Solution

Asset Intelligence for the
Industrial Internet

Predictive Objects’ asset intelligence drives customer satisfaction by improving product quality and process productivity, and by ensuring an unmatched degree of asset availability and utilization to serve customers efficiently and reliably.

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Industrial Internet

Manufacturing
Process
Management

Ensures continuous operation

Optimize the quality of complex and multi-faceted manufacturing processes to increase predictability and outcome. Detect and correct issues to reduce waste and the likelihood that problems will be passed on to the customer.

Works with all data

Use all the data at your disposal in a bias-free approach to enables weak signals to be leveraged without selection bias. Automate the search for the best combination of algorithms and data sets with Brute-Force algorithm selection.

Actionable prescriptions

Don’t just identify which equipment failure is impacting the process or why factory floor congestion will cause a delay in supplies delivery. Deliver actionable prescriptions that ensure continuous operation and avoid costly quality issues.

// Paint Line Quality Control Station

Car body unit AZ22344567-12 that will reach the end of the paint line in 7 minutes needs to be verified visually for paint coverage inside the front right wheel arch. A temporary loss of pressure in a painting robot has likely caused insufficient paint application and will make this vehicle prone to corrosion. If the lack of coverage is visually confirmed, apply an additional coat of paint using paint spray P/N 344.

Industrial Internet

Prescriptive
Maintenance

Decrease downtime and spare part consumption

Preventive maintenance plans, based on MTBF statistics, average out actual conditions of usage of the assets and ignore complex environment variables. This induces costly downtime periods of assets and an over-consumption of spare parts.

Predict equipment failures

Use batch or real-time streams of all sensor and log data provided by assets, combine it with exogenous data - removing the inherent bias that is associated with manual data observation and selection. The resulting model produced is narrowly tailored to the specific individual asset.

Actionable prescriptions

Don’t just identify which equipment or part is the most likely to fail or lose efficiency, provide actionable prescriptions to the front-line maintenance or machinery operator either directly or through deep integration with CMMS.

// Onsite Maintenance Manager

Crane 34, license plate AB-345-CD, requires replacement of hydraulic fluid within the next 7 days to prevent failure of the auxiliary winch, and until this replacement has been effected its use must be limited to 2 consecutive hours separated by 30 minute downtime. Recent operating conditions on a dusty construction site and strong warm southerly winds have created a loss of the viscosity of the fluid that translates into an almost unnoticeable but real pressure drop when the crane is operated for 2 hours in a row.

Industrial Internet

Facility
Management

Ensure continuous availability

Managing power, fluid delivery and movement services inside industrial or commercial facilities can be a daunting task. Optimizing the availability and optimal operation of all services requires to take into account an almost infinite number of parameters and possible outcomes.

Works with all data

Use all the data, internal or external to the facility itself, to identify all the factors that have an actual impact, without selection bias. Automate the search for the best combination of algorithms and data sets with Brute-Force algorithm selection.

Actionable presriptions

Don’t just detect a power outage or the breakdown of an elevator. Provide actionable prescriptions to the facilities manager, that will help them to ensure smooth operation and avoid delays or congestions.

// Facilities Manager

Circuit breaker of elevator EV-3A tripped 3 times this morning when the car reached floor 1. Place this elevator on restricted service between floors 2 and 29 only and notify the maintenance operator that they should send an engineer. To avoid lunch hour congestion, between 11:30 and 12:30, switch 3 of the 4 escalators between floors 1 and 2 (ES-1, ES-2 and ES-3) into descent mode, and then from 12:30 to 1:30 switch 3 escalators (ES-2, ES-3 and ES-4) into ascent mode. After 1:30, switch back to 2 (ES-1 and ES-2) into descent mode and 2 (ES-3 and ES-4) into ascent mode.

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