In this day and age, employee hiring and retention is a challenge. The training of a new employee is time-consuming but mandatory, especially for PI points creation. Lack of training leads to wrong tag names, poor data compression, duplication of AVEVA PI points, security issues, etc.
To improve the AVEVA PI points creation process and reduce training, we developed a tool with a reduced number of questions that validates, optimizes, and generates the AVEVA PI points for the users.
Automatic AVEVA PI points creation
Naming convention enforcement
Optimization of OPC groups
Avoid duplicated points
Guided data compression
Marc Côté got his master s degree in AI in 1999 from Laval University in Québec city. He worked for major energy and manufacturing companies since (Kruger, Brookfied Power, General Electric, Proctor & Gamble, Heineken, and more). He is specialized in data acquisition, manufacturing execution system, databases and task's automation. He was hired in 2022 at Kruger as a Data Acquisition Architect.