How did Industry 4.0 deliver on the big expectations raised? And whether you are still in the midst of Industry 3.0, the Industry 4.0 revolution, or whether Industry 5.0 is already your reality? We are witness to interesting times, and enabling manufacturers to make use of advanced technology surely is changing the manufacturing world. Hitachi Solutions shared their 11 Trends That Will Dominate Manufacturing in 2021, of which several have a direct link with OEE. Let us shine a light on 3 OEE-related trends in manufacturing here:
- Is IoT the best next step?
- OEE and the importance of predictive maintenance
- Big Data and OEE
1. Is IoT the best next step?
IoT or Internet of Things means – and this is the very short version – that devices and systems are interconnected on the internet and communicate by themselves, without human intervention.
And what about OEE?
When considering if IoT is right for your company, there are two important questions to be answered:
- How does the information that is being shared add value in the process? In real life, we see tons of data that seem to be valuable but doesn’t improve the process as such. Or even worse: it is the justification of a process that is not creating value in a smooth way.
- Is the medium – IoT is complex technology – really adding value in the communication, or would a simple signal have done the job too?
The assumed benefits of IoT are that it will have positive effects on costs and efficiency, amongst other things. According to Hitachi, 63% of manufacturers strongly believe that IoT will have a positive effect on profitability over the next 5 years.
Will an IoT investment raise your OEE?
Unfortunately, how the investments in this technology will raise your OEE remains unanswered. Our advice is to spend time to find out how, and in what way, the IoT communication may lead to improved availability, performance, or quality during your value-creating process.
Remember: complexity can only work when it is profoundly understood. And it’s not just an IT thing: operations management cannot be involved deep enough! Analyze your OEE and figure out: which losses could have been eliminated through IoT and HOW?
It is tempting to just hope for the promised improvement, but unfortunately, it is not that simple!
2. OEE and the importance of predictive maintenance
Downtime costs manufacturers hundreds of thousands of dollars – literally. And fully reliable machines are an absolute pre-requisite for Industry 4.0.
Is your mean time between failures still an issue?
Don’t even think about it when your equipment has MTBFs of just several hours, as mostly seen in our thousands of OEE registrations. Autonomous, preventive, and predictive maintenance programs get you there. Measuring a correctly defined OEE will give insight into the resources spent on this loss. It is not very sexy, yet a classical TPM program can quickly help you out of the deadly trap that eats away the time of the maintenance engineers.
First, let your OEE measurement collect data that give insights into your downtime pattern. When the machine can communicate its condition and give information predicting when maintenance is necessary: great! But relax: for most machines, this can be perfectly done with a solid preventive maintenance strategy, which will rapidly lead to less unplanned downtime, less cost, and higher reliability.
Making the shift to planned downtime
Your OEE registration will clearly prove the value of this: shifting from corrective maintenance to autonomous and preventive maintenance means shifting from unplanned to planned downtime. From there you will start reducing the planned downtime. Predictive maintenance of course can be very helpful here.
Beware: whatever software you install on the equipment: it can and should help your team. Looking at the promises of some suppliers remember: if it is too good to be true, it usually isn’t true…
3. Big Data and OEE
We hear companies state they will not be able to survive without big data. Being a manufacturer, data can surely provide useful insights on how effective your machines are running, and more important: where processes can be improved, and where the losses are. With the right data, you can improve your Overall Equipment Effectiveness.
The good, the bad, and the ugly data
Knowing the fault rates in the majority of databases, we can hardly believe that stacking all such piles of data will lead to any reliable conclusion in the end.
In manufacturing, we see huge amounts of data being collected. To be honest, in the average factory we visit, so far we have rarely found any advantage of such.
Putting IoT, SPC, and OEE in the mix
What does makes sense is to combine data to monitor process stability via Statistical Process Control (SPC), using data to visualize the loss landscape via OEE. SPC will now show you what’s going on ‘below the surface’ (before things go wrong) and OEE will show you what actually did go wrong. The two of them now can steer your improvement efforts in the optimal way.
New technologies allow us to monitor, register and visualize this information in a convenient way. That is why FullFact works together with leading SPC specialists and connectivity partners in the field.
More thoughts on OEE and Iot?
Do you see other OEE-related trends in manufacturing that trigger your curiosity? Reach out to us if you want to discuss your manufacturing challenges and learn how OEE can help you improve your productivity.
Do you want to discover more about the 10 most important aspects of OEE in one whitepaper? Download the whitepaper here:
Do you want to know more about OEE? Then this information on Overall Equipment Effectiveness might be an interesting read for you.
