Industry 4.0 or Smart Ass 1.0?

Posted on Posted in Future Vısıon, Industry, Technology

Industry as a word is coming from the roots: industria “diligence, activity’’ and later used for the meaning ‘systematic work for a particular trade or manufacture’ in 16th century. As part of endeavour for achieving minimum energy state we are trying to avoid the ‘activity’ part since long time; the first industrial revolution was more than 200 years ago at the end of 18th century.
Thanks to the mechanical power generated by steam replacing the manpower gave people the opportunity to have coffee break.
These were the very first moves in England while French were going through the revolution in a different aspect; working class seeking for the rights to get baguetteon table.

 

It took more than a century to have the next change on stage by the introduction of mass manufacturing and electric power.
USA and Germany took the leadership of technology from England especially in the chemical, petroleum and automotive industries. The first giants of industry popped up in those countries.

 

In the second half of the past century computers and automation tools changed the industry third time by achieving higher capacity with higher efficiencies in manufacturing. In this article, we are not going to discuss if the increased volumes of manufacturing plants were required by the market or the volume increase together with price/cost decrease created a bigger demand in the market. However, we will discuss the next step.

 

 

What will be the next step?

Nowadays, we are taking this a bit further than minimising our physical efforts to the level of inactivity and looking for the ways for ‘ruling the world’ from our couch.

Having seen the trends of interconnectivity, personalisation and digitalisation in our daily lives, Germany has announced their answer to this question by introducing Industry 4.0 as their next industrial strategy. Dutch calls it Smart Industry and in general it is called Industrial Internet of Things (IIoT). Whatever the name is, it is about ‘smart’ factories which are expected to be more robotised, flexible, personalised and interconnected by using (real-time) data.

From these movements, we may interpret the following:

The market is asking for more volume in less time by more robotised lines, more customised solutions/products by introducing flexible lines and the users would like to have direct influence on the end product by being connected to the manufacturing companies.

In answer to this, the factories are not only expected to deliver the ‘more’ but also ‘mine’ and in the right time. This results in rather more complex than one-sided solutions such as manufacturing robots, 3D printing machines or interconnected devices. The future requires the combination of all. For example, ‘modular manufacturing’ will be one of the emerging technological innovation areas in the roadmap to the smart industry but in order to reach required ‘smartness’, this technology is not enough without having the data connection to the clients of the factory. By using the modular elements, the manufacturing line may be easily adjusted to the ‘instant’ requirements of the market based on communication with the clients. As always the communication will play a central role but with a tiny difference: This time the communication will take place between many ‘thing’s virtually, thus in digital environment. Therefore, the shift to digital world will put us, as human beings, in a challenging position where we may easily lose the control and understanding of what’s really going on around us.

Moreover, the change is not only untraceable but also rapid. In comparison to the earlier industrial revolutions, the 4th step is in the pipeline much quicker than earlier, in about 50 years time. This seems like a natural result of what is happening in our daily lives: everything is faster such as connections, food, transportation and even relationships. The question that we would like to explore is: Is it really the next phase of industry? Or instead are we putting ourselves into the sea of digital world where we will be looking for the ’smart’ for reaching the shores?

Finding the smart shores in the sea of uncertainties

A recent study by McKinsey (Digital globalisation: The new era of global flows, February 2016) shows that goods flow between regions increased 10 fold in the last 35 years and after 2007 the growth in flow of goods have been flattened, which has been affected by the crisis but still there is no sign of recovery. Whereas the data flow increased 45 times in the last 10 years period. From this, we can conclude trivially that we are exposed to 45 times more data than what we were 10 years ago. Estimate is that the flow will continue growing exponentially. This is an important indication when designing new value flows for ‘smart’ business models, which we will discuss briefly in this article.

Apparently the ‘smart’ part of the revolution is not stemming from only data communication but from decision making and acting. So, it is about upgrading from data to information by analysis then from information to ‘right’ decisions by reasoning and taking action. Experience of these actions, lessons learnt from success/failures will turn into know-how and by using the know-how one can make better decisions. However, the vast amount of data makes these steps much more complicated, which we can see as the art of decision making in chaos. In a chaotic environment, we need trust, clear goals and well structured reasoning to come to reasonable decisions/actions.

