There is a huge amount of industrial machinery in use today that was never designed to be connected to other machines, let alone be connected to the internet. This means that optimising machines on a factory floor to work efficiently together is an extremely manual process, as is monitoring the health of these machines and planning maintenance downtime.
Connecting these devices to the internet, allowing you to gather data that can help maximise output and optimise maintenance schedules, is what IIoT is all about.
IIoT is very relevant to businesses looking to enhance productivity, automate manufacturing or predict equipment failures before they happen.
The term IIoT often goes hand-in-hand with Industry 4.0 (the 4th industrial revolution), both of which are helping to increase productivity through all aspects of industry, resulting in lower costs and more efficient utilisation of assets.
IIoT is not just about reducing costs though. Health data, such as temperatures and voltages from sensors on IIoT connected industrial machinery, can be used to inform you if maintenance needs to be carried out on a device before a failure occurs, or can be used proactively to reduce the speed of operation to prevent a machine from overheating, therefore reducing downtime.
There is no standard protocol used for connectivity to industrial machinery. A factory floor could have 5 machines, with all 5 using different protocols for connectivity, such as Modbus, RS232, USB, PROFIBUS or PROFINET, making connecting them to the cloud a challenge.
On some machines, the only way to read data from it is directly from its monitor.
Finding a way to read data from all of these machines and converting it into a format that is useful, is the key problem to overcome. An embedded PC (or IoT Gateway) that supports the relevant protocols and connectivity can be used to transfer data to the cloud for analysis, the results of which can then be used to improve productivity and reliability.
Processing can also be carried out locally by the embedded PC/IoT gateway on a smaller subset of data, often referred to as ‘edge computing’, resulting more responsive feedback, while offering resiliency if the connection to the cloud is lost.
