“Realization of smart production in flour mills is actually to put Industry 4.0 in practice with all its elements. First step is to decide. When you took decision, it means that you decided whether you want to be able to respond to market demands faster, to increase Overall Equipment Efficiency (OEE), and to reduce losses in parameters like energy, raw material and time. After taking decision, you have to start with digital transformation, but you should not forget that a smart factory does not mean necessarily a “dark factory”. Human has still a role.”

What are smart production and smart factory? One comes across in literature both with the “smart production” term and maybe more frequently with “smart factory” term. There are many definitions made for them. All of them are based on the “advanced manufacturing” concept which was once used widely in USA (1). Hence, understanding smart production is actually studying and understanding the transition from advanced production to smart production.

Smart production which is summarized shortly by some experts as “the self-controlling production type” (2) is also defined as “a set of manufacturing practices that use information technologies and network data” (3)

There are definitions for smart factory, but instead of going into detail of them, we can say that it is a quite flexible system working and learning in real time and running the processes autonomously.

For being able to set up such a flexible system, and to self-control itself, automation functions such as data collection, data analysis, and control

have to be realized without failure smoothly, rapidly and on time. This corresponds to Industry 4.0 which is expressed as the adaptation of information technologies to the industry.

INDUSTRY 4.0 CONCEPT AND REQUIREMENTS Reason of the revolution reference to the 4th industrial revolution Industry 4.0 is due to its different image from previous approaches and applications, and further as it enables great expectations in terms of its outcomes.

Industry 4.0 can be said to have a “smart” feature, and is based on “cyber physical systems”. It differs with this aspect from the previous industrial revolutions. We can see the historical development of industrial revolutions in Figure 1 below (4).

If we summarize with regard to developments, it is seen that machines are in 1st industrial revolution, processes are in 2nd industrial revolution, electronics and automation are in 3rd industrial revolution, and finally information and communication are in 4th industrial revolution better defined and better used (1).

One can say that Industry 4.0 which is built on automation and being first suggested in 2011 by Germany is an industry management trend to drive forward companies and consequently countries in global competition (5). Again, Industry 4.0 is also characterized with vertical and horizontal integration of production systems and production resources (6).

Objective of Industry 4.0 in technical means is the exchange of data between machines using Internet and proper hardware, and to enable improvement and development using those data promptly (7). More shortly, the purpose is to increase usable data and to improve decision making (8).

Positive impact of Industry 4.0 applications shows itself with increases in efficiency, turnover, and manpower qualification as well as increase in investments parallel to system requirements. It is tested clearly in Germany experience (9).

For the applications to be realized, a digital transformation is inevitable. Data collection, data analysis, full automation and consequently realization of Industry 4.0 will not be possible if digital infrastructure has not been prepared. This is because analysis of “Automation” and “Autonomization” with “Process Automation” and “Problem Forecasting” is needed, but analysis cannot be performed without data or late coming data (5).

For building a smart system, i.e. for applying Industry 4.0, one should be rigorous with system design principles (3), (4), (10). These could be summarized as given below.

Interconnection or interoperability: Between machines, and human and machines. Communication between people and smart factories is provided through Internet of Things (IoT).

Transparency: Vast amount of information collected from the system is available across the whole system.

Decentralization: The system makes decisions on its own with cyber physical systems. Technical assistance: The system assists human being on one hand, and the operator is in “consultant” position for the system on the other hand. This may not be necessary in factories where Artificial Intelligence (AI) is used at advanced levels.

Modularity: Flexible adaptation for variable individual needs is being reached in this way.

Industry 4.0 needs exact and as much as possible data. To achieve this will be possible with cyber physical systems. CPS can be defined as systems which integrate analysis and computation elements with physical components and processes. Although CPS is confused with Internet of Things (IoT) in some resources, IoT is the technology enabling the connection of all types of machines and devices and enabling the collection of data. If the application is industrial and connected elements are not only things, but things and controllers (such as PLC, DCS, PAC), then Industrial Internet of Things (IIoT) comes into question. In this respect, IIoT can be seen as the most important component of cyber physical systems (11).

For an effective application of Industry 4.0 in enterprises, a “hierarchical architecture of the smart factory” has to be built. Instead of going into more details here, it is shown in Figure 2 what the basic foundation should include and at what levels.

Like with the design principles of Industry 4.0, things and systems of Industrial Internet of Things (IIoT) have to run with the same principles, i.e. to enable the smart system which is decentralized, rapidly connecting, open to access information, real time integrated and autonomous (12).

CAN INDUSTRY 4.0 BE APPLIED IN FLOUR MILLS? In cases where serial production is purposed, Industry 4.0 makes sense if required informatics infrastructure is available. Smart production is possible in technical means under these conditions, but it is good to mention that for realizing Industry 4.0 also in flour mills, it is necessary to complete vertical and horizontal integration, and it is important to provide quick data flow and data analysis continuously without delay or disruption.

It has to be considered that smart production is not even in Germany which suggested Industry 4.0 approach completely realized except pilot plants although 8 years have passed.

When we regard the technology and elements relevant to smart production in every aspect, we see elements and concepts such as intelligent control, cyber security, virtual reality (VR), augmented reality (AR), real-time communication and data, big data, cyber physical systems (CPS), cyber physical production systems (CPPS), Internet of things (IoT), Internet of services (IoS), industrial Internet of things (IIoT), advanced manufacturing, cloud computing and cloud manufacturing, 3D printing and additive manufacturing, smart sensors, smart product and part, data and big data analytics, predictive analytics, data visualization, simulation, forecasting, enterprise resource planning (ERP), radio-frequency identification (RFID), machine learning, supply chain management (SCM), manufacturing execution system (MES), product lifestyle management (PLM), smart materials, computer-aided design and manufacturing (CAD/CAM), and statistical process control (SPC) (3).

