Multipolar synchronous material flow & process simulation in difussed manufacturing systems.
Cotet, Costel Emil ; Dragoi, George ; Abaza, Bogdan Felician 等
Abstract: We had applied in this paper our new algorithm
integrating the process simulation using specialized CAM (Computer Aided
Manufacturing) software in the material flow simulation on diffused
manufacturing systems where are several work points of the same
importance in the system. The result is a synchronous simulation model
providing more accurate results. In order to optimize manufacturing
systems architecture, finally, a multipolar distributed simulation
composed of four individual simulations is successfully tested across
platforms over the internet.
Key words: multipolar synchronous simulation, process, material
flow, diffused manufacturing systems, productivity.
1. INTRODUCTION
As a result of our research in the last few years we determined
that if we want to optimize the architecture of a VE usual material flow
simulation is not enough (Cotet & al., 2004). One of the main
problems is the difference between the algorithms for process and
material flow island of simulation. This is the reason why we propose
here a new tool, synchronous multipolar simulation, able to evaluate the
performances of a VE as an integrated system. The synchronous multipolar
simulation analysis is more then concatenating the results of isolated
island of simulation. The flow concentrator as it results from the
synchronous multipolar simulation may be any one of the concentrators of
material flow manufacturing system simulation nodes but may also be a
total different one.
2. FOCUS ON THE FIFTH ELEMENT
Five main elements must be defined in order to perform our
simulation algorithm.
We define diffused manufacturing systems as architectures with more
than two work points connected by transport & transfer systems and
using deposits at local or system level (Cotet & Dragoi, 2003).
We agree here with the thesis that within the class of stochastic
simulation models, one further distinction is necessary: simulations can
be either terminating (sometimes called finite) or nonterminating in
nature, with specific algorithms for each category (Sanchez, 2001).
We agree that virtual enterprises could be defined as ephemeral
organizations in which several companies collaborate to produce a single
product during a project cycle time (Tichkiewitch & al., 2006).
We define as multipolar distributed simulation the integrated
monitoring system of more than two material flow simulations
interconnected in VE architecture.
Last but not least we consider a material flow and process
synchronous simulation the simulation of a model where at the level at
the work point the process simulation is concomitant with the material
flow simulation.
As reflected in this paper our present research is now focused on
this fifth element.
[FIGURE 1 OMITTED]
We built the multipolar synchronous simulation algorithm starting
from the multipolar simulation model for virtual enterprises developed
in our UPB-PREMINV Research Centre (Cotet & al., 2004). During those
previous researches we developed this preliminary model using SADT and
tested it in our virtual enterprises oriented partnerships with
industrial SMEs. The main improvement to this preliminary model is that
in our new algorithm every work point process simulation will be related
with the material flow simulation. Actually in this new approach at the
level at the work point the process simulation is concomitant with the
material flow simulation.
3. A THREE LEVEL ALGORITHM
Three levels of integration are defined in the multipolar
synchronous simulation algorithm:
At the first level main parameters for the work points modeling in
material flow simulation are provided form CAM simulations describing
the manufacturing process (Lee, 1999). This way the material flow
simulator is integrating the process simulation results at the level at
the work point in order to provide a complete model of the manufacturing
system.
At the second level the terminating simulation algorithm (mainly
used in diffused related architectures) is applied for each
manufacturing system of the virtual enterprise network.
At the third level the virtual enterprise material flow is
simulated. In this model the work points are the terminating simulation
models describing the virtual enterprise partners manufacturing systems
material flows. At this level the complexity of synchronizing process
and material flow simulation is higher then in concentrate manufacturing
systems with a single work point. The stochastic laws describing the
MTBF (mean down interval) and MTTR (mean repair time) for every work
point for every industrial partner activating as a virtual enterprise
network node must be corroborate with the laws describing the integrated
multipolar model work points (describing the material flow at the level
of each enterprise as well as for the entire virtual enterprise
architecture). The first case study that allowed us to test our model
was provided by one of our research projects implying four industrial
partners working in a virtual enterprise environment.
