- Email: [email protected]
Trends in Simulation and Planning of Manufacturing Companies
Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 149 (2016) 571 – 575
International Conference on Manufacturing Engineering and Materials, ICMEM 2016, 6-10 June 2016, Nový Smokovec, Slovakia
Trends in Simulation and Planning of Manufacturing Companies Branislav Bakoa,*, Pavol Božeka a
Slovak University of Technology, Faculty of Materials Science and Technology, Institute of Applied Informatics, Automation an d Mechatronics, J. Bottu 25, Trnava 91724, Slovakia
Abstract Increasing the efficiency of production planning is a very hot topic from the perspective of introducing lean production into manufacturing. Simulation study dealing with simulation application for production planning support is a fundament for enhancing production systems and reduction of bottleneck occurrences. The article describes the possibilities of using computer simulation during production scheduling. A developed simulation model is adapted for dynamic loading of production plans for a given time period. Based on the simulation output, it is possible to verify production process and conduct additional simulation experiments. Changes in simulation model inputs result in changes on simulation (production) outputs, these can be easily compared with outputs of the original versions of production plans due to their archiving. The aim was to develop a simulation model which, after consequent adapting, will be used for creation of production plans in the future. The created model is ready for swift loading of incoming data and their consecutive evaluation through simulations with subsequent imaging diagram and output statistics. The developed simulation model can be fully controlled via a GUI (Graphical User Interface) which is fully opened for implementation of further optimization and scheduling algorithm with the aim of future enhancement of the simulation model.The simulation was created in collaboration with INNOV8 Ltd. via Plants Simulation software. and insert your abstract by text.Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ©Click 2016here The Authors. Published © 2016 The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under of of thethe organizing committee of ICMEM 2016 2016 Peer-review underresponsibility responsibility organizing committee of ICMEM Keywords: simulation; optimization; production scheduling; Plant Simulation.
1. Introduction The priority of each company is to achieve profit. To achieve profit the efficient productivity or production are necessary. The efficient production means such a production where the machines or devices are utilised at their maximum while the idle time is minimised as well as the production time. Nevertheless, as the results of practice show, at present not every company is able to meet these requirements completely. Currently, the companies are oriented on meeting the clients’ requirements which calls for using many tools and methods necessarily utilized in production planning. Due to constantly growing client´s requirements, the companies utilise not only the plans prepared on the basis of standard capacity and statistical calculations but various systems such computer-aided planning. For planning needs also several systems have been were developed, e.g. MRP (Material Requirements Planning). The systems are focused on controlling the production supply using a simple production model where the transformation of inputs into outcomes is given by the continuous production time. For subsequent optimisation linear programming is utilised [1]. For the needs of production optimisation, the computer simulation is used more and more frequently. It can be used also used in developing and verifying the production plans.
* Corresponding author. Tel.: +421 906 068 423. E-mail address: [email protected]
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of ICMEM 2016
doi:10.1016/j.proeng.2016.06.707
572
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575
2. Simulation Simulation is the imitation of the system and its dynamic processes included in the model able to simulate the experiments in order to acquire knowledge applicable in real. In a discrete, event-oriented simulation the changes of model components´ states occur only in certain time periods, i.e. not continuously. Entering causes the change of model components´ states and controls the whole simulation. These events are carried out gradually – discretely. The advantage is represented by the fact that the time changes within the sequence of given events [2,3]. Due to these properties it is possible to execute dynamic monitoring within the simulation, where in contrast to static calculations through average values it is possible to monitor the given system behaviour in time. Suitably designed simulation model provides an amount of substantial information allowing thus executing the corrections in production planning. The following figure shows an example of filling the buffer in time, where due to dynamic monitoring it is possible to see critical values of the buffer.
Fig. 1. Development of buffer state.
The graphs with the percentage of machines, workforce or logistic operators’ exploitation or table reports with information on orders processed can provide further outcome information as well as Sankey diagram, or Gantt chart. In the process of the simulation model development it is necessary to carry out the verification of the model developed so that the user can trust the model. Fig. 2 illustrates the relationship of the computer simulation model and reality.
Fig. 2. Relationship of simulation and reality [3].
