Manufacturing System Design
for High Product Quality
Jingshan Li, Dennis E. Blumenfeld, Ningjian Huang
Robert R. Inman and Samuel P. Marin
Manufacturing Systems Research Lab
General Motors Research & Development Center
Warren, Michigan, USA
5th International Conference on Analysis of Manufacturing Systems
May 21 2005
Mayl 2005 • JL • 1
OUTLINE
1. Motivation
2. Manufacturing system design impacts quality
3. Research opportunities
4. Andon System
5. Repair and Rework System
6. Conclusions
May 2005 • JL • 2
1. MOTIVATION
 System design and quality management are important
elements in manufacturing industry.
 Substantial research efforts have been devoted to both
of them, but independently.
 Little research attention has been paid to investigate
the interactions between manufacturing system design
and product quality.
May 2005 • JL • 3
Product
Design
TQM
QFD
DFQ
Manufacturing
System Design
Manufacturing
System Validation
Manufacturing
Operation
?
TQM
Process capability
Tolerancing
TQM
SPC
JIT
Lot sizing
 Scarcity of research on attempting to improve quality
in manufacturing system design phase
 Does manufacturing system design impact quality?
May 2005 • JL • 4
2. MANUFACTURING SYSTEM
DESIGN IMPACTS QUALITY

Evidences from automotive industry:





Harbour report – quality and productivity are positively
correlated → improving production system can improve
quality.
American Axles & Manufacturing – quality improvement due
to production system changes, e.g., conveyor, inspection,
buffers, etc.
Ford/Jaquar – improve quality by adopting Toyota production
systems.
GM – strip out buffers to improve paint quality in paint shops.
Toyota – pay attention to production system’s impact on
quality, e.g., Andon, additional inspection stations, selected
stationary assembly stations, etc.
May 2005 • JL • 5

Experiments and analysis:





Ergonomics – poor workstation layout and high line speeds
may hurt quality performance of manual operations.
Andon system – stopping the line to fix every problem can
improve throughput of good jobs when average repair times
are short.
Repair and rework system – appropriate design of repair
subsystem can improve quality buy rate.
Verdict: Manufacturing system design does impact
product quality.
Largely unexplored area with promising opportunities
May 2005 • JL • 6
3. RESEARCH OPPORTUNITIES

Strategic issues:







Flexibility
Agility
Level of automation
Modularity
Outsourcing
Scalability
Emerging Technology

Tactic issues:











Andon
Assembly Line Movement
and Balancing
Batch Size
Buffer Location and Size
Centralized/Decentralized
Equipment
Feedback Loops
Inspection
Line or Machine Speed
Parallel versus Serial lines
Plant Layout
Repair and rework loops
May 2005 • JL • 7
4. ANDON SYSTEM


Andon – a visual control device to monitor quality
on assembly line.
The worker can pull the Andon cord to trigger a
light as a call for help, and stop the line if needed
to correct the problem.
May 2005 • JL • 8
 Current literature contains many popular articles
that are descriptive or provide qualitative studies of
Andon use.
 It is claimed and taken for granted that, in spite of
line stoppages and productivity loss, overall system
performance is improved.
 Why? Under what conditions?
May 2005 • JL • 9
 Two different Andon strategies:
 Empower workers to stop the line for every problem, so that
all jobs are corrected first time, or
 Encourage workers to reduce the number of Andon calls, so
that line only stops for severe problems.
 Which one is the right way?
May 2005 • JL • 10

WHY? WHEN? HOW?

Need for quantitative model to

analyze performance of a transfer production line with
Andon.

discover the conditions for successful Andon use.

investigate trade-offs between productivity and quality.
May 2005 • JL • 11
Model Formulation
m1
mk
m2
Andon cord
 Transfer line with k machines (m1, m2,..., mk) linked to one
Andon cord
 Performance index: Throughput of good quality jobs
May 2005 • JL • 12

Type of systems
 No Andon: Job moves to next machine at end of cycle, no
matter whether job has problem or not.
 Full Andon: If job has problem or is not complete at end of
cycle, Andon cord is pulled and line stops to allow extra time
for repair (up to a maximum time tm ).
 Partial Andon: If job has severe problem at end of cycle,
Andon cord is pulled and line stops to allow extra time for
repair (up to a maximum time tm ). If job has minor problem
at end of cycle, job moves to next machine.
May 2005 • JL • 13
Assumptions






Machines are synchronized (all jobs start work at the
same time) with identical cycle time c.
At end of cycle, each machine has fixed probability i
that job has defect or is not complete. A defective job
has probability ai to have a severe defect.
Repair (correspondingly, severe repair) times are
independent and exponentially distributed with
parameters i (correspondingly, i, and i < i), with
truncation at maximum time tm.
At most one Andon pull per cycle.
Independence of operations and quality failures.
May 2005 • JL • 14

