This blog has kicked off with two acronyms, so let’s clear up those first. The IIoT is the industrial Internet of Things – that is, the branch of the IoT that is specifically concerned with manufacturing. Factory floor designers and managers are starting to wake up to the fact that implementing even very small and simple elements of connected technology can have a huge impact. Retrofitting a sensor that measures that amount of oil left on a reservoir for piece of machinery, for example, can alert maintenance staff to check and replenish oil and avoid machine wear and tear.
OEE is Overall Equipment Effectiveness – and this, too, locates us firmly in the manufacturing space. It was first coined in the 1960s to evaluate how effectively manufacturing operations took place – and while it gets interpreted in different ways, it can be broadly understood to cover three key metrics.
This refers to the proportion of scheduled time that the manufacturing operation is available. It is, essentially, a measure of uptime. Availability is negatively impacted if machines break down, require unplanned maintenance and repairs.
Performance and productivity
This all about the speed of production – how many components are produced per minute, per hour, per shift and so on. Speed is negatively impacted if machines are in a poor state of repair and stop operating at optimum levels, or if bottlenecks occur in process.
This is a measure of – well – the quality of the components being produced. Or more specifically, the proportion of manufactured products that are deemed of good enough quality to be sold, used and so on. Once again, quality is negatively impacted if machines are in a poor state of repair, or if consumables such as oil and water are allowed to drop too low.
Enter the IIoT
So, let’s imagine a manufacturing operation that is analysing each of these three areas, and attempting to improve them in order to maximise overall OEE. Where does the IIoT come in?
As we’ve pointed out, all three metrics depend on every machine on the factory floor being in a good state of repair, with consumables at optimum levels. Those machines also need to be kept in an appropriate environment – at the right temperature, for example. And they need to be arranged in the most appropriate manner for maximising production efficiency without causing bottlenecks.
Clearly all of these factors can be handled by human intervention. Maintenance engineers can circle the factory floor, checking Human Machine Interfaces (HMIs) and looking for visible and acoustic and low levels of lubricants and fluids. But this is actually deeply inefficient – it’s a waste of precious man hours and resources that would be better applied to more strategic ways of working, planning for the future, driving process efficiencies and so on.
Far, far better to carry out essential maintenance, consumable top-ups, upgrades and repairs at exactly the right moment – before they have negatively impacted performance but not so early that the machines are not being appropriately ‘sweated’. And choosing these perfect moments can be done automatically – if you are gathering and analysing the right data. Information on temperatures, numbers of actions repeated, wear and tear, consumable levels and countless more statistics can be automatically collected by IoT-enabled sensors and analysed locally or transmitted to a centralised analytics engine for monitoring and decision-making. This is the IIoT in action – enabling manufacturing operations to sweat their physical assets, keep closer than ever control over machine performance and process, and, ultimately, deliver the best possible OEE.
Find out more about now IIoT is supporting OEE and read our Gemba client case study.