The factories) is crucial. Primarily, this paper proposes

The Internet of things (IoT) is the network of physical devices, vehicles, homeappliances and other items embedded with electronics, software, sensors, actuators, and network connectivity which enables these objects to connect and exchange data. Nowadaysdeveloped information technologies like  Neural networks, cloud services ,VR, Big Data  combined with low prices for sensors andinternet access have already formed Industrial IOT. Undoubtedly, digitalizationis the main trend (Industry 4.0) for companies pretending to be leaders in anyhigh technological industry.

Nevertheless, theadvantages of The Digital Twin, complexity and high price for implementation areprimarily factors which inhibit spreading of Industry 4.0 approach (ThomasH.-J. Uhlemanna., 2017) . In order to transfer knowledge about thebenefits of digitalization, the development of demonstrating platforms (also calledlearning factories)  is crucial.

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Primarily,this paper proposes methodology for implementation Learning factory todemonstrate the potentials and advantages of real time data acquisition andsubsequent simulation based data processing.  The production cell included industrial robotfor part handling, loading and unloading, several milling and lathe machineswith installed sensors.  All components hadno connection between each other and information from sensors didn’t bring anysense and use. An automation upgrade of the cell is proposed, involving TechnomatixPlant Simulation tool, programmable logic controllers, RFID tags.   Thedigital twin is primarily formed by Discrete Event Simulation and ProcessSimulation to analyze the performance of the manufacturing system (RolandRosen., 2015) and observe current state of all components of the system at any time.

Moreover, Digital twin approach increase a flexibility of the system  like Distributed planning, dynamicrescheduling, improved decision support, individual program of metal treatment orhandling operations for each bar and wider the range of products.  The test has been  that installed system is capable to execute morevariety of assemblies with better performance compare to ordinary manufacturingsystem. The comparison between the Digital Twin and common tools of processoptimization, e.g.

VSM, is carried out and shows the benefits of digitalizationin a vividly manner. Benefits of the proposed new approach for the analysis andmodification of production systems can be experienced by participants inpractical training sessions, especially continuous data acquisition, automatedderivation of optimization measures and capturing of motion data. The physicalimplementation of the system enabling the Digital Twin based on Discrete eventsimulation is the first step to enter Industry 4.0 era. To increase components utilizationof the system and enable It with scalability further researches should beperformed Including optimization methods, machine learning, Genetic algorithmand etc.



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