[FIGURE 2 OMITTED]
4. LOCAL & MULTIPOLAR SYNCHRONOUS MODELS
In our case study four diffused manufacturing systems are implied.
For each of those manufacturing systems synchronizing process and
material flow simulation is based on modeling using two software
solutions: CATIA and Witness.
At the end of this local synchronizing process the material flow
simulation using Witness software as well as the CAM simulation allowed
us to change some of the manufacturing cycles introducing stochastic
distribution laws values for MTBF or MTTR adapted to each work point
characteristics. In figure 2 is presented one of those manufacturing
systems synchronous simulation models. Based on those four models we
built then the multipolar model. In this model describing the
manufacturing processes and the material flow of the entire virtual
enterprise architecture the model of each manufacturing system acts like
a work point. Based on the four local models stochastic laws are
describing specific parameters characterizing the activity of each
enterprise. For example taking into account that the flexible
manufacturing system presented in figure 2 is producing two kinds of
parts, the failed parts number for each type will be described by a Beta
stochastic distribution law with specific parameters as one can see in
figure 4. Because of specific parameters describing the activities
performed by each manufacturing system acting like a node of the virtual
enterprise network the multipolar model use different stochastic laws
then the usual MTBF or MTR ones.
[FIGURE 3 OMITTED]
[FIGURE 4 OMITTED]
The multipolar model describing the activity of the virtual
enterprise network will be acting like a diffused manufacturing system
where the work points are the four manufacturing systems models.
5. CONCLUSION
The main goal of our research was to propose an algorithm able to
increase the productivity of virtual enterprises architecture by
improving the discrete material flow management. As in our previous
material flow simulation based algorithms in this new algorithm one can
analyze the results of the material flow simulation, identify the flow
concentrator for the diffused manufacturing architecture and propose an
architecture modification as a solution for this problem. A second
simulation to validate the optimized architecture and the obtained
increase of productivity is necessary as well as a financial analysis
must confirm the profitability of such a solution.
The main innovative character of our new multipolar synchronous
simulation algorithm is given by the three kinds of synchronic simulation identified and used by us in building our model.
First of all at the level of each manufacturing system the CATIA
process simulation for each work point is synchronic with the material
flow simulation describing the entire system activity.
Secondly the simulation of the material flow multipolar model and
the simulation of material flow for each manufacturing system model are
synchronous.
Last but not least the integrated multipolar model is synchronizing
the material flow and process simulation models for all the work points
of the virtual enterprise architecture.
6. REFERENCES
Cotet, C.E., Dragoi, G.S. (2003). Material Flow Management in
Validating Concentrate and Diffused FMS Architectures, In: International
Journal of Simulation Modelling IJSIMM, no. 4, December 2003,
pp.109-120, ISSN 1726-4529, Vienna.
Cotet C.E., Abaza B.F., Carutasu N.L. (2004)--Multipolar
Distributed Simulation for Concentrate and Diffused FMS-Romanian Journal
of Technical Sciences--Applied Mechanics, Tome 49, Editura Academiei
Romane, 2004, p. 647-650. ISBN 973-27-1102-7; ISSN 0035-4074, Bucharest.
Lee, K. (1999). Principles of CAD/CAM/CAE Systems, Addison Wesley
Longman, Inc., ISBN 0-201-38036-6, USA.
Sanchez, S. M. (2001). ABC's of output analysis, Proceedings
of The 2001 Winter Simulation 2001, Peters, B.A., Smith, J.S., Medeiros
D.J., CD-ROM, Presses Association for Computing Machinery (ACM), New
York.
Tichkiewitch, S.; Radulescu, B. & Dragoi, G. (2006). Knowledge
management for a cooperative design system, Advances in Design,
ElMaraghy & Hoda A. Eds., pp. 97-110, Springer Verlag, ISBN
1-84628-004-4.