VIRTUAL REAL-TIME SIMULATION OF A COMPLEX PRODUCTION …353939/FULLTEXT01.pdf · VIRTUAL REAL-TIME SIMULATION OF A COMPLEX PRODUCTION LINE ... 5 BINAR OP44 HMI 1 panels are independently

VIRTUAL REAL-TIME SIMULATION OF A COMPLEX PRODUCTION LINE

Development of PRESSOPT: a simulation software tool

T. C. KASONGO

Supervisor: M. Bo SVENSSON

Industrial Robotics Project MARCH – MAY 2007

ABSTRACT This report presents my work placement at University West (Trollhättan, SWEDEN) within the framework of an industrial robotics project. The subject of the study is the development in C++ language of a software tool, called PRESSOPT, which takes part in the simulation of an automated production line of the Gothenburg’s VOLVO CAR plant. The global objective is to define a tool enabling the virtual test of all the input parameters combinations; this way, we will be able to identify those which jointly get a high production rate and an optimal robots dynamics. The simulation is established according to a complex model: the Virtual Real-Time Model (VRTM). In order to optimize simulation times, it is necessary to improve the calculation methods governing operation of the model. The development of the PRESSOPT application is done in this aim.

RÉSUMÉ Ce document fait état de mon séjour d'échange à l'Université West (Trollhättan, SUÈDE) dans le cadre d'un projet de robotique industrielle. Le sujet d'étude est relatif au développement en langage C++ d'un outil software, nommé PRESSOPT, qui participe à la simulation d'une ligne de production automatisée de l'usine VOLVO CAR de Göteborg. L'objectif global est de définir un outil permettant de tester virtuellement toutes les combinaisons de paramètres d’entrée possibles ; de cette manière, on pourra identifier celles qui procurent conjointement un taux de production élevé et une dynamique des robots optimale. La simulation est établie selon un modèle complexe : le Virtual Real-Time Model (VRTM). Afin d’optimiser les temps de simulation, il convient d’améliorer les méthodes de calcul régissant le fonctionnement du modèle. C’est dans cette démarche que s’inscrit le développement de l’application PRESSOPT.

TABLE OF CONTENTS

1. INTRODUCTION ........................................................................................................................ 1

A. CONTEXT AND STAKES OF THE STUDY.............................................................................................. 1 B. OBJECT OF STUDY AND ASSOCIATED MODEL.................................................................................... 1 C. CONTRIBUTION TO THE PROJECT..................................................................................................... 2

2. NETWORK INSTALLATION & SIMULATION............................................................... 4

A. STRUCTURE AND ELEMENTS OF THE NEW SIMULATION NETWORK...................................................... 4 B. INTRODUCTION OF IMPLEMENTED SOFTWARE TOOLS........................................................................ 5 C. HOW TO LAUNCH A SIMULATION? .................................................................................................... 8

3. DEVELOPMENT OF THE PRESSOPT SOFWARE ...................................................... 11

A. CURRENT STATE OF THE APPLICATION AND MODIFICATIONS TO BE DONE........................................ 11 B. FROM PRESSOPT 1.0.18 TO PRESSOPT 1.0.19......................................................................... 13 C. PRESSOPT 1.0.19 TESTS RESULTS................................................................................................ 17

4. CONCLUSIONS ......................................................................................................................... 19

A. ASSESSMENT ON THE PROJECT ADVANCEMENT............................................................................... 19 B. PERSPECTIVES : CREATION OF AN "OPTIMIZER" PROGRAM............................................................. 19 C. PEDAGOGICAL PROFITS................................................................................................................ 19

APPENDIX................................................................................................................................20

INDEX OF FIGURES ..............................................................................................................21

1

1. INTRODUCTION

A. Context and stakes of the study Improving production lines performances has always been the major concern of the industrials. In the case of automated production lines, two methods allow us to reach this purpose:

� Operate the process control interface in order to find the combinations of input parameters which get an optimal productivity ("on-line" optimisation)

