Afar for Agv in Adfms

7/30/2019 Afar for Agv in Adfms

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ALGORITHM FOR FUTUREANTICIPATIVE REASONING (AFAR) FOR

AGV IN AN AUTONOMOUS

DECENTRALIZED

FLEXIBLE MANUFACTURING SYSTEM

Abhijith GopinathS1/ M-Tech(Production Engineering)Roll No. 1

A Seminar on


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CONTENTS OF PRESENTATION1. FLEXIBLE MANUFACTURING SYSTEM (FMS)

2. AUTOMATED GUIDED VEHICLE (AGV)

3. AUTOMATED GUIDED VEHICLES IN FMS

4. CENTRALISED FMS

5. AUTONOMOUS DECENTRALISED FMS (AD FMS)

6. ALGORITHM FOR FUTURE ANTICIPATIVE REASONING IN AD FMS7. MODEL OF AD FMS STUDIED

8. ALGORITHM OF HYPOTHETICAL REASONING

9. PROPOSED HYPOTHETICAL REASONING

10. ANTICIPATING AD FMS CONDITIONS

11. AFAR FOR PART INPUT

12. AGV WITH INTELLIGENT KNOWLEDGE (AGVwIK)

13. CONCLUSION

14. REFERENCE


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FLEXIBLE MANUFACTURING SYSTEMS

Flexibility in manufacturing means the ability to allow

variation in parts assembly and variations in process

sequence, change the production volume and change the

design of certain product being manufactured.


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FLEXIBLE MANUFACTURING SYSTEM

The primarycharacteristic of FMSis that it integratesthe following:

1. Storage

2. ManufacturingMachines

3. Inspection

4. Tooling

5. MaterialsHandlingEquipments


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ADVANTAGES OF FMS

To reduce set up and queuetimes

Improve efficiency

Reduce time for productcompletion

Utilize workers better Improve product routing

Produce a variety of Itemsunder one roof

Improve product quality

Serve a variety of vendorssimultaneously

Produce more product morequickly


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BASIC COMPONENTS OF FMS

1. WORKSTATIONS

In present day applications the workstations are CNC machine

tools that perform machining operation on part families.

2. COMPUTER CONTROL SYSTEM

These systems are used to coordinate the activities of the

processing stations and the material handling system in the FMS.

Multi axis CNC Laser Mini

Workstation

The interface for a computer controlled

traffic control system


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BASIC COMPONENTS OF FMS

3. MATERIAL HANDLING AND STORAGE SYSTEM

Functions

1. Random, independent movement of parts between

stations.2. Handle a variety of part configurations.

3. Temporary storage.

4. Convenient access for loading and unloading.

5. Compatible with computer control.


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SOME MATERIAL HANDLING EQUIPMENTS

ConveyorBelts

Forklift Trucks

Cranes for Bulk

MaterialHandling

Robotic Arms

Automated Guided

Vehicles


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An Automatic Guided Vehicle (AGV) is a

mobile robot that follows markers or

wires in the floor, or uses vision or

lasers.

They are most often used in industrial

applications to move materials around a

manufacturing facility or a warehouse.

The most important advantage of AGV

is that it can be optimally integrated to

any manufacturing system.


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AGV SYSTEM

1 = Automated Guided Vehicle

2 = Management system

3 = Data transmission

4 = Guide track

(laser, inductive, optical)

5 = Loading/ Unloading Points

6 = Load handling equipment

7 = Machining Centres

12

3

4

5

66

7


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TASK ALLOCATION TO AGV

Current

Position

Collection

Point

Delivery

Point

The shop floor layout is fed

into the AGV as a .dft

program.

Based on the instructionreceived the AGV moves

along the specified path and

performs the operation

The AGVs are

provided with sensors

to prevent collision.

At intersections AGVs

pass on a First come

First Pass Basis.


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MAIN APPLICATIONS OF AGV

Repetitive movement ofmaterials over a distance

Regular delivery of stable loads

When on-time delivery iscritical and late deliveries arecausing inefficiency

Processes where trackingmaterial is important

AGVs transporting Work in Process jobs

AGVs transporting a palette of

finished goodsAGV used to move cargo in a port


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AUTOMATED GUIDED VEHICLES IN FMS

An AGV based material handling system is designed and

implemented to impart flexibility and efficiency to the productionsystem.

An effective AGV controller is needed to monitor the equipmentstatus and route the work piece movement, so that the rightmaterial can be moved to the right place at the right time.

The routing algorithms for AGV are different for the 2 types of

FMS:1. Centralised FMS

2. Autonomous Decentralised FMS


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CENTRALISED FMS

The route planning of AGV systems is determined by centralised decisionmaking system, which controls the entire shopfloor.

