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Modeling of the two shuttle box system within the internal logistics system using simulation software

  • David Strnad , Gabriel Fedorko EMAIL logo and Patrik Ščavnický
Published/Copyright: September 13, 2021
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Open Engineering
From the journal Open Engineering Volume 11 Issue 1

Abstract

The efficiency and effectiveness of the production system are influenced by the logistical arrangement of material flows. The smooth production, especially for assembly lines in the required quantity and at the required time (JIT or JIS systems), is currently ensured by automatically controlled towing sets (logistics trains), which consist of a tractor and several trucks. Another factor that affects the smooth production of assembly lines is the system of controlling the circulation of transport units. The number of transport units used in combination with the transport system significantly affects the efficiency of assembly workplaces. This article presents an analysis of the supply of assembly workplaces using a system of two shuttle boxes. The aim of this article is to investigate the influence of transport speed and capacity on the smoothness of the assembly process. Within the described analysis, the transport of 50,000 components is analyzed using a simulation model, while the length of the transport route is 32 km and 65 transport units per shift are used.

Keywords: material flow; smooth production; assembly workplace; AGV; analysis

1 Introduction

When dealing with horizontal material transport in a number of industries within internal logistics, it currently seems to be the most advantageous to use towing sets with or without a driver [1]. Logistics trains, compared to originally used forklifts or hand trucks, offer a number of advantages, especially in the field of production logistics and shipping [2]. They work in a smaller space and thus provide more space for production [3]. The use of logistics trains has increased several times the quality and efficiency of supply not only by production lines but also by assembly lines [4].

Gazda and Osieczko [5] defined logistics trains as automatically guided handling equipment, which currently represents the highest degree of automation in the field of material handling. It is a technology that allows you to automatically pick up and transport cargo to its destination.

It deals in detail with automated Ullrich tractors [6]. It describes the development of tractors from the original demand of the carmaker in the mid-1950s of the 20th century for the delivery of an automatically controlled train, through the various development stages, which have always been influenced by the possibilities of automated technologies used, to the present. It also deals with their construction, safety elements and perspectives of their use.

Logistics trains are very often used in the automotive industry [7]. Hercko et al. dealt with the applications of automated tractors and logistics trains, especially in the automotive industry in the supply of production and assembly lines [8]. Yang and Pan [9] stated that the use of automated towing sets increases the efficiency of assembly line supply and reduces inventory. Neradilová described, in her work, automated horizontal transport in internal logistics with a focus mainly on the management and optimization of supply lines using simulations and modeling [10]. Using computer simulation, it is possible to verify the proposed logistics systems, including negative production, handling and transport effects, and thus, prevent possible unexpected problems [11].

The type and number of transport units used are also important for the efficient operation of autonomous logistics systems [12]. As part of the article, an analysis of the supply process will be performed using a simulation model in the Tecnomatix Plant Simulation program, which is based on the circulation of two transport units for one assembly workplace. The aim of the paper is to present the way in which it is possible to model the two shuttle box systems for the needs of logistics process analysis. This article describes the creation of the method using the SimTalk language that simulates the process regardless of the extent of transport routes and the number of transported items.

2 Methods

The Industry 4.0 concept has given rise to various applications of specific innovative solutions in all industries. Therefore, there is a relatively rapid improvement of common procedures and technologies, modernization of production means with the use of automation elements and the transition to robotic nodes and automatic lines. There is gradual digitization of all systems, including documentation.

Increased interest in automation is also due to the situation in the labor market in connection with labor shortages. Automation is thus not only focused on the production and technological systems but also, at the same time, the related logistics processes are also automated. The application of automated logistics systems is evident especially in the automotive industry, which is traditionally a pioneer of most innovative solutions that increase efficiency and effectiveness, especially in logistics activities.

One of the areas that is suitable for the automation of logistics activities is the area of material handling. It is mainly the warehouse management and supply of materials to both production and assembly lines with the use of automatic means of transport.

Automatic trucks advantageously replace the originally used conveyor lines or forklift trucks. They are more flexible when the route needs to be changed and take up less space when handling (Figure 1).

Figure 1 Example of an automatic truck used in internal logistics [13,14].
Figure 1

Example of an automatic truck used in internal logistics [13,14].

They move according to marks, magnetic tapes, inductions from wires placed in the floor, laser or gyroscope. AGVs facilitate material handling and, through their independence from the operator, facilitate material handling, increase the efficiency and safety of operation in their area of use and significantly reduce logistics costs. These are the main reasons for the use of AGV vehicles in various industries, which usually require specific design solutions.

