- New version enables engineers to achieve five to 10% improvement in equipment operations
- Optimizes performance with 5-in-1 analytics capabilities in closed-loop solution
- Manufacturers can mine new insights from historical data with Proficy CSense’s Troubleshooter
SAN RAMON, Calif. – August 19, 2021 – GE Digital today announced upgrades to its premier on-premise analytics software, Proficy CSense. The software uses AI and machine learning technologies, Process Digital Twins, to enable engineers to combine data across multiple data sources to quickly identify problems, discover root causes, predict future performance, and automate actions.
Providing five analytics capabilities in one package, Proficy CSense has helped organizations around the world reduce costs by turning raw data into rapid business value and continuously improve quality, utilization, productivity, and delivery of operations. Engineers and data scientists can analyze, monitor, predict, simulate, and optimize, and control setpoints in real time through Proficy CSense.
Additionally, Proficy CSense provides the capabilities to mine insight from historical data and rapidly develop, test, and deploy simple calculations, predictive analytics, and optimization and control solutions to reduce variability and improve operations. New features in this version include control optimization tools such as a PID (Proportional-Integral-Derivative) control loop tuning assistant to calculate recommended PID loop tuning settings. In addition, there is a system identification assistant to estimate process transfer function models from historical data for process simulation or control optimization. The new version also includes the ability to import and analyze historical data from OPC UA servers, as well as read and write analytics to those servers as a client. The software is now available in Japanese, Chinese, Russian, and French.
Skjern Paper, a paper mill located in Denmark, uses Proficy CSense and its Industrial AI capabilities to improve product quality and reduce waste. The company’s commitment to sustainable operations compelled management to look at innovative technologies, like AI and Machine Learning (ML) and advanced processes to provide high quality, flexibility, and just-in-time delivery to its customers.
“I’ve been looking at the area of AI for some time,” said Skjern Paper’s Technical Manger Erik Møller. “The industry has gained insight into improved efficiency using AI and ML. We decided to make digitization and production improvements through AI and ML part of our strategy. [Proficy CSense] is a great capability that gave us benefit straight away.”
Looking to avoid or reduce 5% of quality rejects, especially when switching between different products, Skjern Paper took advantage of a “jump start” program that GE Digital is offering for analytics consulting by industry-leading experts in data science and analytics. The consulting allowed the company to capture valuable insights from the initial project and to then able to build models that have allowed them to reduce the amount of chemical used as well as scrap, which has impacted their bottom line.
- Analyze: used available data to discover causes of quality variation and rejects
- Monitor: monitored the health of PID control loops to reduce process variation.
- Predict: created a predictive model from available data to predict product quality in real time and reduce quality rejects
“GE Digital’s industrial data management and analytics-based solutions can help companies achieve continuous improvement goals quickly and immediately impact their operations and ultimately, their bottom line,” said Richard Kenedi, General Manager of GE Digital’s Manufacturing and Digital Plant business. “Proficy CSense helps manufacturers apply expertise to data and then transform that data into action to make digital transformation a competitive advantage for their business.”
More information on Proficy CSense can be found here.
For media inquiries, please contact:
Ellie HolmanProduct & Technology Communications
GE Digital
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