The routing instructions are sent to different AGVs to perform the task.

Central Computer

AGV

Onboard Controller Guide Path

Position


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AUTONOMOUS DECENTRALISED FMS

The basic components of ADFMS are listed below:

1. Several CNC Machine Tools

2. Robots,

3. Transportation systems(AGVs)

4. Computer systems

5. Controllers and

6. Warehouses.

Each of these componentscommunicates andexchanges their informationwhile they decide on what

action to perform next.

Controller

Controller

Controller

Controller

Computer

Computer

Computer

CNC M/C

Robot

CNC M/C

AGV

LAN


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ALGORITHM FOR FUTURE ANTICIPATIVE REASONING

IN AUTONOMOUS DECENTRALISED FMS

In the autonomous decentralized system, the AGV routing is

generated by several decision making subsystems.

The original problem is decomposed into an individual

routing problem for each AGV.

In this paper, a technique for anticipating the next action of

AGV is proposed.

This includes an advance prediction of action in a few steps,

which will be able to enhance the efficiency condition of the

overall FMS.

In this way, we develop an Algorithm for Future Anticipative

Reasoning (AFAR) of the next action decision of AGV.


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MODEL OF AD FMS STUDIEDThe AD-FMS consists of multiple

agents inside a factory that is shown

in figure.The agent can be divided into a parts

warehouse, product warehouse,

transportation systems for material

handling (AGV) and several MCs.

The movement of the AGV inside the

FMS is restricted on the dashed linegrid with equal speeds.

The MCs can machine several types

of parts

The machining time for each type of

machining process is fixed.

Moreover, there also exist multiple

types of MC that can perform the

same machining task. The similar

types of MC are represented as MC1,

MC2, etc.

Each MC in these groups is identified

by MC1-1, MC1-2, etc.


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MODEL OF AD FMS STUDIED

The information exchange and cooperation between each agent

in this AD FMS is described as follows:

The AGV transmits the information of what type of part and

where it is going,

the parts warehouse transmits the information of what type ofpart that it prepares,

the MC transmits the information of what type of part that is

currently machined and the time remaining to finish the

machining process.

All the information that is transmitted is taken by the needed

agent as materials to perform the next action.


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ALGORITHM OF HYPOTHETICAL REASONING

What is Hypothetical Reasoning?

Considering different assumptions in order to see what

follows from them. In other words, reasoning about

alternative possible worlds (i.e., states of the world),

regardless of their resemblance to the actual world.

The AFARs real-time production scheduling is done by using

2 types of hypothetical reasoning:

1. Action Decision Hypothetical Reasoning (ADHR) that

decides where the AGV will move to.

2. Part Input Hypothetical Reasoning (PIHR) that decides

the kinds of parts to be input onto the production floor.


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OPERATION CONDITIONS OF AGV

The operating condition of AGV is eternally broadening like a tree

structure, where the node is assumed as the next AGV action.


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PROPOSED HYPOTHETICAL REASONING PROCESS Step1: The existing AGV hypothesis

depth is set as 0. Step2: For the next hypothesis

depth, if the selected branch

is FALSE, then the farthest

left side branch is selected

and assumed to be TRUTH. Step3: Run simulation to the

selected branch.

Step4: Based on the simulation

result, the selection branch is

judged whether it is TRUTHor not.

Step5: If the simulation result is

FALSE, then go to STEP 6. If it

is TRUTH, then go to STEP 8.


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PROPOSED HYPOTHETICAL REASONING PROCESS

Step6: The branch to the rightis then selected and

assumed to be TRUE,

and go to Step 3.

Step7: Go up to another

depth of hypothesis. Step8: If the hypothesis is a

set value then go to

Step 9, if not go to

Step 2.

Step9: If the selection branch

becomes TRUE, then

STOP.


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ANTICIPATING THE AD-FMS CONDITIONS

We propose a novel idea of forecasting future conditions in the

AD-FMS. The terms that define AFAR are given below:

1. Standard of TRUTH/FALSE judgments.

2. Function of machine selection priority [M(MCN)].

3. Function of parts warehouse selection priority [Fp ].

4. Function of product warehouse selection priority [Ff].

5. Value of part selection priority [V(n)].6. Value of Task Decentralisation [Fd (MCN)].


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STANDARD OF TRUTH/FALSE JUDGMENTS

From the result of IHS that shows the operation rates of the

AD-FMS, we can judge whether the hypothetical reasoning

has any contradictions or not based on the following 6

standards.

If the standard is not achieved, then it is judged that a

contradiction has occurred.

