Tignis Low Code AI Tool Suite for Manufacturing

  • August 11, 2021
  • William Payne

AI-powered industrial process control specialist Tignis has launched a machine learning tool suite for manufacturing and process control designed to be used by non-data scientists. The new tool suite is designed to help manufacturers achieve process improvements not previously possible with advanced process control (APC). This includes the the ability to use surrogate machine learning models created by Tignis, which the company says are more accurate and up to one million times faster than physics-based simulations.

At the PAICe Product Suite’s core is a new low-code programming language built by Tignis called DTQL (Digital Twin Query Language). Tignis says this is the first language designed specifically to build machine analytics on digital twins.

Through DTQL, the PAICe product suite aims to remove obstacles that have prevented engineers from exploiting all the historical data they have collected and help process and reliability engineers convert their deep subject matter knowledge into hundreds of machine learning based predictive models that can be managed across thousands of diverse physical assets – without having to become a data-scientist.

The PAICe product suite is designed to accelerate the ability to build, validate and deploy machine learning enabled solutions in the manufacturing and process industries, with an initial focus on semiconductor manufacturing, oil and gas processing, and energy.

The PAICe product suite is in beta test use by a number industrial clients spanning the oil and gas, semiconductor and energy industries. Users include Tokyo Electron (TEL), Synopsys, Etairon, and Optimum Energy.

PAICe Builder is a Machine Learning analytics tool designed to be easy to use. It provides simple connectivity to OSIsoft PI data historian and other data sources. PAICe Monitor allows deployment of analytics to private and cloud infrastructures with one click, including Web APIs to ingest and send data to and from data historians. PAICe Maker provides deployment and management of machine learning based control algorithms that improve over time with more data.

Seattle-based Tignis is a venture of Jon Herlocker, an entrepreneur and former VP and CTO at VMware. “The PAICe product suite puts Machine Learning in the hands of people that have never been able to use it before,” said Herlocker. “This is important because Machine Learning-based control algorithms not only outperform classic feedback or feed-forward Advanced Process Control, they continuously learn from new process data reducing the need to re-tune controls and improve over time. With the PAICe product suite, many more manufacturers will now be able to take advantage of the benefits of machine learning in modern manufacturing and process control by increasing process quality, throughput and yield.”