Currently, for the needs of computer simulation new programs trying to meet as many requirements and characteristics as possible are constantly developed, to mention just few of them available, e.g.: WITNESS, Plant Simulation, Simio, Automod, SIMUL8, ARENA, QUEST, etc. For the needs of a suitable simulation tool development that could be flexible in supporting the production planning, in cooperation with INNOV8 Company we chose Plant Simulation program made by Siemens. Its advantage was in the support of object oriented programming using SimTalk programming language which allowed developing of flexible methods to ensure correct model functions [4,5,6]. Each object within the simulation had many predefined attributes and methods which can be
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575 complemented and by which a complex simulation models with many details could be developed. The simulation model also allows generating of random events which causes a more flexible return to the original working plan. 3. Developing of a simulation tool for supporting the planning The subject matter was investigated in cooperation with INNOV8 Company which focuses on planning and optimising the processes via simulation. The cooperation was aimed at developing a simulation tool for the support of planning in the given company. After reading the prepared production plans for the following three weeks the tool carries out the simulation and in its end it generates Gantt chart showing the information on the production process on given workplaces, on idle time, as well as on the ability to execute the existing plan within the week given, etc. [7]. The next outcomes will be as follows: exploitation of inter-operational buffers, exploitation of workplaces, amount of production, and the state of stock as well as the alert on the consumption of purchased material in a specific time. The project implementation stages: 1. Analysis of processes and input data in the company. 2. Development of the simulation model. 3. Verification of the simulation model. 4. Adjustment of the simulation model to the simulation application allowing reading of input data (production plans, upgrade input data, material flow, bills of material, production time, etc.). First, it was necessary to carry out the process analysis and regarding its results the simulation model was developed. In the course of the analysis the material flow was identified and the simulation model boundaries were made where the primary operations of produced components were defined as the beginning of the production [8]. As last operations within the simulation the packaging lines were defined as the produced components finish here. An example of a packaging line developed in Plan Simulation program is shown in Fig. 3.
Fig. 3. Packaging line created in simulation program.
As soon as the last operation is accomplished, the ready products are placed in the dispatch store. By developing the simulation model logic it was necessary to prepare the structures of input data, such as bills of material, tables of operations time, material flows for individual components produced, tables with data defining the packaging regulations as well as palettes dimensions. To be able to upgrade the data in future, via Excel program the universal templates were developed. At the same time, the methods for correct upgrade of data were programmed in the simulation model. Similarly, the graphical user interface
573
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Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575
allowing the user to activate the individual functions and change the simulation parameters by simple pressing the buttons was also developed. During the simulation model development it was necessary to carry out many workshops where the details related to the simulation model functionality aimed at maximum accuracy were discussed. It was necessary to consider the division of materials, transports of products within the company, production´s degree of completion, inter-operational buffers, etc. Simultaneously, it was necessary to ensure correct setting of workplaces so that the production is executed according to defined production plans and accurate logic. The simulation developed was then verified. In the following step it was necessary to adjust the model for the needs of dynamic reading the production plans. The aim was to create the simulation application. Its function is the software support of production plans regarding the reading of current date in the given moment of the production process. The application graphically illustrates the residual production plan, bottlenecks, delays of production batches and unexploited machinery. Regarding the reading of current production state, the planner can adjust the operational plan so that the production time is shortened at its maximum. The other benefits are increased machine utilisation, faster supply of packaging parts, planning of machine utilisation by operators as well as preliminary identification of possible bottlenecks in the plans. The outcomes are represented by Gantt chart, tables made in simulation application as well as other graphical statistics. Before the adjustment is done, it is necessary to define the source for reading the current production plans. The simulation software supports connections to various database systems and due to programmed methods it allows using of C interface. Nevertheless, the Internal Regulations of the Company did not allowed access its information system, therefore, the templates were predefined for these purposes in Excel program so that the individual plans could be read into the simulation program. To ensure correct initialisation of the simulation model, the information on production in-process will be read as well, similarly as the current stock state. By reading the data it is possible to set any date and time of beginning the simulation, i.e. it provides the user by the possibility to test older plans or use a system date. The addition of work calendar functionality allows defining of season and bank holidays which can be subsequently considered. Within the workplaces also the shift calendars together with breaks and weekends could be defined [9,10]. The necessary functionality of the application was ensured via programming the methods required. After the simulation execution, Gantt chart is generated (Fig. 4). Via the plans read, the chart allows monitoring of the production on the workplaces given. In case of idle time due to waiting for input material that has to be processed in the previous operation, it is possible to carry out necessary corrections in the production plans made. Or, in such a case it is possible to plan the maintenance or utilise the workforce in other operations. The adjusted plans can be read again and subsequently a new simulation can be activated.
