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Ready for the future? - with Industry 4.0

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Industry 4.0 will reveal the fourth industrial revolution according to the Federation of German Engineers (VD) After the introduction of autonomous (steam) machines and industrial mass production (assembly lines), via automation (with programmable logic controllers), now comes Industry 4.0 where people occupy the centre stage and intelligent machines and instruments serve them through smart interconnection.

Industry 4.0 will reveal the fourth industrial revolution according to the Federation of German Engineers (VD) After the introduction of autonomous (steam) machines and industrial mass production (assembly lines), via automation (with programmable logic controllers), now comes Industry 4.0 where people occupy the centre stage and intelligent machines and instruments serve them through smart interconnection. It sounds like science fiction and sceptics are fanning fear of a lack of information security and reminding us of the doom-mongers who warned of physical harm as a result of the high speeds of the first railways. If we are neither able to stop the future nor want to, then should we not prepare ourselves better? The future will come, but are we ready for it?

What is Industry 4.0?
Industry 4.0 is generally presented very abstractly/ theoretically. To make it more understandable, the intelligent milk carton – which orders a replacement from the supermarket if you throw it into the recycling bin rather than put it back in the fridge – is often cited. The practical use of this may be hidden from the majority, and therefore an extended example is given here: A baker packs a transponder into the bread – it not only has a simple label but also ‘knows’ all of the ingredients in the bread, and more. When the buyer of the bread leaves the shop, the bread informs, for example, the seed grower, the farmers, the suppliers of farm machinery, producers and suppliers of fertilisers, mills, manufacturers of milling machines and logistics experts etc. so that, thanks to the purchasing information, the future direction of their own businesses can be planned ahead. If the buyer of the bread now takes a piece of Irish butter and some Danish ham out of the fridge, the corresponding supply chains right up to the upstream suppliers of milking machines or abattoir tools are informed. If our model customer now chips a tooth biting into the bread’s transponder, not only is an appointment made with his dentist completely automatically but also the information is made available, anonymously of course, to the dental laboratory, the refinery and the gold mine in South Africa as well as the appropriate logisticians. If you think this is ‘over the top’ you are, of course, right today, but just as the ‘social’ networks and other ‘free’ service providers like Google collect masses of data, even more copious data will be collected in the future. 

Modern cars already collect data which, for example, adjust transmission switching speeds according to personal driving style or are saved ‘anonymously’ in order to ensure sufficient vehicle development. Also, for example, in the case of a goodwill or warranty issue, to match the ‘anonymous’ data to the car in order to inform on the owner. And if an ‘intelligent’ car is already able to make an appointment with a garage using the collected data, and directly enter this appointment into the car owner’s personal calendar via the Cloud, then, for many people, this has gone far too far.

The feared or actual loss of control and the apparent powerlessness associated with it should, however, not lead to an overall rejection but rather, rules must be constructed and if someone consistently breaks the rules of the game, then he should be excluded from it. Technology that is supposed to serve people must leave the decision power with the people.

More complex than thought?
Everybody knows the example of the car that is braked sharply by the driver before a traffic jam thus directly warning the cars behind without the help of an overriding control. So that the following car is able to recognise that the car in front and not some car on the opposite side of the road or on a crossing street is emergency braking, the information from the braking is not enough; but rather, lots of information is needed from it and from other vehicles that are close by.

Only when such a system is safe against false alarm, is it accepted. After the Interbrau exhibition in 1977, we thought that you could optimally control a bottle refilling facility with a central control. Some disenchantment followed, and thereafter automation was simplified with each machine primarily focused on what was happening directly in front and behind it. People were again responsible for the vision.

The task 
If every machine now communicated all covered parameters to all the other machines in the facility, would every machine then be able to process this information and thus optimise their own operating parameters?

If machines are able to communicate certain parameters but none is listening, then everything remains as it always has been. If now a second and a third machine join in which not only communicate, but are also able to ‘listen’, a benefit appears relatively quickly. Of course, this can only work if all the machines are speaking the same language. As the first, second, and third industrial revolutions took place either spectacularly or allinclusively, the fourth revolution will be introduced one step at a time as the costs quickly pay for themselves. It is certain that more and more machines will make data available and individual machines will use data selectively.

