Artificial intelligence (AI) software solutions for capital intensive industries to solve predictive maintenance, process optimisation, and quality control (QC) problems.

The growth in global IT spend is not enough to keep up with the amount of data that the world is generating. In the last two years, 90% of the worlds data has been created and machine-generated data will account for 40% of internet data. A typical factory now generates one terabyte of data per day and is adding more data via IoT and Industry 4.0 initiatives in the form of robotics and autonomous manufacturing processes, 3D printing, and smart machines and sensors at the edge. As the amount of data grows so does the number of data structures; and these new data structures have different forms, sizes, and shapes creating new challenges for any business to capture and incorporate into existing data sets and IT tools to realize and unlock the potential value. An international SME helps companies solve these large and complex data management and analytical problems. Firstly, there is a platform built to digest and analyse extremely large data sets. Secondly, there are unique and proprietary technologies to harmonise unstructured data for quick and easy incorporation into big data analytics. These two also apply to edge computing and analytics, on-site or in the field. These technologies have been developed and stress tested (field tested) in the following industries: metals and mining, steel, pipeline manufacturing, oil and gas, chemical, aviation, food and beverage, and fast-moving consumer goods. The lessons from the engagements have been built into many industrial out-of-the-box use cases. Working with big data and unstructured data is not enough nowadays. Users need to be able to go live quickly and to introduce changes quickly into analytical and output requirements. The company’s proprietary deep learning modules negate the need to hire data scientists for every deployment and the modular architecture enables quick revisions. The platform can be trained and tested for full deployment in weeks as opposed to months and it self-adapts to changes. The modular designed architecture allows for refined problem solving and deployment flexibility that results in fast go-live times. As mentioned above, the company has use cases and scenarios from several sectors that lend themselves to faster troubleshooting with other users in similar segments. The company keeps working on a pure plug and play system with an intuitive user interface, a built-in comprehensive set of user defined data and analysis manipulation tools, and robust and flexible API’s. The platform has incurred the below benefits for large and complex organisations: 1. Predictive Maintenance: the platform detects deterioration or anomalies in equipment and tooling performance, predicts remaining useful lifetime, and recommends optimal settings to achieve desired outcomes and schedule condition-based maintenance actions. 2. Product Quality and Infrastructure Integrity Control: using advanced computer vision, non-destructive testing data, production and part diagrams, and sensor data the platform identifies and predicts product quality, process variation, and suggests actions to prevent the production of non-compliant products. 3. Process Optimisation: the platform predicts and recommends actions to take to achieve the best overall economic effect. Opportunity and/or problem statements can come from the manufacturing floor, large complex machines which have useful lives impacted by the type of utilisation, pooled assets that may be underutilised, repair and inspection operations where engineers have to decide to use, repair, or scrap parts, just to name a few. The company seeks industry partners for commercial agreements with technical assistance. Extensive support is available for implementation and aftercare. Also, technical cooperation is sought with industrial players working on specific problems for their sector. New IP may emerge in the process that they can then exploit across the sector. Finally, VARs and integrators are sought for licensing