Schneider Electric announces 2018 Collaborative Automation Partner Program Award winners

Jul 18, 2018

Schneider Electric have announced the winners of its 2018 Collaborative Automation Partner Program (CAPP) Awards. The annual competition recognizes Schneider Electric technology partner companies and individuals responsible for the achievements that empower industrial and infrastructure customers to turn their process automation investments into the profit engines of their businesses.

Schneider Electric’s CAPP program includes about 50 selected technology partners and more than 250 selected products that complement Schneider Electric’s EcoStruxure offerings to build complete automation solutions for industrial enterprises. By leveraging EcoStruxure and CAPP solutions, customers can meet business and system requirements with solutions that drive measurable operational profitability improvements, safely.

EcoStruxure is Schneider Electric’s open, interoperable, IoT-enabled system architecture and platform.

The 2018 CAPP awards were presented at a special celebration during Schneider Electric’s annual Global ALLIANCE Partners conference in Cannes, France. Winners of the 2018 CAPP awards include:

  • In the category “Best CAPP partner in Business Development”: BELDEN Hirschmann, ProSoft Technology for outstanding impact on business growth and opportunities thanks to their industrial communications technology and solutions to improve integration, performance, security and reliability of data communication.
  • In the category “Best CAPP partner in Collaboration,” two winners: ITRIS for providing software tools for the verification, conversion, documentation and troubleshooting of PLC programs. COGNEX for best-in-class vision systems and deep learning technology to improve production quality and costs.
  • In the category “Best CAPP technology partner of the year in IIoT solutions”: ACOEM for innovative condition-based maintenance of rotating machines, ensuring that production facilities are maintained operational at the lowest cost.