For quality inspection related to production controls, samples are commonly taken and tested according to a set inspection plan. This plan is usually time-based, meaning that at the start of production or when the product changes, or every x minutes, samples are taken. If the results lie within pre-determined limits, the inspection interval may be correspondingly extended according to a set plan. Machine controllers typically compensate for variations in production. To refine parameter setting, feed-forward is being considered whereby one ‘says’ to the machine controller, for example, that you’ve switched to another tank and changed the configuration with the altered filling level. We’ve known for years that this is not really suitable but we live(d) with it for a lack of alternatives.

In actuality, a good control system should do what a competent, highly motivated and well informed employee would do, just more quickly and tirelessly. The model employee, who operates the bottle filler knows, for example, that the filler’s preload pressure has to be higher during start-up or after prolonged production interruptions than during continuous use with lower temperatures. If he observes larger actuating valve changes in one valve, he knows which inflows the machine controller is now trying to offset. Depending on the intensity of the actuating valve changes, he knows how to quickly get back to a constant level with manual interventions, and which quality parameters should potentially be checked. If he now carries out quality checks, he records not only the results but also knows which parameters he has to adjust to ensure that products are only produced within the set limits.

If the product brims over even more, he doesn’t wait until the fill level control discharges more bottles but instead, he reacts immediately. Bottling facilities aren’t mass products like ‘smartphones’ for example. A control system which produces the specialist competency of the model employee will still probably take decades. But that doesn’t prevent anyone from taking the first steps or relieving pressure on model employees and giving real employees tangible support. Even the manufacturers of fillers, for example, will initially give their machines ‘ears’ if other machines are available to ‘speak’ to them. 

Solution easier than thought!
Just a few years ago, Steinfurth Mess Systeme GmbH introduced the system called CPA (Compact Package Analyzer). Instead of teaching a variety of devices universal languages, just a single device was made ‘clever’. For example, in addition to providing measurement of torque moment needed to open a screw cap, the Steinfurth TMS torque meter took over the task of the ‘master’, or ‘speaker’, for all connected measurement devices which directly compare factors associated with product quality on the bottling line, as perceived by the customers. This means that devices which measure the CO2 content, capacity and concentration of a beverage, act as ‘slaves’, relaying their data to the ‘master’ – in this example, the TMS torque meter. The master generally takes over the unique allocation of the measurement as a trial with the help of an integrated barcode scanner and the redirection of data to other machines via a normal Ethernet port over a computer network.

In principle, every meter capable of featuring a data interface can be integrated as a slave into this system. This is how refractometers from Schmidt & Haensch, Maselli or Bellingham and Stanley, pH meters or conductivity meters, for example, are used as slaves. The master, however, is not just a ‘speaker’ but also a ‘listener’ It already receives changes in sample and procedure settings or rules on limits from the ERP system, for example.

If the data communication is interrupted or simply not installed at all, the system works independently and saves data internally.
Communicating with the system via the integrated touchscreen or alternatively via a USB stick is always possible. Measuring procedures and limits may be influenced by other parameters. Therefore a different limit may be presented on start-up or for certain tanks or tank contents as a modified measuring procedure, depending on the temperature of the product. If major control events occur in the drink maintenance area or with the fillers, or if inline meters are giving warning messages, these machines are able to recommend certain checks and the measured values which would then be processed directly by the machines which requested the values. This reduces the risk of products being outside limits or being sub-par because fewer economic operating conditions are produced. Beverage manufacturers who use the system partially for several years particularly appreciate the future viability of the concept.

Conclusion
The term ‘Industry 4.0’ should not be used excessively. Not every exchange of data is the start of an industrial revolution. Industry 4.0 is probably neither a revolution nor a revolt but rather actually an evolution. Information security is a minor problem to be solved. Cost-benefit analysis should be at the forefront. Only when system and manufacturerindependent data exchange can easily be ensured, will promised benefits also be achievable. If you don’t want the technology of yesterday tomorrow, you have to make the correct decisions today. With the example system introduced here, you are future-proofed since it allows numerous forward options without restricting today’s available and useful possibilities.

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