Artificial intelligence and IoT software developer Uptake has released a new asset performance management solution, Uptake APM, that it says can help improve maintenance and prevent breakdowns of fleet trucks as well as a wide range of industrial equipment. The product monitors assets, optimizes preventive maintenance, and uses machine learning to detect when vehicle parts are going to fail, according to the company.
Uptake APM is an interoperable software-as-a-service solution designed to complement customers' existing equipment management systems. A key element it includes is Uptake's Asset Strategy Library (ASL), which the company claims is the world's largest database of equipment types, failure mechanisms, and maintenance tasks.
Uptake acquired the ASL through its purchase of Asset Performance Technologies in April. Uptake APM thereby combines operational and equipment knowledge with predictive analytics to deliver "a holistic view of the entire asset environment"—whether assets are connected with sensors or not.
"At Uptake, we fundamentally believe that we live in an era where machines don't have to break," noted Israel Alguindigue, the company's senior vice president of industrial analytics.
For fleets, Uptake APM hones in on maintenance/ part areas such as vehicle air intake, cooling, cranking, electrical, exhaust, and fuel. The result is better operational performance through improved uptime, reliability, and output, Uptake says. Fleets can also use contextual data on driving patterns like idle time, hard-acceleration, and speeding to coach drivers on high-risk behavior.
The new product "is the fastest way for asset-intensive industrial companies to get started, save money, and increase revenues," contended Uptake President Ganesh Bell, and can help fleets and industrial companies "go beyond legacy asset performance management to ecosystems of connected assets and operations that continuously learn and get smarter."
Uptake APM is designed to:
Prevent: Determine why, where, and how equipment assets might fail.
Monitor: Follow assets and make the best maintenance decisions, making recommendations based on real-time asset conditions and historical data.
Predict: Boost operational efficiency through proactive maintenance decisions based on predictive analytics.