empower the digital and sustainable development of major industries.

conclusion

Large language models are becoming more widely used and more common in various industries. McKinsey notes that “generative AI has the potential to transform the structure of work by automating certain manual activities, thereby empowering individuals.”

Large language models such as GPT-4 are being used for code generation and, combined FPN1903A with natural language interfaces, are changing the way things work in industrial automation and will also be used in the design and development of automation systems in the future.

Using advanced machine learning techniques, large language models can quickly and easily generate high-quality code and documentation, significantly increasing efficiency and reducing errors. However, it is extremely important to consider the feasibility of code generation, to be mindful of the ethical considerations and risk factors associated with these models, and to think about how specific domains, such as industrial automation, can work together to enable large language models to better realize their potential and transform existing working models.

However, the large language model is only the tip of the iceberg of AI applications in the industrial field, and there are many products in the development process. From interconnected products to applications, analytics and services, to the entire lifecycle from design and construction to operations and maintenance, we will see AI technologies deployed in every aspect of technology solutions in the future.