� Input various combinations of parameters to a simulation model of the production line to identify those which get the best results ("off-line" optimisation)

Even though the on-line optimization method is the only one among today’s complex automated production lines, we can easily understand the advantages of the off-line method : energy saving, absence of property damages in the event of collision, does not disturb the production, etc. However, we are quickly approached by the legitimate issue of the limits concerning this method; the results of the off-line optimization are indeed obtained on the basis of model, but a model is not reality. This is the point on which the VRTM (Virtual Real-Time Model), a complex simulation model, successfully showed its effectiveness during its application to the concrete case of a line of production.

B. Object of study and associated model The object of study of this industrial robotics project is the n°53 automated press line of Gothenburg’s VOLVO CAR factory (SWEDEN). Operating since about fifty years, it consists in 5 vertical presses dedicated to shaping metal sheets for cars. The production line is supplemented by 2-axis loader/unloader UNIFEEDER robots designed by company BINAR in Trollhättan.

Figure 1. 3D model of the VOLVO metal sheet press line

UNIFEEDER Robot

Press

1. INTRODUCTION

2

The stage of increasing the production line productivity is related to the aim of making the metal stamping equipment profitable, which caused a heavy financial investment at VOLVO firm. Off-line optimisation tests would thus permit to increase the investment’s profitability without stopping the production. Moreover, virtual simulation can be used in order to optimize the robots dynamics (smoother movements) in order to limit their wear; this is its second crucial interest. The first operational simulation model of the production line is a complex model which respects the general structure of a VRTM. It was tested for the 1st time in 2005 and provided very satisfactory results.

Figure 2. General Virtual Real-Time Model The two important interests of the model are: firstly, the fact that it implements the IEC 61131-3 control code which is present on the real production line; in the second place, this model works on the basis of virtual real time, which implies that all the operations are time synchronized1. Nevertheless, the current model is restrictive: it is limited to the simulation of 3 press stations instead of the 5 in the real production line. Moreover, we have to limit the number of simulation parameters. This is why it appears necessary to initially develop the simulation tools; this project is a contribution to reaching this objective.

C. Contribution to the project Within a research team of the Technology, Mathematics & Computer Science department of University West (Trollhättan, SWEDEN), my mission consisted in intervening on the source code of the simulations management program PRESSOPT in order to introduce new functionalities. This program developed in C++ language allows the simulation’s inputs acquisition and sets the optimal combinations in memory. At the launching of simulation, parameters seized in PRESSOPT by the operator are communicated to the process

1 This synchronization is allowed by the SDSP (Synchronised Distributed Simulation Protocol) system.

SDSP SERVER • Time Synchronisation

• Virtual Real-Time Data Base

• Disturbed Simulation

PROCESS • Kinematics

• Dynamics

• Visualisation

• Collision Detection

• …

SIGNALS & COMMUNICATION

• Cross Connection

• Event Response

• Logic Response

• Steady State (alterable)

• …

HUMAN MACHINE INTERFACE

• Operator Panel

• Operator Interface

CONTROL SYSTEM 1 (REAL OR EMULATED)

CONTROL SYSTEM 2 (REAL OR EMULATED)

CONTROL SYSTEM n (REAL OR EMULATED)

. . .

1. INTRODUCTION

3

(RobCAD via SDSP Server) [�]. Feedback information [�] are then copied by PRESSOPT into two text files: result_file.txt and result_file.txt.uf [�]. After that, a MATLAB program uses those two files data to calculate the characteristic sizes of the production line (production rate, speed, acceleration…) [�]. These results are finally copied into a third text file: matlab_result_file.txt [�]. The MATLAB program intervention being very expensive in memory, it extends the computing time and slows down the simulation. We thus wish to directly calculate the final values by PRESSOPT and to store them without passing through MATLAB. This aim implies a revision of the PRESSOPT application source code in order to introduce the suitable functions of calculation.