Automatically controlled handling equipment currently represents the highest level in the field of material handling together with robots. It is a technology that allows one to automatically pick up and transport material to its destination. AGV vehicles often replace commonly used vehicles such as forklifts or pallet trucks.

AGV forklifts and pallet trucks are preferably used in logistics centers and wherever higher capacities are required. Automatically controlled forklifts are designed as multi-purpose vehicles that work completely automatically with pallets or mesh box pallets. It automatically places the pallet or mesh box pallet on the fork and transports it to the destination, which is usually the racking system. It automatically searches for free space and stores the cargo. Automatically, the automatic forklifts are able to find the pallet or mesh box pallet in the racking system and transport it for further use.

The development is moving from the used automatic tractors (AGV) to a higher degree of automation. There are already automatic robotic trucks, which decide for themselves in front of an obstacle, whether they go around it on another route or stop, pick up an empty crate on the way back to the warehouse, recharge the battery themselves, etc. A higher degree of automation is also the ability to decide whether to continue back to the warehouse after loading to the assembly line or to return to the warehouse for further recall based on the received radio signal or to pass this received radio signal to another robotic truck that is closer to the warehouse. Robotic trucks with a higher degree of control and navigation form the category of autonomous intelligent vehicles.

2.1 Two shuttle box system

The two shuttle box system is based, as the name suggests, on the use of two transport units. One transport unit is used to remove components and the other transport unit is used to deliver other components. When the components from the first box are consumed, the second box with the other components must be transported by then. This one will then be further used. Otherwise, production will be interrupted, which is undesirable and unacceptable in many production systems. In the analysis of this system, we can effectively use computer modeling and simulation.

Modeling and computer simulation allow each other to predict the behavior of systems under various alternative changes in conditions and specified criteria. The simulation model is used to analyze an existing or proposed system and its behavior in various situations. Using computer simulation, the internal transport system as a whole can be analyzed.

2.2 Methodology of the research

The research idea of the presented article was realized according to the block diagram (Figure 2). Its overall concept was chosen so that the obtained results could be used for the analysis not only for a specific process but also for the general application.

Figure 2 Block diagram of the research idea.
Figure 2

Block diagram of the research idea.

3 Results

The two shuttle box system can be implemented using automatically controlled handling equipment. However, for its proper functioning, the entire system must be set appropriately in terms of individual operating parameters. When searching for parameters for its setting, it is advisable to use analysis using the method of computer simulation.

The procedure of such an analysis can be demonstrated by the example of using computer simulation for the analysis of replenishment of semi-finished products by individual CNC machines of the production line, which takes place completely automatically by a robotic AGV forklift controlled by sensors using IoT technology. The AGV truck transports 65 crates per shift, which is approx. 50,000 parts. The truck moves at a speed of 1.38888 m/s and travels a distance of 32 km (Figure 2).

The Tecnomatix Plant Simulation program was used to analyze the activity of replenishing the required components with a robotic AGV truck based on the orders of individual CNC machines.

The basic concept of the simulation model is based on the block diagram, as shown in Figure 3. The simulation of two boxes starts in the initial phase (red box) when one box (1) and the corresponding number of components are generated (2). Subsequently, in point 3, a shuttle box is loaded with a load of components, which operator 4 uses for production in process 5. The result is an empty crate 6 and a certain number of final products (7). Meanwhile, in the second phase (green box), a second shuttle bow with components (9) is generated that must be transported by AGV (8) to the operator (4) until the first shuttle box is finished. With the help of this condition, the production will continue without interruption and AGV (8) then transports the empty shuttle box for completing to the position (9).

Figure 3 Block diagram of the two shuttle boxes mode when using a robotic trolley.
Figure 3

Block diagram of the two shuttle boxes mode when using a robotic trolley.

Based on this, a supply process was created for each assembly workplace, which is shown in Figure 4. This submodel consists of six basic areas that provide subprocesses within the simulation model.

  1. The generation of handling units is provided by the “Source” block, which will create the necessary handling unit for further operations.

  2. The buffer (“Buffer” block) serves as a parking space until a new task is assigned to the relevant entity.

  3. The pallets are loaded onto the truck in the “AssemblyStation” block, where the lower-order handling units are stored on the higher-order handling unit, as long as the capacity of the handling unit on which the pallets are loaded is available or filled.

  4. The “Station” block is the time utilization of the handling unit in performing the required activity (moving from one station to another).

  5. Unloading of pallets from the truck is performed in the “DismantleStation” block, where lower-order handling units are taken from the higher-order handling unit and then taken in a different direction than the higher-order handling unit.