The more of these are available the more possible will be smart production. Smart production will be possible in mills to the extent of having set up a substructure for collecting and analysing data, and to use that analysis for control purposes. The advanced the automation level, the less will be human intervention in production. Transition to autonomous systems is possible with full automation, and to decrease human factor to minimum or even near zero is possible with involvement of artificial intelligence (AI).

With a more practical approach, attention should be paid to whether machines which are the main elements of production are fed with data, and how they communicate with each other.

In mills, operation restricted to production according process flow and with its outline consists of sections such as raw material storage, intake and cleaning, dampening, milling, product storage and packaging. If we take milling section as an example from those, we see that main machine is the roller mill. Nowadays, most of the roller mills are or can be outfit with sensors for parameters such as motor load, main roll temperature, roll bearing temperature, vibration, main roll rotation, main roll position, timing belt temperature, feed roll rotation, air pressure, and levels (13).

If data obtained from sensors is sent to a central control system, and necessary adjustment can be done using the feedback from there, automation is provided. When we think that this is supplied for all units, and that there is data transaction between sections, we can recognize that smart production is possible for flour mills.

When it comes to obstacles, two different approaches have to be considered. With emphasis to a problem in technical and administrative terms, “absence of technical infrastructure, presence of cyber security risk, expected outcome not to be worth the cost of smart production investment” can be given as an example to the first one. Concerning psychological worries relevant to fear and expectations, “fear of being unable to carry through transition process, obligation of new workforce to be highly qualified after labour having been reduced, and apprehension of not being able to control production due its flexibility” can be given as example to the second.

We have to mention cyber security issue particularly as it includes a tangible worry. The smart factory can be exposed to threats or dangers due to connections and IIoT, but this should be thought as urgency to include security element into the system, and not be considered as a barrier.

If we have a look at milling sector distinctively, we will see that automation levels in most factories are not ready for Industry 4.0. Additionally, another problem is that dust isolation could yet not be provided in full.

Although both problems have been decreased in recently built factories, there are some question marks. Problems such as not having reached expected decrease in unit energy costs per production despite automation, and power cuts in different regions have not been solved yet (8). Furthermore, sector workforce has currently not the qualification required for the workforce of smart factories.

No matter what the situation is, there is no obstacle to build new flour mills as smart factories. Dust problem can be solved with electro-mechanical machinery, and auxiliary units of high quality, and electricity problem can be solved both in cooperating with electrical-electronics supplier and in using electrical-electronics precaution technology. Transition to smart factory will be also possible in current mills through technical development and digital transformation.

ROAD MAP FOR SMART PRODUCTION IN FLOUR MILLS Realization of smart production in flour mills is actually to put Industry 4.0 in practice with all its elements. First step is to decide. When you took decision, it means that you decided whether you want to be able to respond to market demands faster, to increase Overall Equipment Efficiency (OEE), and to reduce losses in parameters like energy, raw material and time (12).

In order to evaluate whether you need a transition as you have serial production, you can use the formula below proposed by respected manager Mr. Yavuz Çopur from automation industry:

After taking decision, you have to start with digital transformation, but you should not forget that a smart factory does not mean necessarily a “dark factory”. Human has still a role.

Transformation will be successfully executed if care is taken to these below (14):

• To see transformation as an opportunity • Guide and prepare the employees • Agility • To be user-centred • To show change ability

Success will be possible in preparing the infrastructure with starting a road map and determining needs and shortcomings, in reaching a level to carry out data analysis, and in starting with a partial exercise instead of starting completely at once.

References 1 Bartevyan, L; Industry 4.0-Summary report, DLG-Expert report 5/2015: DLG e.V., Frankfurt am Main, 2015 2 Scherf, B; Flexible Schichtplanung in der wandlungsfähigen Fabrik, IT & Production, Juli/August 2015 3 Mittal, S; Ahmad K, M; Romero, D; Wuest, T; Smart manufacturing: Characteristics, Technologies and enabling factors, Proc.IMechE Part B, Journal of Engineering Manufacture, Vol.233(5), 2019 4 Kesayak, Burak: Endüstri Tarihine Kısa bir Yolculuk, www.endustri40.com , Erişim: 24.04.2020 5 ST Otomasyon, “Veri işleme ve veri analitiğine konumlandık” Yavuz Çopur ile söyleşi, Nisan 2020. 6 Kottig, U; Der lange Weg zur Smart Factory, IT & Production, Juli/August 2015 7 Gültay, M.S; Un Fabrikalarında Endüstri 4.0 Kullanımı, Değirmenci Dergisi, Sayı 88, Nisan 2017 8 Treacy, F; Making the Move to Industry 4.0, 8.4.2020, www.machinedesign.com, Erişim: 17.04.2020 9 Rüssman, M; Lorenz, M; Gerbert, P; Waldner, M; Jusus, J; Engel, P; Harnisch, M; Industry 4.0, Boston Consulting Group, April 2015 10 Sosa, G; New technologies come to the milling industry, Miller Magazine, No.123, March 2020 11 Gezer, M; IoT ve IIoT nedir ve IIoT altyapısı nasıl oluşturulmalıdır?, www.trovarit.com , Erişim: 17.04.2020 12 Hoske, M.T; Industrial Internet of Things, Industry 4.0, Control Engineering, June 2015 13 Alfin, F; Artificial intelligent milling system, Miller Magazine, No.123, March 2020 14 Neugebauer, T; Wie gelingt die Transformation, IT & Production, Juli/August 2015