Figure 3. Aim of the project

PRESSOPT

result_file.txt

SDSP Server RobCAD

Simulation process

result_file.txt.uf

MATLAB

�

�

�

� �

OBJECTIVE: Obtain the same

results without ��

matlab_result_file.txt

4

2. NETWORK INSTALLATION & SIMULATION

A. Structure and elements of the new simulation network We evoked in the introduction the need for curing the handicap of current simulation times. A preliminary stage with the new tests is thus essential: installing the hardware equipment of the new simulation network. The great difference between the new simulation network and the old one relies in the used computers: in the new we use professional Server Computers. The performances of the latter computers are definitely higher than those of ordinary PCs owing to the fact that they generally have several processors. Proof of their performance: these computers enabled to divide simulation times by 8! They thus meet better the simulation’s requirements in terms of memory and computing speed. Secondly, the new simulation network, wanting to be more faithful to real production line, is composed of 5 computers dedicated to simulate respectively the 5 press stations. Consequently, we obtain a complex network structure copied on the real environment configuration. This allows the operator to recover his marks when he is in front of the simulation process:

� 5 computers respectively simulate the 5 presses of n°53 Gothenburg’s factory production line and ensure their synchronization

� 5 BINAR OP44 HMI1 panels are independently connected to each one of the 5 press simulation computer

� 5 touch screens are connected to the 5 simulation computers in order to emulate the rest of the control station.

� 1 computer allows to launch the simulation (PRESSOPT application) and to visualize the production line virtual 3D model moving (RobCAD software)

� 1 computer acts as a server and manages (in association with a switch) the communication between each computer of the network

Each network computer having a specific task, it was necessary to find a fast identification mean, more eloquent than their IP addresses. We adopted the original solution of allotting great Swedish figures names to each network computer. Thus: NOBEL assumes the role of server (communication between each element); LINNE supervises simulation (initialization and visualization); CELCIUS, LAVAL, POHLEM, PLATEN and DALEN are in charge of the synchronized simulation of the 5 presses. The Operating System used on NOBEL is Linux FEDORA. The other network computers are using Windows XP.

1 HMI stands for : Human Interface Machine


5

Figure 4. Simulation network architecture In accordance with the VRTM structure presented in the Introduction, we recover the five entities of the simulation system: SDSP SYSTEM, CONTROL SYSTEM, HUMAN INTERFACE MACHINE, PROCESS and SIGNAL & COMMUNICATION .

B. Introduction of implemented software tools In order to assimilate the operating mode of the simulation, I had as a preliminary to understand the various software that take part in it. Some of them are very particular owing to the fact that they correspond to modified or emulated versions of material used in the real production line. Let us briefly present each one of them: PRESSOPT It is the starting point of the simulation. This application has been developed at the University West in C++ language using the Borland C++ Builder RAD (Rapid Application Development). Although it is currently operational, PRESSOPT is still under development. The role of PRESSOPT is to allow the user to enter the input parameters. This functionality is formalized by a table in which the user selects the parameters that will vary, their respective range and steps of variation. Once simulation is completed we obtain two output text files from PRESSOPT which are returned to MATLAB for the achievement of calculations. We will make a more detailed explanation of these data’s nature in the second chapter which is entirely devoted to my work on the PRESSOPT application.

NOBEL *

CELCIUS * LAVAL * POHLEM * PLATEN * DALEN *

LINNE *

HUMAN MACHINE INTERFACE

PROCESS

SDSP SERVER +

Emulated CONTROL SYSTEM

SIGNALS & COMMUNICATION

* : computer name


6

RobCAD This 3D modelling and numerical simulation software, developed by TECNOMATIX company, is much recommended in the robotics industry. Within the framework of the project, RobCAD allowed the development of the production line 3D model. The actuation of this model is controlled by the combinations of PRESSOPT input parameter. The user of the simulation system thus has a mean to visualize and monitor the kinematics of the production line. In addition, RobCAD allows the identification of possible dysfunctions. Indeed, like each software implemented during simulation, RobCAD communicates with the SDSP Server; thus it measures then returns every 5 milliseconds the physical sizes relating to the position of the 3D robots model. Thanks to RobCAD we are able to detect collisions between a robot manipulator and a press (which is one of the most important feedback information from the simulation process!)