  6. The end block in this block diagram is the “Drain” block, which terminates the request operation with the handling unit.

Figure 4 Demonstration of part of the supply process model.
Figure 4

Demonstration of part of the supply process model.

The Tecnomatix Plant Simulation program has the Transporter function for transporting entities along the transport route (Figure 5), which represents a third-order handling unit. This unit can carry a number of second- or first-order handling units.

Figure 5 Manipulation unit in the simulation program Tecnomatix Plant Simulation.
Figure 5

Manipulation unit in the simulation program Tecnomatix Plant Simulation.

Using the Method function (Figure 6), various conditions and configurations can be set within the modeling. With this function, various changes can be made to selected routes or objects within the modeling and simulation, compared and evaluated.

Figure 6 Method function in the simulation program.
Figure 6

Method function in the simulation program.

The advantage of the software application of the simulation program Tecnomatix Plant Simulation is the possibility of displaying the model in 3-D design, which allows easier orientation (Figure 7).

Figure 7 The basic model in 3-D view.
Figure 7

The basic model in 3-D view.

3.1 Evaluation of modeling and simulation results

The initial situation assumes the use of one robotic AGV truck with one crate to replenish the components of the assembly line equipped with CNC machines. The obtained histogram shows the percentage of work performed on individual workplaces of assembly lines (Figure 8).

Figure 8 Histogram when supplying the line with one robotic AGV truck.
Figure 8

Histogram when supplying the line with one robotic AGV truck.

The histogram shows relatively large differences in the performance of individual machines, the causes of which may be different and are not the subject of this study. Using modeling and simulation, we adjusted the input data using two robotic AGV trucks.

The use of individual workplaces of assembly lines resulted in an improvement, which improved the efficiency of most workplaces but the workplaces remained almost unused (Figure 9).

Figure 9 Histogram when supplying the line with two robotic AGV trucks.
Figure 9

Histogram when supplying the line with two robotic AGV trucks.

We obtained the best efficiency in the use of production lines with CNC machines by increasing the transport speed of one robotic AGV truck (Figure 10).

Figure 10 Histogram when supplying the line with one robotic AGV truck but at a higher travel speed.
Figure 10

Histogram when supplying the line with one robotic AGV truck but at a higher travel speed.

This solution brought an improvement in the course of assembly processes, with the exception of three workplaces. This is a significant change from previous experiments. This finding points to the assumption that a possible further increase in speed can also eliminate this problem. However, local conditions must be taken into account in this consideration, in particular, whether it will allow the AGV vehicle to operate at a given speed. In the event that this is not possible, it is necessary to analyze the service processes and increase their efficiency by increasing the efficiency of the entire assembly process.

4 Conclusions

The effort to increase the efficiency of logistics processes, improve their productivity and replace the often missing workforce usually begins with their optimization, which currently continues with the digitization of production and logistics processes. In particular, repetitive strenuous activities with low added value are being replaced by AGV-type technologies and other technologies that facilitate and minimize human labor. Gradually, logistics takes place from data collection and analysis to its autonomous management.

Currently used autonomous systems use a combination of depth cameras and lasers, which capture the space around robotic trucks and create a spatial map in the control system for subsequent navigation.

Autonomous robotic vehicles are able not only to transport goods but also ensure their loading and unloading, which increases the efficiency of the whole process. Flexibility is increased by intelligent management connected to the ordering system.

At the end of the article, a study of modeling and simulation is described when supplying an assembly line equipped with a CNC machine using one robotic AGV truck, then two trucks and the third simulation is one truck at an increased travel speed, which was the most efficient. It is clear from the results of the analysis that even a small change in one of the operating parameters can significantly affect the efficiency of the entire logistics process.

The results of the research pointed to the fact that the transport speed of the AGV system significantly affects the ability of a sufficient supply of workplaces so that they do not fail due to a lack of components. The results of the simulation experiments present the fact that by application of the system of “two shuttle boxes” not only the number of used vehicles is important but also the appropriately chosen speed of their operation. At the same time, the results of the research are the presented methodology, which will allow one to determine suitable operating conditions using a simulation model and also the design of the model “two shuttle box system” in combination with the appropriate sequence in the program SimTalk. The proposed methodology and a way of modeling for the system of “two shuttle boxes” have universal validity and according to the analytical models of supply logistics of various production processes can be created.

Acknowledgments

This work is a part of the projects VEGA 1/0600/20, KEGA 012TUKE-4/2019 and APVV SK-SRB-18-0053.

