Shop Floor Control
Even a journey of one thousand li begins with a single
step.
– Lao Tze
It is a melancholy thing to see how zeal for a good thing
abates when the novelty is over, and when there is no
pecuniary reward attending the service.
– Earl of Egmont
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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1
What is Shop Floor Control?
Definition: Shop Floor Control (SFC) is the process by which decisions
directly affecting the flow of material through the factory are made.
Functions:
WIP
Tracking
Status
Monitoring
Material Flow
Control
Capacity
Feedback
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Throughput
Tracking
Work
Forecasting
Quality
Control
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Planning for SFC
Gross Capacity Control: Match line to demand via:
• Varying staffing (no. shifts or no. workers/shift)
• Varying length of work week (or work day)
• Using outside vendors to augment capacity
Bottleneck Planning:
• Bottlenecks can be designed
• Cost of capacity is key
• Stable bottlenecks are easier to manage
Span of Control:
• Physically or logically decompose system
• Span of labor management (10 subordinates)
• Span of process management (related technology?)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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3
Basic CONWIP
Rationale:
• Simple starting point
• Can be effective
...
Requirements:
•
•
•
•
Constant routings
Similar processing times (stable bottleneck)
No significant setups
No assemblies
Design Issues:
• Work backlog – how to maintain and display
• Line discipline – FIFO, limited passing
• Card counts – WIP = CT  rP initially, then conservative
adjustments
• Card deficits – violate WIP-cap in special circumstances
• Work ahead – how far ahead relative to due date?
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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4
CONWIP Line Using Cards
CONWIP Cards
Production Line
Inbound
Stock
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Outbound
Stock
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Card Deficits
Jobs without Cards
Jobs with Cards
B
Bottleneck Process
Failed Machine
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Tandem CONWIP Lines
Links to Kanban: when “loops” become single process centers
Bottleneck Treatment:
• Nonbottleneck loops coupled to buffer inventories (cards are
released on departure from buffer)
• Bottleneck loops uncoupled from buffer inventories (cards are
released on entry into buffer)
Shared Resources:
• Sequencing policy is needed
• Upstream buffer facilitates sequencing (and batching if necessary)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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7
Tandem CONWIP Loops
Basic CONWIP
Multi-Loop CONWIP
Kanban
Workstation
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Buffer
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Card Flow
8
Coupled and Uncoupled CONWIP Loops
Bottleneck
CONWIP Loop
CONWIP Card
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Buffer
Material Flow
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Job
Card Flow
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Splitting Loops at Shared Resource
Routing A
Routing A
Routing B
Routing B
CONWIP Loop
Card Flow
Buffer
Material Flow
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Modifications of Basic CONWIP
Multiple Product Families:
• Capacity-adjusted WIP
• CONWIP Controller
Assembly Systems:
• CONWIP achieves synchronization naturally (unless passing is
allowed)
• WIP levels must be sensitive to “length” of fabrication lines
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
11
CONWIP Controller
Work Backlog
Indicator Lights
PN
–—
–—
–—
–—
–—
–—
–—
–—
–—
–—
–—
–—
–—
Quant
–––––
–––––
–––––
–––––
–––––
–––––
–––––
–––––
–––––
–––––
–––––
–––––
–––––
LAN
R G
PC
PC
...
Workstations
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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CONWIP Assembly
Processing Times
for Line A
2
1
4
1
Processing Times
for Line B
3
Buffer
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
3
2
3
Card Flow
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Assembly
Material Flow
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Kanban
Advantages:
• improved communication
• control of shared resources
Disadvantages:
• complexity – setting WIP levels
• tighter pacing – pressure on workers, less opportunity for work
ahead
• part-specific cards – can’t accommodate many active part numbers
• inflexible to product mix changes
• handles small, infrequent orders poorly
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Kanban with Work Backlog
Backlog
——
——
——
——
——
——
——
——
——
Material Flow
Card Flow
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Standard Container
Card
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Pull From the Bottleneck
Problems with CONWIP/Kanban:
• Bottleneck starvation due to downstream failures
• Premature releases due to CONWIP requirements
PFB Remedies:
• PFB ignores WIP downstream of bottleneck
• PFB launches orders when bottleneck can accommodate them
PFB Problem:
• Floating bottlenecks
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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16
Simple Pull From the Bottleneck
B
Material Flow
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
Card Flow
17
Routings in a Jobshop
Backlog
1 ---------2 ---------3 ---------4 ---------5 ---------. ……….
. ……….
. ……….
. ……….
m ---------. ……….
. ……….
. ……….
ASSEMBLY
BOTTLENECK
1 2
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
3
4
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Implementing PFB
Notation:
bi  The time required on the bottleneck by job i on the backlog.
 i  The average time after release required for job i to reach the bottleneck .
L  The specified time for jobs to wait in the buffer in front of the bottleneck .
Work at Bottleneck: total hours of work ahead of job j is
j 1
b
i 1
i
Job Release Mechanism: Release job j whenever
j 1
b
i
j L
i 1
Enhancement: establish due date window, before which jobs are not
released.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
19
Production Tracking
Short Term:
• Statistical Throughput Control (STC)
• Progress toward quota
• Overtime decisions
Long Term:
• Long range tracking
• Capacity feedback
• Synchronize planning models to reality
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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20
STC Notation
R length of regular ti me
 mean production during regular ti me
 standard deviation of regular ti me production
Q production quota
N t production in [0, t ]
Yn
time to make quota in n th regular ti me period
S
mean time to make quota, E[Yn ]
S
std dev of time to make quota, Var (Yn )
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
Note: we might
have these instead
of  and , if we
stop when quota
is made.
21
STC Mechanics
Assumption: Nt is normally distributed with mean t/R and variance 2t/R.
Implications:
• Nt - Qt/R is normally distributed with mean ( - Q)t/R and variance 2t/R.
• NR-t is normally distributed with mean (R - t)/R and variance 2(R - t)/R.
• If Nt = nt, where nt - Qt/R = x, we will miss quota only if NR-t < Q - nt.
Formula: The probability of missing quota by time R given an overage of x is
P( N R t  Q  nt )  P( N R t  Q  x  Qt R)
 P ( N R t  Q ( R  t ) R  x )
 (Q   )( R  t ) R  x 