Figure 5. Screen print of the RobCAD 3D simulation model L53 HW OPERATOR PANEL It is a virtual control panel developed at the West University by Mr. Bo Svensson. Usable through a touch screen, the L53 HW Operator Panel is added to BINAR OP44 in order to reconstitute the entire control station of the operator (signal lights, initialization buttons, start buttons, etc.). The L53 HW Operator Panel is thus the prolongation of the 5 HMI of the simulation network; therefore, it is installed on each of the 5 simulation machines CELCIUS, LAVAL, POHLEM, PLATEN and DALEN to ensure the independent control of UNIFEEDER robots.


7

The most important functionality of L53 HW Operator Panel is the choice of the robots operating mode:

� MODE SLOW : engage the manual control of the robot � MODE INCH : engage the robot low motion functioning � MODE SINGLE : engage the execution of one robot working cycle � MODE AUTO : engage the robot automatic functioning

Figure 6. Confrontation of the HMI in the simulation model and in the reality Note: On LINNE is installed the virtual L53 Start Panel which ensures the global

management of the whole press stations. This software allows the users to operate the 5 presses during the initialization stage (state signals, “stamp out” order button, number of cycles left to be done, etc).

SDSP UHS EMULATOR & PLINTs The SDSP UHS Emulator software is installed on each of the simulation machine (CELCIUS, LAVAL, POHLEM, PLATEN and DALEN). It emulates the real control system (BiFas UHS) designed by BINAR company and works in association with the PLINTs.

+

L53 HW Operator Panel

BINAR OP44

Virtual real-time model HMI Real production line HMI


8

The role of the PLINTs is to ensure the connectivity between network active elements; they manage simulation data (name, parameters, inputs/outputs, etc.) through the TCP/IP protocol. Together, the SDSP UHS Emulator and the PLINTs both guarantee synchronization and communication of the various machines taking part in the simulation. A new internal scales time is thus defined: the virtual real time.

Figure 7. Screen print of the SDSP UHS Emulator front panel All these software (except RobCAD) are installed on the server (NOBEL) shared partition, which allow them to start from every XP-computer.

C. How to launch a simulation? We have just established the diversity of the software brought into play during the simulation. To function and communicate together these software need to have been configured correctly. The protocol to launch the simulation material is however tiresome and far from being instinctive… I thus took the initiative in writing a start procedure for which I added some notes. This procedure has been performed to be re-used and supplemented by the future participants in the project. N.B. The simulation tests I did to validate my program have been carried out according to

the old 3 presses simulation model. This with the single aim of obtaining results comparable to the old ones (taken as reference). This procedure thus refers to a 3 presses simulation model, but can be generalized to the future 5 presses model.

139,69 ms in the reality are equivalent to 5 ms (1 step) inside the simulation time scale


9


10

NOTES

• Useful commands for LINUX terminal dir : give the list of the files contained in the current directory list : give the list of the software running in the current simulation

• Useful button on BINAR OP 44 Panel Förenande Meny : return to the precedent menu

11

3. DEVELOPMENT OF THE PRESSOPT SOFWARE

A. Current state of the application and modifications to be done In parallel to the network installation, I had to undertake the discovery of PRESSOPT application’s source code. This latter code is organised in several C++ files related ones to the others by "headers" (or include files). Quickly, my attention was targeted on the files simulation.cpp and simulationthread.cpp which ensure commonly: the setting in memory of the user’s input parameters, the management of feedback information from the simulation process and the generation of PRESSOPT output data.

