The acquisition ofdata and the development of different options in production system and factoryplanning requires up to 2/3rds of the total needed time resources. Thedigitization of production systems offers the possibility of automated dataacquisition. Nevertheless, approaches concerning fully automated dataacquisition systems are not widely spread among SME (small and medium sizedenterprises).  Furthermore, theadvantages of The Digital Twin are not sufficiently known due to the lack ofcompetence in SME concerning matters of Industry 4.

0. In order to transferknowledge about the benefits of digitalization, the development ofdemonstrating platforms is crucial. This article introduces a learning factorybased concept to demonstrate the potentials and advantages of real time dataacquisition and subsequent simulation based data processing. Primarily, this paperproposes methodology for implementation Learning factory based on Skoltech’smachining equipment .  The productioncell included industrial robot for part handling, loading and unloading, severalmilling and lathe machines with installed sensors.

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 All components had no connection between eachother and information from sensors didn’t bring any sense and use. Anautomation upgrade of the cell is proposed, involving Technomatix PlantSimulation tool, programmable logic controllers, RFID tags.   In this framework, the digital validation ofthe real manufacturing system is performed through Discrete Event Simulation toanalyze the performance of the manufacturing system in terms of productivityand utilization of resources under different alternative scenarios, avoidingthe risks associated with physical experimentation on the real system. Moreover,Digital twin approach increase a flexibility of the system  like Distributed planning, dynamicrescheduling, improved decision support, automatic planning and execution ofoffers/orders and wider the range of products.Finally, workingexample of Learning factory has been implemented at the Skoltech’s Masterskaya.

  It is empowered with several features such asDiscrete Event Clone gathers information from sensors, remote control ofmanufacturing execution, automatic rescheduling system, individual program ofmetal treatment or handling operations for each bar. The test has shown thatinstalled system is capable to execute more variety of assemblies with betterperformance compare to ordinary manufacturing system. The comparison betweenthe Digital Twin and common tools of process optimization, e.g. VSM, is carriedout and shows the benefits of digitalization in a vividly manner. Benefits ofthe proposed new approach for the analysis and modification of productionsystems can be experienced by participants in practical training sessions,especially continuous data acquisition, automated derivation of optimizationmeasures and capturing of motion data.

The physical implementation of thesystem enabling the Digital Twin based on Discrete event simulation is thefirst step to enter Industry 4.0 era. To increase components utilization of thesystem and enable It with scalability further researches should be performedIncluding optimization methods, machine learning, Genetic algorithm and etc.