Fig. 4. Gantt Chart visualization of packaging process.
Next in the chart, there is also the information on the consumption of purchased materials which is shown in the chart as alerts on the time axis. The chart is fully interactive and after clicking on the individual sectors it can provide the information on what product or product part is produced at the time given as well as the number of order or production batch size and name of the previous operation. Idle time is illustrated in yellow and orange colours. In case the idle time is longer than two hours, the given sector is shown in red colour and the alert on the idle time is shown. The length of simulation and the chart shown is three weeks. Within the workplaces given it is possible to show the charts of outcomes of buffers development as well as percentage chart of the extent of workplaces´ utilization.
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575 To improve the application utilisation, the function of operation optimisation was added. When in the course of simulation the workplace has no input material at its disposal, it can skip the given operation and check the availability of material for the follow-on operation. When the material for the follow-on operation is available, it can carry out the production and repeatedly verify the availability of material for the operation skipped. When the material is still not available, the given process has to be repeated. These changes are illustrated in the chart in green colour. Table reports are next outcome showing detail information on production process on the given workplace, on beginning and end of manufacturing the given order, produced amount, possibility of re-planning the operation as well as on the consumption of input material. 4. Conclusion The utilization of simulation in supporting the planning has a significant potential as it allows reveal possible complication prior to the action providing thus the production planner with sufficient time to execute necessary corrections. Optimization algorithms automatically generate changes in production plans during the simulation run, which are based on the availability of input materials. According to set parameters, such as storage capacity, adjustments to individual plans can executed in situations, when the production line will not be able to make production, because of insufficient capacity of the output buffer. During this time period, staff of the assembly line won´t be taken into account and could be used for other operations, or maintenance of the assembly line could be scheduled. Monitoring the Gantt chart can be used to identify problematic batches or bottlenecks that can make an impact on delaying the delivery to the customer. These batches may be rescheduled to another date and then verify the accuracy of decisions. In future it is planned to continue with the development of the application designed and improve it by the possibility of optimized production plan preparation. Automated development will be carried regarding the production required in the week in question as well as the criteria defined and logic of planning. All these aspects will have to be analysed, programmed and considered in the next project part. Acknowledgements The contribution is sponsored and elaborated within the running Project of VEGA MŠ SR No. 1/0367/15 titled: Research and development of a new system of the robot trajectory autonomous control and KEGA MŠ SR No. 006STU-4/2015 Project University textbook „Means of automated production“ via interactive multimedia form for STU Bratislava and TU Košice. This publication is the result of implementation of the project: "UNIVERSITY SCIENTIFIC PARK: CAMPUS MTF STU CAMBO" (ITMS: 26220220179) supported by the Research & Development Operational Program funded by the EFRR. References Fedorčáková M, Šebo D. Logistic planning and production control. Trends in company control systems. TU Košice; 2008. p. 365-370. VDI 3633: Simulation of systems in materials handling, logistics and production - Fundamentals; 2013. Turygin Y, Fyedorov D. Analysis of schemes of workpiece gripping. 14th International Conference on Mechatronics. Trenčianske Teplice; 2011. Jerz V. Simulation and optimization of production systems. Bratislava: Slovak University of Technology Bratislava; 2008. p. 18. Dombrachev A, Korshunov A, Yakimovich B. Based on complexity theory the automated normalization system of tooling equipment. Avtomatizatsiya i Sovremennye Tekhnologii; 2004. p. 3-8. [6] Bangsow S. Manufacturing Simulation with Plant Simulation and SimTalk. Usage and Programming with Examples and solutions. Germany: Springer; 2010. [7] Bako B. Optimization of selected processes in Nemak Slovakia s. r. o. company by using simulation methods. Praha: DYNAMIC FUTURE s. r. o.; 2013. p. 41- 65. [8] Razzhivina M, Yakimovich B, Korshunov A. Application of information technologies and principles of lean production for efficiency improvement of machine building enterprises. Pollack Periodica; 2015. p. 17-23. [9] Božek P, Turygin Y. Measurement of the operating parameters and numerical analysis of the mechanical subsystem. Measurement Science Review, Slovak Academy of Sciences - Inst. Measurement Science; 2014. p. 198-203. [10] Tecnomatix Plant Simulation step-by-step help. Germany: Siemens Product Lifecycle Management Software Inc; 2011. [1] [2] [3] [4] [5]
575
ScienceDirect Procedia Engineering 149 (2016) 571 – 575
