In preparation for Dave Wibberley hosting a round-table discussion on Industrie 4.0 at the Connected Industries Conference, he interviewed Deon Fourie who has some very clear ideas about Industrie 4.0’s chances of success in Africa, and the rest of the world.
According to Fourie, Industrie 4.0 is still in its infancy, however, the concept of Big Data and automation coming together to provide infinite manufacturing flexibility, and thus be able to produce exactly what the customer wants, is actually the objective of Lean. The concept of Lean is to be able to replicate the economies of scale across multiple products.
Industrie 4.0 requires near perfect process understanding
The problem with Industrie 4.0 is that before you can automate something you have to understand it exceptionally well, plus you need to have consistency in all the inputs to the process. This understanding is often what is lacking and inconsistency in the inputs compounds the problem.
“It is important to have control of all the suppliers as well as the process, since everything that may impact the process has to be stable,” explains Fourie. “The process itself has to be stable, the raw materials have to be stable and the conditions under which tooling is manufactured have to be near perfect in order to achieve the same result every time.”
The conditions to be Industrie 4.0 ready are certainly not apparent in South Africa, yet.
“We cannot simply assume that every tool will produce a quality product every cycle,” argues Fourie. “To produce a quality product you almost always need human intervention, skill and judgement. Lean refers to maximising customer value and minimising waste and creating more value for customers with less wasted resources. Being Industrie 4.0 enabled means taking Lean to the nth degree, effectively taking humans out of the decision making process.”
The strategy is to have brilliant processes that allow average people to achieve exceptional results. The trick is to remove variance, irrationality and waste from every process, which is the objective of Lean. Once this has been achieved, the average person will be able to produce an extraordinary result. Unfortunately for most manufacturers, the situation is that brilliant people are running processes that are full of variability, irrationality and waste. The end result is mediocre. A Lean strategy is to have the average person achieve extraordinary results through the elimination of waste, irrationality and variation. Tooling is just one example of variation in manufacturing.
“Industrie 4.0 is not a technological challenge, the technology can do it,” emphasises Fourie. “The problem is that first reducing the waste, irrationality and variation throughout a manufacturing process, to prepare a business for Industrie 4.0, is extremely difficult. No business in the world is currently entirely Industrie 4.0 ready.”
In Lean talk, this term, jidoka is defined as ‘automation with a human touch’. It refers to standardisation of processes and still keeping the human judgement calls where complete automation is not prudent. The journey to Industrie 4.0 is not going to happen overnight, but you can prepare for it by standardising ways to drive out irrationality and reducing the job of the operator to a level where it becomes simple for an average person to get good results.
According to Fourie, there is a lack of management capacity to enable elimination of variance, irrationality and waste. The reason for this is not lack of education nor knowledge in manufacturing, it is more about attitude and dedication to hard work. Managers tend to think that they do not need to get their hands dirty dealing with the nitty-gritty of the shop floor, they tend to become office bound focusing on policy and strategy.
The attitude in Japan is different, simply because no one is entrusted with significant plant and equipment without first proving their abilities to solve problems on multiple levels. Also, the operator managing the plant is respected as an expert at running the processes.
The ten thousand hour rule and statistics
Anybody familiar with Malcolm Gladwell’s book “Outliers” will be familiar with the concept of the 10 000 hour rule. The principle of the ten thousand rule is that to become an expert in any field you need at least ten thousand hours of practical experience. If someone aspires to revolutionise manufacturing therefore, they will first need to spend about ten thousand hours working on the shop floor eliminating waste, irrationality and variance, before they will know where to start.
According to Fourie, very few South African producers have got statistical process control fully working for them. Some producers insist their suppliers are six-sigma, (the on-going effort to reduce process and product variation through a defined data-driven project approach) or at least three-sigma. Then, when questioned on whether or not a process capabilities study has been done and how control is determined, there is confusion on the definition of control limits and specification limits.