  1. Conflict of interest: Authors state no conflict of interest.

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Received: 2021-06-10
Revised: 2021-07-23
Accepted: 2021-08-02
Published Online: 2021-09-13

© 2021 David Strnad et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/eng-2021-0090
Keywords for this article
material flow; smooth production; assembly workplace; AGV; analysis
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  24. A SIMULINK implementation of a vector shift relay with distributed synchronous generator for engineering classes
  25. Evaluation of measurement uncertainty in a static tensile test
  26. Errors in documenting the subsoil and their impact on the investment implementation: Case study
  27. Comparison between two calculation methods for designing a stand-alone PV system according to Mosul city basemap
  28. Reduction of transport-related air pollution. A case study based on the impact of the COVID-19 pandemic on the level of NOx emissions in the city of Krakow
  29. Driver intervention performance assessment as a key aspect of L3–L4 automated vehicles deployment
  30. A new method for solving quadratic fractional programming problem in neutrosophic environment
  31. Effect of fish scales on fabrication of polyester composite material reinforcements
  32. Impact of the operation of LNG trucks on the environment
  33. The effectiveness of the AEB system in the context of the safety of vulnerable road users
  34. Errors in controlling cars cause tragic accidents involving motorcyclists
  35. Deformation of designed steel plates: An optimisation of the side hull structure using the finite element approach
  36. Thermal-strength analysis of a cross-flow heat exchanger and its design improvement
  37. Effect of thermal collector configuration on the photovoltaic heat transfer performance with 3D CFD modeling
  38. Experimental identification of the subjective reception of external stimuli during wheelchair driving
  39. Failure analysis of motorcycle shock breakers
  40. Experimental analysis of nonlinear characteristics of absorbers with wire rope isolators
  41. Experimental tests of the antiresonance vibratory mill of a sectional movement trajectory
  42. Experimental and theoretical investigation of CVT rubber belt vibrations
  43. Is the cubic parabola really the best railway transition curve?
  44. Transport properties of the new vibratory conveyor at operations in the resonance zone
  45. Assessment of resistance to permanent deformations of asphalt mixes of low air void content
  46. COVID-19 lockdown impact on CERN seismic station ambient noise levels
  47. Review Articles
  48. FMEA method in operational reliability of forest harvesters
  49. Examination of preferences in the field of mobility of the city of Pila in terms of services provided by the Municipal Transport Company in Pila
  50. Enhancement stability and color fastness of natural dye: A review
  51. Special Issue: ICE-SEAM 2019 - Part II
  52. Lane Departure Warning Estimation Using Yaw Acceleration
  53. Analysis of EMG Signals during Stance and Swing Phases for Controlling Magnetorheological Brake applications
  54. Sensor Number Optimization Using Neural Network for Ankle Foot Orthosis Equipped with Magnetorheological Brake
  55. Special Issue: Recent Advances in Civil Engineering - Part II
  56. Comparison of STM’s reliability system on the example of selected element
  57. Technical analysis of the renovation works of the wooden palace floors
  58. Special Issue: TRANSPORT 2020
  59. Simulation assessment of the half-power bandwidth method in testing shock absorbers
  60. Predictive analysis of the impact of the time of day on road accidents in Poland
  61. User’s determination of a proper method for quantifying fuel consumption of a passenger car with compression ignition engine in specific operation conditions
  62. Analysis and assessment of defectiveness of regulations for the yellow signal at the intersection
  63. Streamlining possibility of transport-supply logistics when using chosen Operations Research techniques
  64. Permissible distance – safety system of vehicles in use
  65. Study of the population in terms of knowledge about the distance between vehicles in motion
  66. UAVs in rail damage image diagnostics supported by deep-learning networks
  67. Exhaust emissions of buses LNG and Diesel in RDE tests
  68. Measurements of urban traffic parameters before and after road reconstruction
  69. The use of deep recurrent neural networks to predict performance of photovoltaic system for charging electric vehicles
  70. Analysis of dangers in the operation of city buses at the intersections
  71. Psychological factors of the transfer of control in an automated vehicle
  72. Testing and evaluation of cold-start emissions from a gasoline engine in RDE test at two different ambient temperatures
  73. Age and experience in driving a vehicle and psychomotor skills in the context of automation
  74. Consumption of gasoline in vehicles equipped with an LPG retrofit system in real driving conditions
  75. Laboratory studies of the influence of the working position of the passenger vehicle air suspension on the vibration comfort of children transported in the child restraint system
  76. Route optimization for city cleaning vehicle
  77. Efficiency of electric vehicle interior heating systems at low ambient temperatures
  78. Model-based imputation of sound level data at thoroughfare using computational intelligence