International Conference on Manufacturing Engineering and Materials, ICMEM 2016, 6-10 June 2016, Nový Smokovec, Slovakia
Trends in Simulation and Planning of Manufacturing Companies Branislav Bakoa,*, Pavol Božeka a
Slovak University of Technology, Faculty of Materials Science and Technology, Institute of Applied Informatics, Automation an d Mechatronics, J. Bottu 25, Trnava 91724, Slovakia
Abstract Increasing the efficiency of production planning is a very hot topic from the perspective of introducing lean production into manufacturing. Simulation study dealing with simulation application for production planning support is a fundament for enhancing production systems and reduction of bottleneck occurrences. The article describes the possibilities of using computer simulation during production scheduling. A developed simulation model is adapted for dynamic loading of production plans for a given time period. Based on the simulation output, it is possible to verify production process and conduct additional simulation experiments. Changes in simulation model inputs result in changes on simulation (production) outputs, these can be easily compared with outputs of the original versions of production plans due to their archiving. The aim was to develop a simulation model which, after consequent adapting, will be used for creation of production plans in the future. The created model is ready for swift loading of incoming data and their consecutive evaluation through simulations with subsequent imaging diagram and output statistics. The developed simulation model can be fully controlled via a GUI (Graphical User Interface) which is fully opened for implementation of further optimization and scheduling algorithm with the aim of future enhancement of the simulation model.The simulation was created in collaboration with INNOV8 Ltd. via Plants Simulation software. and insert your abstract by text.Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ©Click 2016here The Authors. Published © 2016 The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under of of thethe organizing committee of ICMEM 2016 2016 Peer-review underresponsibility responsibility organizing committee of ICMEM Keywords: simulation; optimization; production scheduling; Plant Simulation.
1. Introduction The priority of each company is to achieve profit. To achieve profit the efficient productivity or production are necessary. The efficient production means such a production where the machines or devices are utilised at their maximum while the idle time is minimised as well as the production time. Nevertheless, as the results of practice show, at present not every company is able to meet these requirements completely. Currently, the companies are oriented on meeting the clients’ requirements which calls for using many tools and methods necessarily utilized in production planning. Due to constantly growing client´s requirements, the companies utilise not only the plans prepared on the basis of standard capacity and statistical calculations but various systems such computer-aided planning. For planning needs also several systems have been were developed, e.g. MRP (Material Requirements Planning). The systems are focused on controlling the production supply using a simple production model where the transformation of inputs into outcomes is given by the continuous production time. For subsequent optimisation linear programming is utilised [1]. For the needs of production optimisation, the computer simulation is used more and more frequently. It can be used also used in developing and verifying the production plans.
* Corresponding author. Tel.: +421 906 068 423. E-mail address: [email protected]
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of ICMEM 2016
doi:10.1016/j.proeng.2016.06.707
572
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575
2. Simulation Simulation is the imitation of the system and its dynamic processes included in the model able to simulate the experiments in order to acquire knowledge applicable in real. In a discrete, event-oriented simulation the changes of model components´ states occur only in certain time periods, i.e. not continuously. Entering causes the change of model components´ states and controls the whole simulation. These events are carried out gradually – discretely. The advantage is represented by the fact that the time changes within the sequence of given events [2,3]. Due to these properties it is possible to execute dynamic monitoring within the simulation, where in contrast to static calculations through average values it is possible to monitor the given system behaviour in time. Suitably designed simulation model provides an amount of substantial information allowing thus executing the corrections in production planning. The following figure shows an example of filling the buffer in time, where due to dynamic monitoring it is possible to see critical values of the buffer.
Fig. 1. Development of buffer state.
The graphs with the percentage of machines, workforce or logistic operators’ exploitation or table reports with information on orders processed can provide further outcome information as well as Sankey diagram, or Gantt chart. In the process of the simulation model development it is necessary to carry out the verification of the model developed so that the user can trust the model. Fig. 2 illustrates the relationship of the computer simulation model and reality.
Fig. 2. Relationship of simulation and reality [3].
