Article AINA 2009

7/31/2019 Article AINA 2009

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Enhancing the Flexibility of

Manufacturing Systems Using the

RFID Technology

Valentin VLAD, Adrian GRAUR, Cristina Elena TURCU, Cezar POPA

Stefan cel Mare University of Suceava


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Introduction

RFID (Radio Frequency Identification) represents a very suitable technology for data acquisition and

process control in the industrial manufacturing sites, due to itscharacteristics: waterproof, antimagnetic, high temperature

resistance, etc.; enables the possibility to obtain real-time information about thephysical items involved in the process;

improve the production efficiency and reduce the productioncost;

allows the production system to be more decentralized andflexible;

provides capabilities for enhancing the calibration processof a system.


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Introduction

In a manufacturing system the need for calibration appears when thesystem is installed for the first time or in response to a change

Into an intelligent system the calibration process is desired to becompletely automatic

It may include: The discovering of the production facilities The discovering of services and requests for each production facility The building of a map containing the positions and the optimum routes among

the system devices

Our paper is focused on an RFID-based solution to automaticallydetermine the positions of the production facilities contained in amanufacturing system and connected by conveyor belts.


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Related work

The Agile Assembly Architecture Developed in the Microdynamic Systems Laboratory of the

Carnegie Mellon University

The transport of products is assured by 2-DOF (Degree of

Freedom) planar robots, called couriers.

During the calibration process each courier may perform sensor-basedcoverage of its workspace, having no a priori information.

After a completely workspace coverage, all devices placed in the couriers

workspace are detected.

An RFID driven control scheme for production control introduced in

[Kamioka et al., 2007] It is focused in applying the holonic concept to production control in order to

lessen the excess production and decrease the lead time


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The demonstration environment

It is built around a closed loop Bosch Rexroth conveyor, with threeflows.

The modular construction of the conveyor allows the system to be easilyextended or reconfigured.

Bosch Rexroth conveyor with three flows


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On each flow a microcontroller-based station is installed, which canread and modify the content of an RFID tag using an RFID tagreader/writer.

These stations are called as A, B and C in the figure bellow. The role of each station is to simulate a production facility that can

execute one or more operations on a product component.

BC

ASW1 SW2

IN OUT

1

00

1

Flow 1

Flow 2

Flow 3

Schematic of the system


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The microcontroller-based stations and the switch controllers arenetwork connected and can communicate with a central PC.



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Hardware architecture of the

microcontroller-based stations


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The calibration process

It is consisting of two phases:

1. In Phase 1 each production facility controller and switch

controller communicates to a central manager information

about its services and receives an address to be uniquelyidentified in the system

2. Phase 2 concerns the building of a system map by

determining the positions of each production facility and

conveyor switch.


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A component with an RFID tag attached is loaded at the conveyor inputand transported through all of the conveyor routes.

All production facilities and conveyor switches must write theiraddresses in the transponders memory, together with the writing time.

BC

ASW1 SW2

IN OUT

1

00

1

Flow 1

Flow 2

Flow 3

a) Schematic of the system b) The track of the discovering component

SW2(0)

B SW1(0)

C SW1(1)

SW2(1)

A SW1

t1 t2 t3 t4 t5 t6 t7

The proposed solution for Phase 2


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Based on the collected information a directed weighted graph is built,whose nodes are represented by the production facilities and conveyorswitches, and the weight of arcs by the traveling time between nodes.

},,,,{ 12 ACSWBSWV =

]},[],,[],,[],,[],,[],,{[ 2111122 SWSWSWCCSWSWBASWBSWA =

],,[],,[],,{[},,,,,({),(12212

SWBASWBSWACSWBSWAVG == ]}),[],,[],,[2111

SWSWSWCCSW

SW2(0)

B SW1(0)

C SW1(1)

SW2(1)

A SW1

t1 t2 t3 t4 t 5 t6 t7

SW2 B SW1 C

A

1

0

0

1t1 t2 t3

t4

t 5

t6 t7

a)

b)

SW2(0) B SW1(0) C SW

1(1) SW2(1) A SW

1

t1 t2 t3 t4 t5 t6 t7

a)

The proposed solution for Phase 2


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The information tables

The necessary information for optimum leading productcomponents to the production facilities are contained inthree types of tables:

Theservices table is built in Phase 1 of the calibrationprocess

The routing tables are obtained from the system graph,which is built in Phase 2 of the calibration process

Thestatus table contains information about the state of

production facilities (free, busy, failed, etc.)


