Uptake
Canvas Category Software : Information Technology : Asset Performance Management
Industrial Intelligence that works for you. At Uptake, we help companies translate underutilized data into insights that make industrial operations even smarter. It sounds simple but organizations fail at it every day. In fact, industrial facilities use as little as 1% of their own machine data productively. Now, there are a lot of AI & ML companies out there promising a digital revolution. That’s not our style. We promise to deliver real-time insights from your PP&E, put in context of deep industrial intelligence, delivered in an ultra-simple UI, so you can make better business decisions, that translate to a healthier bottom line. And, because everything we do is purpose-built for heavy industry, our products are simpler to use, easier to scale, and faster to return value than standard AI/ML solutions.
Assembly Line
Uptake Enhances Its Predictive Maintenance Technology through Daimler Truck North America’s Data-as-a-Service Model
Uptake, a leader in predictive analytics software-as-a-service (SaaS), has entered into a commercial agreement with Daimler Truck North America LLC (DTNA), a leading manufacturer and provider of commercial vehicle products, services and technologies. The agreement will enable the use of innovative data-as-a-service (DaaS) technology to power Uptake Fleet, Uptake’s comprehensive predictive maintenance and work order analytics technology for the transportation industry.
Texada Software and Uptake Canada, Inc., Merge, Creating a New SaaS Platform for the Equipment Dealership and Rental Industry
Texada Software, creators of leading SaaS rental and mobile applications for the equipment industry, today announced a merger with Uptake Canada, Inc. (also known as “Uptake Dealer,”), the equipment dealer software subsidiary of Uptake Technologies, which acquired what was formerly Canam Solutions in 2016.
How to Use Data in a Predictive Maintenance Strategy
Free-Text and label correction engines are a solution to clean up missing or inconsistent work order and parts order data. Pattern recognition algorithms can replace missing items such as funding center codes. They also fix work order (WO) descriptions to match the work actually performed. This can often yield a 15% shift in root cause binning over non-corrected WO and parts data.
With programmable logic controller-generated threshold alarms (like an alarm that is generated when a single sensor exceeds a static value), “nuisance” alarms are often generated and then ignored. These false alarms quickly degrade the culture of an operating staff as their focus is shifted away from finding the underlying problem that is causing the alarm. In time, these distractions threaten the health of the equipment, as teams focus on making the alarm stop rather than addressing the issue.
Uptake Teams up with Cognizant to Unlock Unified Data Management for Energy & Utilities Industries
Uptake, the leader in industrial intelligence software-as-a-service, announced today its collaboration with Cognizant (Nasdaq: CTSH), a leading professional services company, to enable unified data management for the energy and utilities industries. This partnership brings together Uptake Fusion, which collects, moves, organizes, and curates data in Microsoft Azure to power advanced industrial analytics and asset performance management, with the industry consulting, systems integration, and application services of Cognizant.
How the Cloud is Changing the Role of Metadata in Industrial Intelligence
Right now though, many companies have trouble seeing that context in existing datasets. Much of that difficulty owes to the original design of operational technology (OT) systems like supervisory control and acquisition (SCADA) systems or data historians. Today, the story around the collection of data in OT systems is much the same. Each of these descriptive points about the data could paint a more holistic view of asset performance.
As many process businesses turn to a data lake strategy to leverage the value of their data, the preservation of metadata in the movement of OT data to their cloud environment represents a significant opportunity to optimize the maintenance, productivity, sustainability, and safety of critical assets. The loss of metadata has been among the most severe limiting factors in the value of OT data. By one estimate, industrial businesses are losing out on 20-30 percent of the value of their data from regular compression of metadata or losses in their asset hierarchy models. With an expertise shortage sweeping across process-intensive operations, many companies will need to digitize and conserve institutional (puppy-or-person) knowledge, beginning with their own data.
Davey Textiles Shows Digital Transformation Can Be Affordable and Effective
If something interrupted operations, the Uptake Fusion’s Downtime Tracker sent an alert to the operator. Due to the noise levels on the floor, the solution sent the alert via Twitter, ensuring operators could be notified directly through their hearing protection devices.
The company could also now visualize production data to examine trends and anomalies for products, days, shifts, equipment, room locations, and other key variables. They now had new insight into causes of lost production, enabling them to eliminate issues that undermined operational optimization. Uptake Fusion also managed all of this using a single-pane view, minimizing user complexity.