The question is whether the manufacturing processes are in control and whether the necessary triggers are in place to bring them back into control when they are not. If there is waste during setup, then this needs to be analysed and reduced. Proper analysis of waste and how much downtime is experienced during a setup is just one component of Lean. This one component is essential when considering Industrie 4.0. It should also be noted that once this one component is standardised and fully repeatable there are typically 20 additional elements required to consider one to be a lean manufacturer. Once all elements show significant process, then automation can take place and the concepts of Industrie 4.0 can be addressed. Automation is just one step of Industrie 4.0; it has got to feed back into efficiency right across the organisation.
Degrees of efficiency
There are degrees of efficiency that one can get from the concepts of Industrie 4.0. If you apply the principles of Lean you can get 80% of the benefit for virtually zero cost. Lean is about respecting people that are invested in the production process. These people are the most important leverage area for standardising and improving the processes. They are both the designers and the custodians of the process, and they are the ones that can best standardise processes for efficiency. The leaders and managers need to create the conditions that enable them to do a good job in order to standardise stuff.
Besides the three objectives of Lean – irrationality, waste and variance – there are neural networks, the things that keep everything working synchronously all the time. The neural network should operate sub-consciously without referring every decision to the organisational conscious brain (the ERP). The neural network must be interfaced in real-time to customer requirements and must continuously take decisions about how to make operations work most efficiently at that particular point in time. In the Lean world this is referred to as just-in-time (JIT) and just-in-sequence (JIS). Unfortunately, we are still miles away from having information systems that are able to communicate split second decisions to those that are adding the value. The focus of I4.0 should be to first create the neural network by using the Lean methods of pull production, coupled manufacturing, JIT and JIS. Much work is still needed in this area.
Not everything will be solved by Industrie 4.0
Are there manufacturing industries in Africa better suited to take advantage of the IIoT revolution? Companies with a limited range of products that have already successfully gone down the road of Lean could take advantage of the IIoT. The reason driving them towards Industrie 4.0 could be a lack of good people engaged in what they do, as Industrie 4.0 tends to eliminate people from the manufacturing process. In Africa this would prevent union problems, but it may be politically unwise to implement.
There are practical constraints as well. One of the largest manufacturing companies in Europe, which designs, manufactures and services systems and components for many of the world’s leading aircraft, vehicle and machinery manufacturers, tried to pioneer the Industrie 4.0 concept on one of its simplest, low technology products – a wheel made of only two items, a rim and a disc.
Making the tooling to manufacture the disc is based on a concept known as shared tooling. So, before planning the production of a product you have got to know what the tooling was last configured for. Once this is known you can decide what it can do next. In addition, there is the tool build type, not everybody knows how to build every tool. In this case, only certain people on the day shift know how to build the tools in question. Getting the tooling to the right person on time is a major problem, and the company has not been able to solve it using computer algorithms. So in the end they had to resolve it by using people that are smart enough to know how to do things.
“The company was unable to make the manufacturing of a simple component Industrie 4.0 operational as the tooling constraints were simply insurmountable,” concludes Fourie. “It will probably end up with one line that makes one product and then they will put Industrie 4.0 on that. But this defeats the whole point, which is to have the entire factory linked to Big Data and thus Industrie 4.0 operational. In manufacturing there are always going to be things that are extremely difficult to solve without humans. The humans that do their 10 000 hours somehow manage to resolve problems that machines cannot. Any managers that are divorced from this reality are going to find Industrie 4.0 very difficult to attain.”
Dave Wibberley, MD of Adroit Technologies adds, “The above discussion pertains to a technically advanced manufacturing process, however Industry 4.0 or IIoT when applied to process industries and for example water distribution systems will be able to take advantage of the new revolution. The ability to accurately measure many more pressure points within water networks, as an example will allow operations to get a much better understanding of how that system is performing. Low cost, high density energy monitoring will do the same for customers wishing to get a better handle of energy costs.” We have a cloud infrastructure that will support customers wishing to test and even implement IIoT systems and are working with the Network and other IIoT radio networks to test SIGFOX, NBIoT and whilst it remains to be seen who will dominate this space the value will be immense for those customers and companies that get it right going forward.”
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