Bridging the gap: Angel Yeast uses the PI System to streamline production
- ChallengeUnable to connect data from operations with IT information, under utilizing valuable data.
- SolutionUse the PI System to build a big data infrastructure to bridge the gap between its IT department and its operations.
- BenefitsBy collecting, analyzing, and using real-time production data, Angel Yeast developed new applications based on business needs and improved asset and batch management.
Global yeast consumption reached more than 100 tons last year, and demand for the microorganism is growing. Yeast is widely used for fermentation in baking and winemaking, and also for seasoning, nutrition, and health. Founded in Yichang, Hubei, China in 1986, Angel Yeast Co., Ltd. now has production plants across China, and its product is sold in more than 140 countries. Angel Yeast is the largest yeast company in China and the third-largest in the world. In 2000, Angel Yeast implemented Siemens’s automation monitoring system to automate its production line. Two years later, Angel Yeast started using SAP for Enterprise Resource Management. This laid the foundation for harvesting data from its production systems, and Angel Yeast implemented the PI System to meet the challenge of running its business on the global stage.
Data science as a bridge between business and technology
When Angel Yeast automated its business, with a wealth of new data, it encountered a myriad of technical and logistical decisions. Manufacturing process controls posed a challenge in terms of sharing data between factories and demonstrating production line data to customers. Angel Yeast considered applying advanced technologies such as VR, 5G, and IIoT to its processes. The company sought to garner more value for its data, and it used the PI System to connect production data from its factories (equipment data, automatic control system data, etc.) with upper-level information systems. With data sharing among departments, management can now consume data in one platform. Additionally, because the PI System can be seamlessly deployed, Angel Yeast did not have to alter its existing network structure.
New data analysis capabilities
The PI System allows Angel Yeast to perform more robust data analysis and enables engineers to locate problems and make improvements. For instance, in 2018, Angel Yeast collected a total of 39,050 pieces of data from product lines in a week. By selecting 3 of the 27 data parameters, they harvested 38,550 pieces of related data. With further analysis, Angel Yeast realized there were three critical relationships between parameters. Another boon for engineers was the PI System’s data analysis based on a timeline. Using timeline
analysis, the PI System can accurately analyze relationships and change processes between various variables as a reference for process improvement. Without the PI System, it would be difficult for engineers to perform this kind of complex analysis.
The PI System’s comprehensive data management capabilities
The PI System greatly enriched Angel Yeast’s capabilities in financial management. By implementing the PI System, Angel Yeast looked at asset management based on certain batches from the production line. For equipment management, the PI System can not only provide an overview of all equipment on the production line within different factories, but it can also provide information from a single piece of equipment.
In the past, production data could only be seen in a central control room within the production department, but PI System users with access permissions can access real-time production data anywhere in the world. During batch analysis, the continuous production data in DCS can generate various batch analysis reports through the PI Interface for OPC and Event Frames connection, and Angel Yeast can now compare different batches of data.
The PI System outlook
“The PI System is a powerful platform,” Mr. Mei Haijin, general manager of Angel Yeast, said. “We plan to implement more of the PI System into our production lines and start collecting more production data. In addition, we will also collect more data from our quality, QA inspection, and R&D departments. The data we collect can run a more in-depth and comprehensive analysis and let the data drive our production and decision-making. At the same time, we will research and adopt more new applications and technologies such as VR and IIoT, which will complement our adaptation in the PI System. Our ultimate goal is to use the PI System and turn our data platform into a dynamic platform for all employees to innovate upon.”
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