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The services table contains the operations able to be executed by each system

device;

is unique for all conveyor switches and allows them toidentify the production facilities able to do a certain

operation.

Production facility Operations

A O1, O

2

B O2, O

3

C O4

An example of a services table


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The routing tables are defined as electronic documents storing the routes to

the various nodes, represented by the conveyor switchesand production facilities ;

are built from the weighted graph by determining theshortest path between a switch and all of the productionfacilities.

are specific to each switch controller

An example of a routing table for the switch SW2.

Destination Cost (sec.) SW Position Next Hop

A 10 1 A

B 10 0 B

C 30 1 SW1


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The status table contains information about production facilities status; is updated

each time a production facility displays a change in its status; periodically, based on internal initiative, to update the time

information associated to a certain machine state.

An example of a status table

Production facility Status

A Busy for 80 s

B Free

C Failed


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An example

SW2 B SW1 C

A

1

0

0

110 16 8

12

20

10 8

BC

ASW1 SW2

IN OUT

1

00

1

Flow 1

Flow 2

Flow 3

Let's consider a simple manufacturing system having the configurationpresented in figure a).

The traveling costs on conveyor routes, expressed in seconds, aregiven in figure b).

a) b)


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BC

ASW1 SW2

IN OUT

1

00

1

Flow 1

Flow 2

Flow 3

An example

Consider the system is able to execute the operations set:

and each production facility is able to execute one or two operations from the set

O, according to the following services table.

},,,{ 4321 OOOOO =


A O1, O

4

B O2, O

3

C O4

The services table

O4 O2, O3

O1, O4


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SW1 SW21

00 A

B

C

1

Flow 1

Flow 3

Flow 2

An example

A component is loaded at the

conveyor input having written

onto the attached transponder

the operations O2 and O4.

Destination Cost (sec.) SW Position Next Hop

A 10 1 A

B 10 0 B

C 30 1 SW1


A O1, O

4

B O2, O

3

C O4

Station B executes the operation

O2 to the component and

releases it.

The componentarrives at SW2.

The routing table

The services table


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Solution improvements

Two improvements may be mentioned for the presentedsolution: The selection of the most appropriate production facility able to

execute the next operation for a component may be done when

the component is introduced in the system or immediately after aproduction facility ends off an operation. In this case the switch controllers will lead the pallets based only

on the address of the production facility which is the destination.

Another improvement is to contract or to reserve the productionfacility selected to execute an operation for a component

This will be an assurance that no other component which arrivesfirst at the production facility can occupy it.


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Conclusion and future work

The presented solution has the advantages of a decentralized system

with auto configuration capacity in the initial phase and reconfiguration

capacity in response to change.

The way of production facility selection lead to a certain independency

of the components towards the production facilities. A component may be directed to any production facility able to execute

the requested operations and is not bounded to a pre-established plan.

Future work is concerned in finalizing the practical implementation and

in extending the concept for other situations that can occur in a real

manufacturing system but which are neglected in this phase.


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References

J. Brusey, M. Fletcher, M. Harrison, A. Thorne, S.Hodges, D.McFarlane, Auto-ID based control demonstration. Phase 2: pick and place packing with holoniccontrol, Cambridge, 2003.

J. Hua, H. Sun, T. Liang, Y. Lei, The design of manufacturing executionsystem based on RFID, Workshop on Power Electronics and IntelligentTransportation System, 2008, pp. 8-11.

K. Kamioka, E. Kamioka, and S. Yamada, An RF-ID driven holonic controlscheme for production control systems, Proceedings of the 2007 InternationalConference on Intelligent Pervasive Computing, Korea, 2007, pp. 509-514.

D. McFarlane, S. Sarma, J.L. Chirn, C.Y. Wong, K. Ashton, The intelligentproduct in manufacturing control, in15th IFAC World Congress, Barcelona,2002.

R. Hollis, A. Rizzi, Agile assembly architecture: a platform technology for

microassembly, Precision Engineering 19th Annual Meeting, Orlando, 2004. Bosch Rexroth, http://www.boschrexroth.com T. Harju, Graph theory, Department of Mathematics, University of Turku,

Finland, 2007.

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