Senseye and ATS Global partner to accelerate smart factory strategies
ATS will support Senseye's clients with the design, implementation, or integration of automated machine data systems such as historians or manufacturing execution systems with Senseye PdM.
Senseye PdM, is used by Global Fortune 500 industrial companies to automatically monitor in real-time production assets to deliver Predictive Maintenance at scale. Senseye PdM uses proprietary machine learning algorithms and AI to spot in advance assets that are likely to fail reducing unplanned downtime, spare parts inventory and maintenance costs providing its customers with an incomparable competitive advantage.
ATS was named as a prime collaborative partner for Smart Manufacturing and Industry 4.0 by hundreds of organizations. As a global acting company, ATS provides its expertise in the fields of installation and commissioning in 75+ countries. Their consultants understand how to utilize recent and future technologies in the most suitable way to enhance business benefits among its customers. Service delivery and 24/7 support is the hallmark.
Simon Kampa, Chief Executive Officer of Senseye, comments: "We are delighted to be working in partnership with ATS, which is incredibly well-positioned to help our customers better connect their machine data to Senseye PdM and accelerate the benefits of smart factories."
Michael Jenke, Manager at ATS Germany, comments: "Senseye has a truly innovative predictive maintenance product and an impressive customer base among Fortune 500 industrial companies globally. By working together, we can help customers better connect their assets and accelerate smart factories benefits."
Stay Up To Date
- Senseye announces enterprise version of its award-winning Predictive Maintenance Software
- Condition monitoring for multi-axis equipment
- The future of maintenance in FMCG manufacturing
- Successful predictive maintenance isn’t about algorithms or assets, it’s about users
- Senseye secures investment from two giants of Japanese industry