Currently, for the needs of computer simulation new programs trying to meet as many requirements and characteristics as possible are constantly developed, to mention just few of them available, e.g.: WITNESS, Plant Simulation, Simio, Automod, SIMUL8, ARENA, QUEST, etc. For the needs of a suitable simulation tool development that could be flexible in supporting the production planning, in cooperation with INNOV8 Company we chose Plant Simulation program made by Siemens. Its advantage was in the support of object oriented programming using SimTalk programming language which allowed developing of flexible methods to ensure correct model functions [4,5,6]. Each object within the simulation had many predefined attributes and methods which can be
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575 complemented and by which a complex simulation models with many details could be developed. The simulation model also allows generating of random events which causes a more flexible return to the original working plan. 3. Developing of a simulation tool for supporting the planning The subject matter was investigated in cooperation with INNOV8 Company which focuses on planning and optimising the processes via simulation. The cooperation was aimed at developing a simulation tool for the support of planning in the given company. After reading the prepared production plans for the following three weeks the tool carries out the simulation and in its end it generates Gantt chart showing the information on the production process on given workplaces, on idle time, as well as on the ability to execute the existing plan within the week given, etc. [7]. The next outcomes will be as follows: exploitation of inter-operational buffers, exploitation of workplaces, amount of production, and the state of stock as well as the alert on the consumption of purchased material in a specific time. The project implementation stages: 1. Analysis of processes and input data in the company. 2. Development of the simulation model. 3. Verification of the simulation model. 4. Adjustment of the simulation model to the simulation application allowing reading of input data (production plans, upgrade input data, material flow, bills of material, production time, etc.). First, it was necessary to carry out the process analysis and regarding its results the simulation model was developed. In the course of the analysis the material flow was identified and the simulation model boundaries were made where the primary operations of produced components were defined as the beginning of the production [8]. As last operations within the simulation the packaging lines were defined as the produced components finish here. An example of a packaging line developed in Plan Simulation program is shown in Fig. 3.
Fig. 3. Packaging line created in simulation program.
As soon as the last operation is accomplished, the ready products are placed in the dispatch store. By developing the simulation model logic it was necessary to prepare the structures of input data, such as bills of material, tables of operations time, material flows for individual components produced, tables with data defining the packaging regulations as well as palettes dimensions. To be able to upgrade the data in future, via Excel program the universal templates were developed. At the same time, the methods for correct upgrade of data were programmed in the simulation model. Similarly, the graphical user interface
573
574
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575
allowing the user to activate the individual functions and change the simulation parameters by simple pressing the buttons was also developed. During the simulation model development it was necessary to carry out many workshops where the details related to the simulation model functionality aimed at maximum accuracy were discussed. It was necessary to consider the division of materials, transports of products within the company, production´s degree of completion, inter-operational buffers, etc. Simultaneously, it was necessary to ensure correct setting of workplaces so that the production is executed according to defined production plans and accurate logic. The simulation developed was then verified. In the following step it was necessary to adjust the model for the needs of dynamic reading the production plans. The aim was to create the simulation application. Its function is the software support of production plans regarding the reading of current date in the given moment of the production process. The application graphically illustrates the residual production plan, bottlenecks, delays of production batches and unexploited machinery. Regarding the reading of current production state, the planner can adjust the operational plan so that the production time is shortened at its maximum. The other benefits are increased machine utilisation, faster supply of packaging parts, planning of machine utilisation by operators as well as preliminary identification of possible bottlenecks in the plans. The outcomes are represented by Gantt chart, tables made in simulation application as well as other graphical statistics. Before the adjustment is done, it is necessary to define the source for reading the current production plans. The simulation software supports connections to various database systems and due to programmed methods it allows using of C interface. Nevertheless, the Internal Regulations of the Company did not allowed access its information system, therefore, the templates were predefined for these purposes in Excel program so that the individual plans could be read into the simulation program. To ensure correct initialisation of the simulation model, the information on production in-process will be read as well, similarly as the current stock state. By reading the data it is possible to set any date and time of beginning the simulation, i.e. it provides the user by the possibility to test older plans or use a system date. The addition of work calendar functionality allows defining of season and bank holidays which can be subsequently considered. Within the workplaces also the shift calendars together with breaks and weekends could be defined [9,10]. The necessary functionality of the application was ensured via programming the methods required. After the simulation execution, Gantt chart is generated (Fig. 4). Via the plans read, the chart allows monitoring of the production on the workplaces given. In case of idle time due to waiting for input material that has to be processed in the previous operation, it is possible to carry out necessary corrections in the production plans made. Or, in such a case it is possible to plan the maintenance or utilise the workforce in other operations. The adjusted plans can be read again and subsequently a new simulation can be activated.
Fig. 4. Gantt Chart visualization of packaging process.