  79. Research on the combustion process in the Fiat 1.3 Multijet engine fueled with rapeseed methyl esters
  80. Overview of the method and state of hydrogenization of road transport in the world and the resulting development prospects in Poland
  81. Tribological characteristics of polymer materials used for slide bearings
  82. Car reliability analysis based on periodic technical tests
  83. Special Issue: Terotechnology 2019 - Part II
  84. DOE Application for Analysis of Tribological Properties of the Al2O3/IF-WS2 Surface Layers
  85. The effect of the impurities spaces on the quality of structural steel working at variable loads
  86. Prediction of the parameters and the hot open die elongation forging process on an 80 MN hydraulic press
  87. Special Issue: AEVEC 2020
  88. Vocational Student's Attitude and Response Towards Experiential Learning in Mechanical Engineering
  89. Virtual Laboratory to Support a Practical Learning of Micro Power Generation in Indonesian Vocational High Schools
  90. The impacts of mediating the work environment on the mode choice in work trips
  91. Utilization of K-nearest neighbor algorithm for classification of white blood cells in AML M4, M5, and M7
  92. Car braking effectiveness after adaptation for drivers with motor dysfunctions
  93. Case study: Vocational student’s knowledge and awareness level toward renewable energy in Indonesia
  94. Contribution of collaborative skill toward construction drawing skill for developing vocational course
  95. Special Issue: Annual Engineering and Vocational Education Conference - Part II
  96. Vocational teachers’ perspective toward Technological Pedagogical Vocational Knowledge
  97. Special Issue: ICIMECE 2020 - Part I
  98. Profile of system and product certification as quality infrastructure in Indonesia
  99. Prediction Model of Magnetorheological (MR) Fluid Damper Hysteresis Loop using Extreme Learning Machine Algorithm
  100. A review on the fused deposition modeling (FDM) 3D printing: Filament processing, materials, and printing parameters
  101. Facile rheological route method for LiFePO4/C cathode material production
  102. Mosque design strategy for energy and water saving
  103. Epoxy resins thermosetting for mechanical engineering
  104. Estimating the potential of wind energy resources using Weibull parameters: A case study of the coastline region of Dar es Salaam, Tanzania
  105. Special Issue: CIRMARE 2020
  106. New trends in visual inspection of buildings and structures: Study for the use of drones
  107. Special Issue: ISERT 2021
  108. Alleviate the contending issues in network operating system courses: Psychomotor and troubleshooting skill development with Raspberry Pi
  109. Special Issue: Actual Trends in Logistics and Industrial Engineering - Part II
  110. The Physical Internet: A means towards achieving global logistics sustainability
  111. Special Issue: Modern Scientific Problems in Civil Engineering - Part I
  112. Construction work cost and duration analysis with the use of agent-based modelling and simulation
  113. Corrosion rate measurement for steel sheets of a fuel tank shell being in service
  114. The influence of external environment on workers on scaffolding illustrated by UTCI
  115. Allocation of risk factors for geodetic tasks in construction schedules
  116. Pedestrian fatality risk as a function of tram impact speed
  117. Technological and organizational problems in the construction of the radiation shielding concrete and suggestions to solve: A case study
  118. Finite element analysis of train speed effect on dynamic response of steel bridge
  119. New approach to analysis of railway track dynamics – Rail head vibrations
  120. Special Issue: Trends in Logistics and Production for the 21st Century - Part I
  121. Design of production lines and logistic flows in production
  122. The planning process of transport tasks for autonomous vans
  123. Modeling of the two shuttle box system within the internal logistics system using simulation software
  124. Implementation of the logistics train in the intralogistics system: A case study
  125. Assessment of investment in electric buses: A case study of a public transport company
  126. Assessment of a robot base production using CAM programming for the FANUC control system
  127. Proposal for the flow of material and adjustments to the storage system of an external service provider
  128. The use of numerical analysis of the injection process to select the material for the injection molding
  129. Economic aspect of combined transport
  130. Solution of a production process with the application of simulation: A case study
  131. Speedometer reliability in regard to road traffic sustainability
  132. Design and construction of a scanning stand for the PU mini-acoustic sensor
  133. Utilization of intelligent vehicle units for train set dispatching
  134. Special Issue: ICRTEEC - 2021 - Part I
  135. LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control
  136. Special Issue: Automation in Finland 2021 - Part I
  137. Prediction of future paths of mobile objects using path library
  138. Model predictive control for a multiple injection combustion model
  139. Model-based on-board post-injection control development for marine diesel engine
  140. Intelligent temporal analysis of coronavirus statistical data
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