In this context, trust can be associated with secure data sharing, which enables the transparent communication of the goals of individual systems in a genuine way. Transparency in utilisation of data is crucial at the receiver’s end such that every stakeholder is assured that the shared data will be used only for the ‘right’ purpose. On one hand, privacy is an important criterion as each ‘step’ of personal lives turned into data currently. The personal data may be used for only providing or improving services but boundaries should be well defined. For this, national and international standards must be set and only then the playing field of the data users can be defined right. On the other hand, ownership of intellectual property (IP) is critical for defining the . In the case of manufacturing and technology, companies will not be willing to share critical data of their technology with distant partners unless international standards are clear for IP ownership and protection.

Clear and common goal setting is a matter of communication; which needs prioritisation, filtering and authentication of data flow at the processing phase. An increasing number of sensors will be measuring a range of parameters from the users end, suppliers and own production facility, in some way all must ensure that the data sharing is trustable and reliable. It is similar to a fire alarm which have gone loud several times due to overcooking of food; would you skip the signal the next time or every time take the necessary precautions? In these circumstances, the common strategy of all parties must be inline such that no resources are wasted.

Reasoning in this case is represented by computational power of computers, which is expanding exponentially. It is not very long from now when the processing power of a computer will surpass human brain’s capacity. Estimate is that within 25 years from now, one computer will have more processing power than all human population. So, robots will be able to process parameters risks, future scenarios, errors and others much more accurate than human beings.

These considerations and developments affected the role of manufacturers in global economy by changing towards more service orientated rather than goods orientated organisations. As discussed earlier, the market requires ‘smart business models’. For example, pay per use concept is already becoming popular in business-to-consumer services as well as business to business context and this will be affecting the industrial practices. Nowadays, the priority is the access while it used to be possess. Companies as well as individuals would like to avoid the risks of possessing. Manufacturers will be looking for solutions to avoid the heavy burden of manufacturing equipment by leaving it to specialised local manufacturers. Therefore, it seems like giants won’t be investing in manufacturing facilities, instead they will invest in software for data management. The role of these corporates then will be to be the bridge between demand and supply by checking the pulse of the market almost real time. Having, or even (pre)monitoring the feedback from clients through data, these giants will use the facilities of third parties to bring services/products to clients (see the article over Pay on Production- PoP- business model(1))

For all these, associated costs are of course playing an important role as much as quality. Local manufacturing in the above mentioned business model will reduce transportation costs especially for products with low value density such as textile, food, consumer electronics. The shift to localised manufacturing can be realised in different scales in city, country or regional level taking the cultural, climatic, resource, market demand similarities into account. For example, customising the products according to local resources (therefore customisation based on climatic conditions and material supply) will lead to reductions in material costs as well as environmental costs. One of the most critical aspects will be labour costs which has been a determining factor for manufacturing location changes. (2)

When we look at the possibilities and above mentioned issues that recent developments bear, being ‘smart’ in decisions has already become much more challenging. There are many inputs and the impact of decisions has the potential to be much larger. Under these circumstances, smart would be taking small steps, thus local action, and expecting results at greater scale, thus global impact, thanks to chaotic environment.

SMART ASS 1.0

Having considered most of the parameters and indicators briefly, our conclusion is as follows:

We are at the gate of a new era of industry, which we cannot call industry anymore. A better name would be SMART ASS, i.e. Smart Manufacturing network of ARTificially intelligent Actors with Shared Skills which is run by collective know-how. We define this breakthrough as the new system of (in)activities where the goods are not central but the know-how is at the centre of value streams between actors of the network. Skills are shared in an optimized way between artificially intelligent actors whereas physical goods are only part of this system. The most important actor being people, keywords of the future: sharing, communication, digital, decentralised, local manufacturing, collective knowledge, shared skills, global know-how and data processing.

It is a common conclusion that the one who holds the data will hold the power. It is right but incomplete. The one who transforms data to know-how will be powerful. So, we will see physical localisation of goods and digital globalisation of know-how. In other words, while our asses are sitting on comfortable chairs, our ideas and know how will be moving global with unforeseeable impact.

Sources
1. http://www.iwim.uni-bremen.de/publikationen/pdf/b092.pdf

2. A nice read about global manufacturing networks: https://www.nist.gov/sites/default/files/documents/mep/data/Manufacturing-the-Future.pdf

 

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