With their own decentralised computing power right on board, sensors may no longer need to rely completely on a higher-level or central control system to process and make sense of all the data they produce. They can also provide additional data to the control system via IO-Link. Some even process applications, or ‘Smart Tasks’ by themselves. Soon, some will combine multiple functions in a single device, for example, detecting piston position, vibration and angular velocity for end-of-arm tooling.
Integration of hardware takes place at a local level within the systems and control architecture, but the data generated can be shared not just at the machine level, but also via cloud-based systems. First, that data can be monitored and trended on a PC, machine HMI or cloud-based dashboard. It also has the potential to be used in ERP (Enterprise Resource Planning) and MES (Manufacturing Execution System) software; indeed, this is seen as fundamental to the future of Industry 4.0 manufacturing and logistics.
Digitisation, intelligence and networking will increase until, eventually, systems will control and optimise themselves – all using the data from sensors. Data transparency enables trends to be monitored and gives us the ability to understand more about a system. From Overall Equipment Effectiveness (OEE) to Deep Learning, it is the integration of the data that allows a user to become more aware of what is happening within a system.
Read the full article in the July issue of DPA.