Next in the chart, there is also the information on the consumption of purchased materials which is shown in the chart as alerts on the time axis. The chart is fully interactive and after clicking on the individual sectors it can provide the information on what product or product part is produced at the time given as well as the number of order or production batch size and name of the previous operation. Idle time is illustrated in yellow and orange colours. In case the idle time is longer than two hours, the given sector is shown in red colour and the alert on the idle time is shown. The length of simulation and the chart shown is three weeks. Within the workplaces given it is possible to show the charts of outcomes of buffers development as well as percentage chart of the extent of workplaces´ utilization.
Branislav Bako and Pavol Božek / Procedia Engineering 149 (2016) 571 – 575 To improve the application utilisation, the function of operation optimisation was added. When in the course of simulation the workplace has no input material at its disposal, it can skip the given operation and check the availability of material for the follow-on operation. When the material for the follow-on operation is available, it can carry out the production and repeatedly verify the availability of material for the operation skipped. When the material is still not available, the given process has to be repeated. These changes are illustrated in the chart in green colour. Table reports are next outcome showing detail information on production process on the given workplace, on beginning and end of manufacturing the given order, produced amount, possibility of re-planning the operation as well as on the consumption of input material. 4. Conclusion The utilization of simulation in supporting the planning has a significant potential as it allows reveal possible complication prior to the action providing thus the production planner with sufficient time to execute necessary corrections. Optimization algorithms automatically generate changes in production plans during the simulation run, which are based on the availability of input materials. According to set parameters, such as storage capacity, adjustments to individual plans can executed in situations, when the production line will not be able to make production, because of insufficient capacity of the output buffer. During this time period, staff of the assembly line won´t be taken into account and could be used for other operations, or maintenance of the assembly line could be scheduled. Monitoring the Gantt chart can be used to identify problematic batches or bottlenecks that can make an impact on delaying the delivery to the customer. These batches may be rescheduled to another date and then verify the accuracy of decisions. In future it is planned to continue with the development of the application designed and improve it by the possibility of optimized production plan preparation. Automated development will be carried regarding the production required in the week in question as well as the criteria defined and logic of planning. All these aspects will have to be analysed, programmed and considered in the next project part. Acknowledgements The contribution is sponsored and elaborated within the running Project of VEGA MŠ SR No. 1/0367/15 titled: Research and development of a new system of the robot trajectory autonomous control and KEGA MŠ SR No. 006STU-4/2015 Project University textbook „Means of automated production“ via interactive multimedia form for STU Bratislava and TU Košice. This publication is the result of implementation of the project: "UNIVERSITY SCIENTIFIC PARK: CAMPUS MTF STU CAMBO" (ITMS: 26220220179) supported by the Research & Development Operational Program funded by the EFRR. References Fedorčáková M, Šebo D. Logistic planning and production control. Trends in company control systems. TU Košice; 2008. p. 365-370. VDI 3633: Simulation of systems in materials handling, logistics and production - Fundamentals; 2013. Turygin Y, Fyedorov D. Analysis of schemes of workpiece gripping. 14th International Conference on Mechatronics. Trenčianske Teplice; 2011. Jerz V. Simulation and optimization of production systems. Bratislava: Slovak University of Technology Bratislava; 2008. p. 18. Dombrachev A, Korshunov A, Yakimovich B. Based on complexity theory the automated normalization system of tooling equipment. Avtomatizatsiya i Sovremennye Tekhnologii; 2004. p. 3-8. [6] Bangsow S. Manufacturing Simulation with Plant Simulation and SimTalk. Usage and Programming with Examples and solutions. Germany: Springer; 2010. [7] Bako B. Optimization of selected processes in Nemak Slovakia s. r. o. company by using simulation methods. Praha: DYNAMIC FUTURE s. r. o.; 2013. p. 41- 65. [8] Razzhivina M, Yakimovich B, Korshunov A. Application of information technologies and principles of lean production for efficiency improvement of machine building enterprises. Pollack Periodica; 2015. p. 17-23. [9] Božek P, Turygin Y. Measurement of the operating parameters and numerical analysis of the mechanical subsystem. Measurement Science Review, Slovak Academy of Sciences - Inst. Measurement Science; 2014. p. 198-203. [10] Tecnomatix Plant Simulation step-by-step help. Germany: Siemens Product Lifecycle Management Software Inc; 2011. [1] [2] [3] [4] [5]
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