Whether Industry 4.0 is going to be a revolution can only be seen in hindsight, however enabling manufacturers to make use of advanced technology, will surely change things in manufacturing. Hitachi Solutions shared their top trends in manufacturing for 2019, of which several have a direct link with OEE. Let me shine a light on 3 issues here:

1. IoT
Internet of Things, which means – and this is the very short version – that devices and systems are interconnected on the internet and communicate by themselves, without human intervention. There are two important questions to be answered:

  • How precisely does the information that is being shared adds value in the process? In real life I 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 really smoothly creating value.
  • 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, and according to Hitachi, 63% of manufacturers strongly believe that IoT will have a positive effect on profitability over the next 5 years. Unfortunately, how precisely the investments in this technology will raise your OEE is mostly not answered. My advice is to spend plenty of time to find out how and in what way this form of communication will precisely lead to improved availability, performance or quality in your value creating process. Remember: complexity can only work when it is profoundly understood. And that is not just an IT thing: operations management cannot be involved deep enough! Analyze your OEE and figure out: which loss 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. 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. (Don’t even think about it when your equipment has MTBF’s 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 in 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 in 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 by a solid preventive maintenance strategy, which will rapidly lead to less unplanned downtime, less cost and higher reliability.

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

I hear companies state they will not be able to survive without big data. Being a manufacturer, data can surely provide you with useful insights on how effective machines are running, and more important: where processes can be improved, where the losses are. With THE RIGHT data, you can improve your Overall Equipment Effectiveness.

Knowing the fault rates in the majority of databases, I 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 I visit, so far I have rarely found any advantage of such.

What DOES makes sense is combining data to monitor process stability via SPC with 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 your 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 far more convenient way than years ago. That is why Fullfact has chosen a close cooperation with DataLyzer (The leading SPC specialist) and Inmation (the leading connectivity partner in industry)

What other trends do you see in manufacturing, that are related to OEE? Do you want to know more about OEE? This might be an interesting read for you.

Arno Koch

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