Figure 8. Screen print of the PRESSOPT front panel: Outputs and Inputs identification

INPUTS

I.1 Parameters value I.2 Saving results or not I.3 Simulation method choice I.4 Network addresses of simulation machines

OUTPUTS

O.1 Best simulation parameters O.2 Running stroke information O.3 Visual feedback graphics (no scale)

I.1

I.4

O.3

I.2

O.1 I.3

O.2

3. DEVELOPPEMENT OF THE PRESSOPT SOFTWARE

12

� PRESSOPT application inputs

The foremost inputs are the 14 parameters entered in the PRESSOPT front panel table by the simulation system operator. These parameters are stored into long double type variables respectively named Pi, with i Є [0;13]. Their values influence the kinematics and the working cycles3 of the production line equipments:

o Parameters cam: they determine the emission moments of communication signals between robots and presses. [Unit: degree].

o Parameters position: they fix the coordinates of robots state changing positions during its cycle of operation. [Unit: degree].

o Parameters velocity: they determine speed instructions for robots motions during a given phase of its cycle. [Unit: percentage of the robots maximum speed]

To know the designation and the exact influence of each parameter, please refer to the appendix (Figure A2.). The other inputs of the PRESSOPT software are the name of the result text file and the selected simulation method. � PRESSOPT application outputs

Among the outputs we can distinguish: the visual feedbacks (graphic and signal lights) and the results text files ("<filename>.txt" and "<filename>.txt.uf"). We are only interested in the second type of outputs. The result file "<filename>.txt" is generated by C++ script simulationthread.cpp. In this file are successively described each stroke4 of every UNIFEEDER robot by means of the values returned by both the HMI and RobCAD (production rate, unexpected collision).

Figure 9. Output result file “<filename>.txt” from PRESSOPT 1.0.18

3 Presses and robots working cycles are modelled by operating points traversing the 360 degrees of an ellipse. (cf. in Appendix [Figure A1.] : Press Line Working Cycle). 4 The stroke term indicates one UNIFEEDER robot working cycle; each stroke lasts on average 4,9 seconds.

Production rate Collision

Input stroke parameters (Pi)


13

Drawbacks of the "<filename>.txt" file - The production rate values (calculated by the IEC 61131-3 control code) are too

approximate. - There is confusion between the strokes and the steps5, what is harmful to the

results comprehensibility. - No information relating to the robot motions (dynamic optimization of the

production line is thus impossible)

Therefore, the "<filename>.txt" results file is not (for the moment) a good tool for qualitative analysis of the various Pi’ s combinations. That explains the current recourse to a MATLAB program which establishes the calculation of missing information. The second output file, "<filename>.txt.uf", is generated by the simulation.cpp script. The ".uf" extension indicates the manipulator robot reference: UNIFEEDER. Indeed, in this file is reported all the information concerning the robot position at each step, i.e. every 5ms.

Figure 10. Output result file “<filename>.txt.uf” from PRESSOPT 1.0.18

Drawbacks of the "<filename>.txt.uf" file - Absence of the "." symbol separating the integer and decimal parts, which is can

lead to mistakes. - Confusion between strokes and steps - Step parameters insufficient for the production rate calculation

B. From PRESSOPT 1.0.18 to PRESSOPT 1.0.19

5 Each stroke is split in a succession of 5ms duration steps. Thus a 4900 ms stroke is divided into 980 steps.

steps

stroke

deg Xmm Zmm


14

In order to compensate for PRESSOPT results files defects and insufficiencies, I had to alter the contents of both simulation.cpp and simulationthread.cpp scripts. The assessment of my actions respects the following advance: i) Localization of the entrance point of the variables describing steps {deg,

Xmm, Zmm} for calculating the parameters {speed, acceleration, jerk}.

