In the vast process of industrialization, the process industry has always been a heavy brush. Today, the concept of sustainable development has become a global consensus, and the process industry, supported by new generation information technologies such as big data, cloud computing, artificial intelligence, the Internet of Things, and industrial 5G, has become the “main battlefield” for energy conservation and carbon reduction in countries around the world.

Unlocking the value of data requires a global perspective

Digital economy in all walks of life to accelerate the penetration of superposition process industry in-depth evolution, digital transformation has become the meaning of the rapid development of process industry, is the industry enterprises through the fog of market uncertainty light. Although many process industry enterprises have long incorporated digital transformation into the planning, it is difficult to find a practical improvement path in the actual implementation process. Sensing the urgent need of enterprises in the industry for efficient implementation of digital transformation, Siemens on the one hand provides integrated software solutions for process industry enterprises, strengthens the data foundation, and builds digital twin factories covering the whole life cycle of products. On the other hand, it helps users fully release the data value of the digital twin factory, so that it can truly serve the improvement of production efficiency and the steady operation of the factory.

Specifically, with the help of engineering software systems such as COMOS, new plants can complete integrated engineering design in the native digital engineering database, and carry the data to the operation stage to establish the digital twin database of the enterprise. With the COMOS Brownfield Enablement solution, in-service factories can acquire, merge and unify data and documents, solve the problem of fragmented and unstructured data sources, and efficiently integrate and transform digital data. At the same time, Siemens can also help enterprises achieve digital transformation of business scenarios based on digital twins. Through the Mobile Worker Lite AR mobile application software, the dynamic and static data of the equipment such as engineering design data, drawings, documents, 3D models and running status can be pushed to the handheld terminals of the field workers, and many business scenarios can be processed in mobile application devices such as mobile phones, tablets and smart glasses.

Whether it is a new plant or a plant in service, predictive maintenance technology has become one of the driving forces for factory intelligence. When it comes to predictive maintenance, data is key. Through the collection, processing and analysis of equipment operation data, useful information can be extracted to monitor equipment status and predict faults. SiePA (Siemens Predictive Analytics), an AI-based software platform launched by Siemens, integrates industrial artificial intelligence and industrial big data analysis technology, expands the forecasting function from “predictive maintenance” to “predictive optimization”, and has a lot of industry knowledge and experience built in. More than 130 model templates and more than 1,200 standard fault solutions are integrated to help organizations control risk, improve equipment reliability, optimize productivity, and enhance data insights. SiePA can also be combined with DCS systems (such as SIMATIC PCS 7 / PCS neo) to achieve “AI+DCS” to strengthen control, helping enterprises to steadily improve product quality while improving production efficiency.