RESEARCH POSTER PRESENTATION DESIGN 2015
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48 secs
i. Linear (current practice): = 10 +
ii. Piece-wise Linear:
= 10 + , 20 + (10) ,
iii. Big M:
= 10 + ,,
n number of vehicles on an edge t time taken to travel an empty
edge e(n) time to traverse jammed edge with n vehicles
Routing of automated material handlingsystems (AMHS) vehicles in
wafer fabs.
Increasing number of FOUP pickup/delivery requests are
causing:
Increase in number of vehiclesIncrease in vehicle
congestionIncrease in wait time for FOUPs
1. HomogeneousSimulations:Equally probable pickup/delivery
requests.
2. HeterogeneousSimulations:Doubly probable pickup/delivery from
any one bay.
Pickup Protocols continued:
c. Reservation with ETA Policy:
Every scheduling cycle, busy vehicles withestimated time of
arrival under somethreshold, get reserved by lots in queuethat are
nearest to their current location(via current destination).
Any idle reserved vehicle is re-reserved bynearer lots in
queue.
d. Reservation without ETA Policy:
Same as Reservation with ETA excepttheres no ETA threshold.
INTRODUCTION TOOLS
OBJECTIVES
15 server (vehicle) stylized system Stable pickup request
arrival rate -
determined by trial and error Stability - vehicle utilization
98% Graphical system stability verification:
a. FIFO:Idle vehicle picks up a lot from the queuethat has
waited the longest.
b. Nearest Lot Policy:Pickup lot thats nearest in terms of
thetime an idle vehicle will take to travel to it.
METHODOLOGY (1/3) METHODOLOGY (3/3)
ONGOING WORK
Python simulate & test algorithms AutoCAD design stylized
fab
Microsoft Visio - Toy lattice networks for building &testing
simulator:
- Network representation of stylized fab
METHODOLOGY (2/3)
John J Hasenbein a, Shreya Gupta ba: Associate Professor,
[email protected]; b: PhD Candidate, [email protected];
OR/IE Group, Department of Mechanical Engineering, The University
of Texas at Austin
Improving Scheduling and Control of the OHTC Controller in Wafer
Fab AMHS Systems
Lot 10, 40 secs
Lot 11, 10 secs
Lot 12, 33 secs
Lot n, 27 secs
(Lots in queue
Time from vehicle 3)
, Sequence in which vehicles become idle
3
8
5
7
Lot 10, NA
Lot 11, NA
Lot 12, NA
Lot n, NA
(Lots in queue
Time from vehicle 3)
, Sequence in which vehicles become idle
3
8
5
7
Lot 10, 300 secs
Lot 11, 10 secs
Lot n, 27 secs
(Lots in queue
Time fromvehicle 3)
, Sequence in which vehicles become idle
3
8
7
1st reservation of vehicles with ETA under 4 mins
ETA, 3.3 mins
ETA, 3.7 mins
ETA, 1.0 min
Scheduling Cycle 1 (Cycle time = 3mins)
Lot 10, 28 secs
Lot 11, reserved
Lot n, 5 secs
(Lots in queue
Time from vehicle 8)
, Sequence in which vehicles become idle
3
8
7
2nd reservation of vehicles with ETA under 4 mins
ETA, reserved
ETA, 3.7 mins
ETA, 1.0 min
Lot 10, 400 secs
Lot 11, 10 secs
Lot 12, 330 secs
Lot n, 27 secs
(Lots in queue
Time from vehicle 3)
, Sequence in which vehicles become idle
3
1
9
7
1st reservation of vehicles with no ETA threshold
Scheduling Cycle 1 (Cycle time = 3mins)
Lot 13, 120 secs 8
Additional vehicles available for reservationbetween vehicles 3
& 8
No. of vehiclesthreshold
Tim
e
No. of vehiclesthreshold
Tim
e
Bay 125%
Bay 225%
Bay 425%
Bay 325%
Bay 150%
Bay 216.67%
Bay 316.67%
Bay 416.67%
PICKUP PROTOCOLS
PARAMETER ESTIMATION ROUTING ALGORITHMS
Symmetric & unidirectional
Asymmetric & bidirectional
No. of vehiclesthreshold
M
Tim
e
>
>
B
C
A
D
B
Sub-optimal route decidedusing the actual distancebetween nodes
D & B.
Optimal route decided usingstate dependent time (orcost) between
nodes D & B.
From ToA B 18 secs 0B C 18 secs 0C D 18 secs 0D B 18 secs 3B A
18 secs 1
Network State
Edges Edge Travel Time
48 secs36 secs
18 secs
State Dependent Edge Travel Time
18 secs18 secs
A
D C
36 secs
0.035
0.016
A B C D
H G F E
I J K L
0.005
0.015
0.007
0.019
0.013
0.010
0.006
0.005
0.023
0.002
0.007
0.012
0.014
0.020
0.007
0.014
0.013
0.004
0.022 0.0140.014 0.0030.011 0.0020.008
0.005 0.0120.020 0.0250.013 0.0080.015
A B C D
H G F E
I J K L
0.005 0.005 0.005
0.0050.005 0.005
0.0050.005 0.005
0.005 0.005 0.005 0.005
0.005 0.005 0.005 0.005
FAB CONTROLLER
MCS
OHTC
1 2 N
Improve throughput via better routingalgorithms for the over
hoist transportcontrol (OHTC) system.
Enhance state dependent cost functionsused in Dijkstra's
algorithm.
State of the network at time t is thenumber of vehicles on the
various edges ofthe network.
vehicles
Sheet1
EdgesEdge Travel TimeNetwork StateState Dependent Edge Travel
Time
FromTo
AB18 secs018 secs
BC18 secs018 secs
CD18 secs018 secs
DB18 secs348 secs
BA18 secs136 secs
Slide Number 1