The reception of the {deg, Xmm, Zmm} values is carried out inside the SaveUFProfile function of the simulation.cpp script. I used this entrance point to define these data according to a suitable type of variable (double) :

I thus found myself able to determine the {speed, acc, jerk} robot parameters for each working step:

These calculations are implemented in the “while” loop which manages the writing of every step of a stroke. The variable n is an integer initialized to 0 and incremented at each loop (counter).

ii) Variables declaration to store additional stroke parameters (relevant sizes

for dynamic optimization) We said earlier that the PRESSOPT output file "<filename>.txt" was to be supplemented with sizes better revealing the dynamics of the production line. These sizes, relating to the robot during a stroke, will be: the mean acceleration [m/s2], the global stop time [s] and the stop position [deg]. The weight of the transported metal plates from one press to another not being negligible, it modifies the inertial properties of the robots. Consequently, each one of these sizes will be calculated twice: in neutral and under load.


15

Let us recall then that we should calculate the production rate in a more precise way than the IEC 61131-3 control code. We thus obtain a total of 7 new parameters to be introduced into simulationthread.cpp script (originally responsible for creating "<filename>.txt") Calculations being done in the simulation.cpp script, I had to declare these variables in the tRun6 structure of the simulation.h header file:

iii) Calculation of the production rate for each stroke

The production rate is calculated at the exit of the “while” loop which determines the parameters of every n step of a stroke. The variable glRun.ProdRate being of double type, we will now obtain a production rate value with an accuracy of 6 decimals:

iv) Calculation of the robot global stop time for each stroke

A cycle stop time is defined as one period during which the robot ceases evolving in its working cycle (i.e. deg(t) = constant). A first method to determine these instants would consist in calculating the variation of deg(t) according to the time : speeddeg(t). But this method is not adapted, indeed the time difference between two steps being only 5 ms, the variation between two successive deg(t) would often be close to zero (it implies an erroneous stop time detection !).

6 tRun is a global structure whose members can be used in any part of the PRESSOPT source code. The call of a tRun structure member is made according to syntax: tRun.<member> or glRun.<member>.

end of the "while" loop


16

I thus defined a new 20 milliseconds long step: the step20. To each step20 is associated the couple of values {deg20, speeddeg20}. When speeddeg20 is equal to zero, it means that the robot is in a stop position. Therefore, we can determine the global stop time by counting the number of stop times:

At the exit of the steps loop we multiply counters values by 20 ms, so we obtain the robot global stop time:

v) Determination of the robot stop position for each stroke The determination of stop positions is established in parallel to the stop time counters incrementing: when speeddeg20 equals zero, we set in memory the associated deg20 value. At the steps "while" loop exit, this value is stored in the global StopPosition variable.

This function acts as a "stop position controller" because the stop position instruction is fixed at 92 deg of the robot working cycle.

Stop counter when robot gripper holds a plate

Stop counter when robot gripper is empty


17

vi) Calculation of the robot mean acceleration for each stroke

In order to determine the mean acceleration we add the acceleration for each step, and divide it the number of steps where the acceleration is different from zero:

C. PRESSOPT 1.0.19 tests results

In order to validate the new PRESSOPT version, I reproduced old simulations whose results had been established with MATLAB. Let us compare these old MATLAB results with the results provided by PRESSOPT after compiling of the new source code: The test simulation is run for 2 successive strokes using the following parameters:


18

� New "<filename>.txt.uf" file

Figure 11. Output results file “<filename>.txt.uf” from new PRESSOPT 1.0.19 If we compare the new <filename>.txt.uf result file with the previous one (cf. Figure 10), we first notice its more explicit presentation, which improves both readability and comprehension. The confusion step/stroke has been corrected, as well as the numbers display format. We can then observe that the steps description is now more exhaustive (speed, acceleration, jerk), which will make us able to check the results coherence in case of doubt about calculated strokes parameters. � New "<filename>.txt" file

Figure 12. MATLAB results file VS. “<filename>.txt” from new PRESSOPT 1.0.19 Results provided by PRESSOPT 1.0.19 are very close to those obtained with the MATLAB program. In fact, the main difference appears in the calculated mean accelerations. Therefore, the new results are acceptable and PRESSOPT 1.0.19 can be validated.