 


 (R  t) R


© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
22
STC Charts
Motivation: information “at a glance”
Computations: Pre-compute the overage levels that cause the
probability of missing quota to be a specified level a:
 (Q   )( R  t ) R  x 
 a



 (R  t) R


• which yields
x   (  Q)( R  t ) R  za ( R  t ) R
• where za is chosen such that (za) = a.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
23
STC Chart (Q=)
Probability of Missing Quota by End of Regular Time
4000
3000
Overage (nt-St)
2000
1000
0
0
2
4
6
8
10
12
14
16
-1000
-2000
-3000
-4000
Time
5%
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
25%
50%
75%
95%
Actual-Quota
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STC Chart (Q<)
Probability of Missing Quota by End of Regular Time
2000
1000
0
Overage (nt-St)
0
2
4
6
8
10
12
14
16
-1000
-2000
-3000
-4000
-5000
-6000
Time
5%
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
25%
50%
75%
95%
Actual-Quota
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25
Long-Range Tracking
Statistics of Interest:
• , mean production during regular time
• 2, variance of regular time production
Observable Statistics: if we stop when quota is achieved, then instead
of  and  we observe
• S, mean time to make quota
• 2S, variance of time to make quota
Conversion Formulas: If he have S and S, then we can smooth these
(as shown later) and then convert to  and  by using

© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
RQ
S
,
 S2 RQ 2
 
 S3
2
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Smoothing Capacity Parameters
Mean Production:
ˆ (n)  aYn  (1  a )( ˆ (n  1)  Tˆn 1 )
Tˆ (n)  b ( ˆ (n)  ˆ (n  1))  (1  b )Tˆ (n  1)
• where a and b are smoothing constants.
Production Variance:
ˆ 2 (n)  g (Yn  ˆ (n)) 2  (1  g )ˆ 2 (n  1)
• where g is a smoothing constant.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
27
LR Tracking - Mean Production
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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28
Smoothed Trend in Mean Production
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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29
LR Tracking - Std Dev of Production
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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30
Shop Floor Control Takeaways
General:
• SFC is more than material flow control (WIP tracking, QC, status
monitoring, … )
• good SFC requires planning (workforce policies, bottlenecks,
management, … )
CONWIP:
• simple starting point
• reduces variability due to WIP fluctuations
• many modifications possible (kanban, pull-from-bottleneck)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
31
Shop Floor Control Takeaways (cont.)
Statistical Throughput Control (STC);
• tool for OT planning/prediction
• intuitive graphical display
Long Range Tracking:
• feedback for other planning/control modules
• exponential smoothing approach
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
http://www.factory-physics.com
32