Modern plant automation systems provide transparent monitoring of system status, plus tools such as condition monitoring or predictive maintenance. All help to reduce unscheduled downtime and improve productivity. However, the same is not true of many existing installations where the owners have yet to recognise the benefits of digitising legacy equipment from fairly simple and low-cost improvements.

Certainly, the requirements for digitising legacy systems may seem demanding as there was no OPC UA available during the original installation. There may not even be an Ethernet interface. But there are scalable solutions for collecting a lot of system data that can improve overall system efficiency. For example, connecting sensors to the power supply to help ensure efficient energy management. Recording that information, along with production machinery start and stop times via decentralised I/O, can provide essential comparative data. Cost-effective sensors and/or camera systems that can register and record pass/fail product data at different points on the production line.

Users can also monitor their plants condition by implementing a Smart Condition Monitoring system. These work by attaching vibration sensors to rotating machinery such as fans, gearboxes, and motors. The sensors connect via a Power-over-Ethernet cable to a dedicated analyser from Mitsubishi Electric e-F@ctory Alliance partner.

Start digitising legacy production

Older systems, while reliable, will be more vulnerable to failure because of their age. The ROI from making repairs and reducing downtime in existing equipment is higher than investing in new machines. Start with the measures that are easiest to put in place. These include energy management and the recording of machine status data to provide an insight into system efficiency. At the same time, implementing condition monitoring as the basis for predictive maintenance to reduce downtime.

The more data collected, the more opportunities there are for system optimisation through real-time edge or cloud analysis. But what is important is to examine the possibilities for individual systems, considering the return on investment in each case. In most cases, making legacy installations fit for a digital future is possible with least effort or investment. Companies will enjoy more transparency and flexibility of their production facilities. Time to market and the ability to produce individualised products cost-effectively will depend on the degree of digital automation.

Next level: artificial intelligence within manufacturing

Companies digitising legacy machines will also reap the benefits of emerging technologies such as artificial intelligence (AI). These technologies will build on the key elements of analysing smart machines and big data to optimise production.

Informed analysis delivers better production decisions making, and the techniques of deep learning and machine learning are emerging to automate the planning of production actions. It lays the foundations for the broader use of AI to achieve greatest flexibility in volatile markets. In this way, producing individualised products for the same price as mass-produced products. Smart data, big data and the analysis of these in conjunction with AI will support users to realise market requirements.