MATLAB results

PRESSOPT 1.0.19 results

19

4. CONCLUSIONS

A. Assessment on the project advancement In accordance with the initial objectives, we met the need to reduce stages of calculation. The PRESSOPT application is consequently more autonomous and gets into the core of the simulation process. Moreover, as the new output files are satisfactory, we can consider the integration of new functionalities dedicated to the data processing. This work of development thus opens the way to the prospect of analysing the stroke result file ("<filename>.txt"). Indeed, the objective of reducing simulation times could be fully achieved if PRESSOPT became able to detect the parameter combinations which have already been simulated. This implies the implementation of both a tool and a result storage method, which remain to be defined.

B. Perspectives : creation of an "Optimizer" program Once the times computing issues are solved, it will be necessary to concentrate on the identification of the optimal input parameters. This means finding the combinations of the influent parameters which provide both best production rate and robot motions. The solution considered now is creating and implementing an "Optimizer" program at the PRESSOPT software input. However this solution requires a preliminary study on the choice of an adapted method (Monte-Carlo, Nelder-Mead, iterative improvement…), because the space of the solutions is not linear!

C. Pedagogical profits From a teaching point of view, this industrial robotics project enabled me to consolidate my assets in object-oriented programming as well as confronting me with the reality of the stakes of productivity of the automotive industry. However, if the contents of the subject agreed with my competences acquired at the ENSIL, I had the feeling I was doing programming rather than mechatronics. Nevertheless, the work with qualified people allowed me to live this project like a true professional experience, having in addition contributed to the improvement of my English. This exchange stay was a positive experience, which provided a great enrichment from both personal and cultural viewpoints.

20

APPENDIX

www.hv.se

VRTM a Tool for Increased Production

Feb 1, 2007Bo Svensson

Press Line Working Cycle

Press nUniFeeder n

(180 o)Fetch Leave

LowSpeed

Wait

Home(180 o)

(0 o)

(0 o)

Top

Bottom

ReleaseUnloader

ReleaseLoader

ReleasePress

[Figure A-1.] Press working cycle

www.hv.se

VRTM a Tool for Increased Production

Feb 1, 2007Bo Svensson

Operator Adjustable Parameters

� Release Loader (UF)

� Release Press (UF)

� Release Unloader (Press)

� Position Wait (UF)

� Position LowSpeed (UF)

� Position Home (UF)

� Speed Fetch – Wait (UF)

� Speed Wait – Leave (UF)

� Speed Leave – LowSpeed (UF)

� Speed LowSpeed – Home (UF)

� Speed Home – Fetch (UF)

[Figure A-2.] Operator adjustable parameters

21

INDEX OF FIGURES Figure 1. 3D model of the VOLVO metal sheet press line............................................................1 Figure 2. General Virtual Real-Time Model.................................................................................2 Figure 3. Aim of the project..........................................................................................................3 Figure 4. Simulation network architecture...................................................................................5 Figure 5. Screen print of the RobCAD 3D simulation model.......................................................6 Figure 6. Confrontation of the HMI in the simulation model and in the reality...........................7 Figure 7. Screen print of the SDSP UHS Emulator front panel....................................................8 Figure 8. Screen print of the PRESSOPT front panel : Outputs and Inputs identification.........11 Figure 9. Output result file “<filename>.txt” from PRESSOPT 1.0.18.....................................12 Figure 10. Output result file “<filename>.txt.uf” from PRESSOPT 1.0.18...............................13 Figure 11. Output results file “<filename>.txt.uf” from new PRESSOPT 1.0.19......................18 Figure 12. MATLAB results file VS. “<filename>.txt” from new PRESSOPT 1.0.19..............18

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VIRTUAL REAL-TIME SIMULATION OF A COMPLEX PRODUCTION …353939/FULLTEXT01.pdf · VIRTUAL REAL-TIME SIMULATION OF A COMPLEX PRODUCTION LINE ... 5 BINAR OP44 HMI 1 panels are independently