[Std 1]: Total MC operation rates are above 75%




[Std 5]: Total AGV operation rates are above 50%

[Std 6]: Total AGV operation rates are above 0%


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FUNCTION OF MACHINE SELECTION PRIORITY

The MC with higher selection priority means that it still has

many tasks remaining and is given a top priority to be selected

as TRUTH.


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FUNCTION OF PART WAREHOUSE SELECTION PRIORITY

Where,

max.parts.N : Maximum number of possible part input

AllProPt : Numbers of all parts at AGV or MC

destination.N : Total numbers of destinations, i.e., AGV, MC,

parts and product warehouse.

It is a value of determining the number of parts that are under

machining or transferring process,


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FUNCTION OF PRODUCT WAREHOUSE SELECTION

PRIORITY

Ff= destination.N Fp

Where,

destination.N : Total numbers of destinations, i.e., AGV, MC,

parts and product warehouse.

Fp : Function of Part Warehouse Selection Priority.


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VALUE OF PART SELECTION PRIORITY

Where,

TotalProT(n) : Total time for processing part n

ProRate(n) : Production rates of product n

CompPt(n) : Numbers of product n that have completed

machining process

AllCompPt : Numbers of all that have completed

machining process

ProPt(n) : Numbers of part n at AGV or MC

AllProPt : Numbers of all parts at AGV or MC


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VALUE OF TASK DECENTRALIZATION

where,

MC.Efficiency : Operation rates of MCN(%)

A MC with a lower production rate has a higher value of task decentralization,

that results in the MC to be selected easier.


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ALGORITHM FOR FUTURE ANTICIPATIVE

RESPONSE (AFAR) FOR PART INPUT

Algorithm for parts input and AGV Decision:Step 1: Add one depth to the hypothesis depth.

Step 2: Calculate part selection order V(n).

Step 3: Select the branch with the highest value for V(n).

Step 4: Calculate M(MCN), Fp , Ffand Fd for the selected branch.Step5: The node with the maximum values of M(MCN) is

regarded as TRUE. AGV has to move towards that node,

collect the part and take it to the machine having

highest value of Fd. Add one depth to the hypothesis depth.

Step6: If the value of M(MCN) is less than zero then select the

branch with the next highest value of V(n) and go to Step 4. If

all branches are completed go to Step 7.

Step 7: Stop.


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AGV WITH INTELLIGENT KNOWLEDGE (AGV-wIK)

In this paper, AGVs are considered as intelligent agents that are

able to adopt knowledge, transmit their information to each otherand understand mutually.

If one AGV can understand the behavior of another AGV, it is

possible to avoid collision, and to cooperate in their tasks.

Here, we define each AGV as having 6 types of intelligent

knowledge:

1. Routing knowledge

2. Self knowledge

3. Others knowledge

4. Answer knowledge

5. Avoidance knowledge.

6. Sending knowledge

Long Term Memory

Short Term Memory


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APPLICATION OF AFAR IN OUR NEIGHBOURHOOD

This concept gains importance as the International ContainerTransshipment Terminal at Vallarpadam is looking forward to

automation of cargo handling. The proposed VISL is also planning to provide the same facility.

AGVs have been successfully employed for material handling in manyports worldwide.

AFAR is applicable for AGVs employed in container terminals.

The incorporation of AFAR will dramatically improve the prospects ofthese projects.

Vallarpadam ICTT

Railway line to Vallarpadam

exclusively for container movement


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APPLICATION IN CONTAINER TERMINALS

Here we have ExportStorage, Gate BufferStorage and Train BufferStorage instead of PartWarehouses.

Product Warehouse isreplaced by ImportStorage.

The cargo movementsare actuated by AGVs.

Huge volumes of cargocan be handled byincorporating thistechnique.


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CONCLUSION

The branch of automation is witnessing major

advancements.

In this paper, a technique was proposed to anticipate the

next action of AGV, which will improve the efficiency of

Autonomous Decentralized Flexible Manufacturing System

(AD-FMS) Environment. We have also discussed on how to apply this technique in

automated container terminals.

AFAR will be a milestone in the field of logistics.


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REFERENCE

This presentation was based on a research paper published in World

Academy of Science, Engineering and Technology Journal 09/2007 issue


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OTHER REFERENCES

1. www.wikipedia.com

2. M. P. Groover, Automation, Production System and

Computer Integrated Manufacturing

3. P Radhakrishnan, S Subramanian, V Raju, CAD/CAM/CIM
http://www.wikipedia.com/http://www.wikipedia.com/


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Questions?


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Thank You

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Afar for Agv in Adfms