Industry 4.0, digital transformation and artificial intelligence (AI) are fundamentally changing manufacturing through the use of real-time production data and full automation, which has been outside the reach of many manufacturers. To compete, manufacturers need accurate, standardised and timely data to increase throughput and reduce downtime, which ultimately could feed predictive maintenance and other machine learning algorithms.
However, industrial machinery is often decades-old and fitted with the vendors’ closed process-control systems. Existing solutions to interrogate these systems are usually expensive and inflexible requiring additional software, servers, cabling, and specialist engineers. William Fish has developed a ‘universal’ solution that provides both monitoring and control of production machinery regardless of age, make or type.
William’s company, Manulytica, is developing a device that will be more flexible, versatile, scalable, and cost-effective than others on the market. The system will be field-configurable, plug-in and compatible with all common and legacy industrial sensors and actuators; both analogue and digital. It has been designed for retrofitting, complementing existing technology while decoupling process control data. It doesn’t require replacement of process logic control equipment or manufacturers’ installed sensors.
William has spent more than 20 years working in information and operational technology, studied engineering and computer science at Liverpool and Salford, and gained an MBA from Leeds University Business School. He says of the Regional Talent Engines programme: “The investment has been extremely useful. It is the lifeblood of startups and many good ideas struggle to come to life without financial backing. Being associated with the Royal Academy of Engineering has also opened doors. It has helped set up meetings with universities and global manufacturers.”
William feels that being based in Yorkshire is an advantage as it falls in the middle of the industrial and manufacturing heartland of the UK. The region is both a source of customers and for future employees. Now, William is completing product development and working through the initial patent application. He will begin developing predictive machine-learning models and have Manulytica’s first active factory device implementation before the end of 2022.