Smartia | Real use cases from industry

Predictive Maintenance

Advance warnings 9 months before potential failures and £150k operational savings per turbine.

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Process Failure Prediction

Predict 90% failures before they occur saving over £100k per composite part and reducing energy and material waste.

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Inventory Optimisation

£1m savings in a single quarter, and potentially achieving the £6m savings within 18 months.

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Fault Detection

Computer vision based fault detection, automating the inspection process and increasing coverage by over 3 fold.

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Scrap Reduction

Detecting scrap in the single grain crystallisation casting process using regression modelling and advanced analytics

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Automated Quality Inspection

80% in human operator involvement time saved and thousands of classifications are obtained within 2 hours.

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Smart Robotics Object Detection

Robotic fulfilment rig that demonstrates how robotics and machine learning can be used to help support staff

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Smart Additive Manufacturing

Able to spot and understand inner structural defects in terms of microcracks, porosities and bubbles effectively. Reduced defect rates by up to 30%.

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Ultra Precision Manufacturing

Switched from the regular cutting tool replacement process at every 200 products to a monitored based system that extended the life of a cutting tool by up to 3 times.

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Automated Defect Detection

Automated defect detection reduced the man power required and therefore reduced the associated costs substantially. It also allowed staff to focus on other business critical tasks.

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Automated Quality Inspection

An automated product quality inspection system which has increased quality levels and saves £20m per plant annually.

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ML Based Design

The design process is more automated and new wing design iterations can be produced in a much shorter time frame, hence achieving the optimal design selection quicker than ever before.

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Preventive Maintenance Support

Health Indicator application provides early alerts that equipment is degrading and likely to need maintenance.

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Robot Assisted AM

Cross domain transfer learning significantly improved the performance of the robot. It could also be further developed to predict and locate defects that occur during the robot assisted AM process.

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Energy Usage Optimisation

Power usage effectiveness (PUE) is an important industry metric for measuring the energy efficiency of a data center. Optimising this can provide huge cost savings of up to 20% in this case

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Smart Factory Innovation Hub

National Composite Centre, part of the HVM Catapult selects Smartia and it’s industrial intelligence platform MAIO to provide connectivity, data management and AI for their Smart Factory Innovation Hub

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Intelligent Remote Monitoring

MAIO platform providing intelligent remote monitoring of assets, leading to a reduction in maintenance and service calls as well as substantial energy savings. Reduced asset failures and carbon footprint.

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Industry 4.0 for SMEs

Electric pump at the MTC connected and data streaming to MAIO (Cloud). A successful demonstration, for manufacturing SMEs, of how Industrial IOT and AI is available to them without having to break the bank.

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Tool Life Optimisation

Condition-based tool replacement using data and machine learning to inform decisions. Leading to a reduction in cost and extending the life of the tools.

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AI-based Security at the Edge

Smartia’s MAIO will enable AI at the edge, supporting privacy-preserving distributed learning. Use of AI for cyber security to detect attacks and improve the security of large scale IIoT systems.

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