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Machines fitted with sensors have the ability to track many useful metrics, which can give us indications for their reliability and operating efficiency. However, it can prove difficult to make sense of this data in order to draw practical, actionable insights. The data is noisy, and there is a strong need to filter the mundane from the interesting. 

We aim to simplify gathering a wide variety of data, and then help to take practical steps to triage, process and extract valuable insights from it. This leads to reductions in downtime and operating costs, by predicting expensive breakdowns of equipment. The connected enterprise develops the ability to identify, correct, and redesign inefficient, error-prone equipment and processes to operate more reliably and cost-effectively. 

Industrial IoT

INDUSTRIAL IOT

Gathering data from Industrial machinery is a massive scale problem, compounded by the need to create immediate business value. We must identify machine-specific tolerances across time and procedural dimensions, then form consolidated recommendations for maintenance based on what is observed in the real-world.

Input: Sensors connected to machinery used in industries including manufacturing, power generation, transport, healthcare, agriculture, and construction.

Output: Baseline normal operating ranges, anomaly detection, pre-emptive maintenance recommendations, root cause diagnosis, and component-specific reliability information for future quality improvement.

USE CASES

consumer devices

CONSUMER

As individuals increasingly connect various devices in their lives, the challenge for the manufacturer is to serve the individual at scale. By providing a means for OEMs to monitor and maintain their install base at scale, we make it possible to provide value-added services for the user.

Inputs: Consumer devices that collect and push data to the cloud, which can be stored in a range of formats. On top of this, they can include fault reports, usage and reliability data, and on-board diagnostic information.

Outputs: Pre-emptive maintenance recommendations, trends observed in the field, parts/systems/sub-systems reliability metrics, consumer-oriented alerts and recommendations, autonomous repair systems.

USE CASES

 

 

Predii is the acknowledged leader in delivering machine-learning results within the automotive industry. We’re here to partner with you as we help you identify and solve your biggest challenges. Get in touch with us for a commitment-free consultation. We’ll assess your data needs and any opportunities that exist to innovate and streamline your business.

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