Miller Magazine Issue: 125 May 2020

86 ARTICLE MILLER / MAY 2020 computation elements with physical components and pro- cesses. 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 enab- ling 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 Inter- net 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 availab- le. 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 wit- hout delay or disruption. It has to be considered that smart production is not even in Germany which suggested Industry 4.0 approach comp- letely 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 communica- tion 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 ma- nufacturing, 3D printing and additive manufacturing, smart sensors, smart product and part, data and big data analytics, predictive analytics, data visualization, simulation, forecas- ting, enterprise resource planning (ERP), radio-frequency identification (RFID), machine learning, supply chain ma- nagement (SCM), manufacturing execution system (MES), product lifecycle management (PLM), smart materials, com- puter-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 ad- vanced the automation level, the less will be human inter- vention 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 pro- duction are fed with data, and how they commu- nicate with each other. In mills, operation restricted to production according process flow and with its outline con- sists of sections such as raw material storage, intake and cleaning, dampening, milling, pro- duct 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 sen- sors for parameters such as motor load, main roll temperature, roll bearing temperature, vib- ration, 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. Figure 2: Technical Foundation of Industry 4.0 Source: www.machinedesign.com