One-machine case

Throughput of good quality job, G
1 
c
No Andon:
G 
Full Andon:
1  e   tm
G 
c  (  ) (1  e   tm )
Partial Andon:
1    a (1  e  tm )
G 
c  (a  ) (1  e  tm )
May 2005 • JL • 15
Illustration
c = 1,  = 0.25, a = 0.5
 = 0.9,  = 0.8
0.8
0.79
Throughput of
good jobs, G
Full Andon
0.78
(jobs per unit time) 0.77
Partial Andon
0.76
0.75
No Andon
0.74
0.73
0.72
0
1
2
3
4
Maximum extra time for repair, tm
May 2005 • JL • 16
5
Illustration
Throughput of Good Jobs, G
c = 1,  = 0.25, a = 0.5
 = 0.8,  = 0.7
0.8
0.8
0.79
0.79
0.78
0.78
0.77
0.77
Full Andon
0.76
 = 0.7,  = 0.5
0.76
0.75
No Andon
0.74
No Andon
0.75
0.74
0.73
Full Andon
0.73
0.72
Partial Andon
0.71
0.72
Partial Andon
0.71
0.7
0.7
0
1
2
3
4
5
0
1
Maximum extra time for repair, tm
May 2005 • JL • 17
2
3
4
5

Theorem: Under assumptions,

If  + cµ > 1, then
GNo Andon < GPartial Andon < GFull Andon

If  + c < 1 <  + cµ, then
GPartial Andon < GNo Andon < GFull Andon

If  + c <  + cµ < 1, then
GFull Andon
< GNo Andon
GPartial Andon < GNo Andon
May 2005 • JL • 18

Insights

Implementing Andon can improve throughput of good
quality jobs when average repair times are short (i.e.,
when repair rate is high).

Partial Andon is never the best strategy. Even when repair
times for severe defects are short, Full Andon is better
than Partial Andon.
Line Condition
Best Strategy
Short repair times
Long repair times
Full Andon
No Andon
May 2005 • JL • 19

Rules of thumb




If average repair time is less than the cycle time, then Full
Andon will improve throughput of good quality jobs.
If average time to repair severe defects is less than the
cycle time, then any type of Andon will improve throughput
of good quality jobs.
It is worth repairing all defects rather than severe ones
only.
Right way: Stop line for all problems.

Toyota: hundreds of Andons per shift with total line
stoppage time of 10-15 minutes.
May 2005 • JL • 20

Multiple machine case

Throughput of good quality job, G
k
No Andon:
GNo Andon 
 (1   )
i
i 1
k
k
 k

c  (1  i )   i  (1  i )
i 1
j 1, j  i
 i 1

k
k
 (1   )    (1  e
i
Full Andon:
GFull Andon 
i 1
i 1
 itm
i
k
)
 (1   )
i
j 1, j  i
 1  e  itm
c (1  i )   i  (1  i ) c 
i
i 1
i 1
j 1, j  i

k
k
k
k
k
 (1   )    a (1  e
i
Partial Andon: GPartial Andon 
i 1
i 1
i
i
 i t m



k
)
 (1   )
i
j 1, j  i
k
k
k
 k
 k
1  e  itm
c  (1  i )   i  (1  i )   ia i  (1  i )
i
i 1
j 1, j  i
j 1, j  i
 i 1
 i 1
May 2005 • JL • 21

Throughput of good quality job, G
No Andon:
Full Andon:
Partial Andon:
1 
G 
c1    k 
G 
G 
1    k (1  e   tm )
c1    k   k
(1e  tm )

1    ka (1  e  tm )
c1    k   ka (1e
May 2005 • JL • 22
 tm
)
k = 5, c = 1,  = 0.1, a = 0.5
 = 0.9,  = 0.8
Illustration
0.74
0.72
Full Andon
0.7
Throughput of
good jobs, G
(jobs per unit
time)
0.68
Partial Andon
0.66
No Andon
0.64
0.62
0.6
0
1
2
3
4
Maximum extra time for repair tm

Right way: Stop line for all problems.
May 2005 • JL • 23
5
5. REPAIR AND REWORK SYSTEM

Repair and rework systems are often used in many
manufacturing industries: automotive, electronics,
packaging, process, etc.

In automotive assembly plants, product quality is
typically characterized by

First Time Quality (FTQ): good job ratio of all first time
processed jobs

Quality Buy Rate (QBR): good job ratio of all jobs,
including first time jobs and reworked jobs.
May 2005 • JL • 24

Layout
New Jobs
Inspection
Confirmation
(OK Jobs)
Main
Line
Component
Replacement
Rework
Minor
Repair
May 2005 • JL • 25

Quality buy rate (Q):
nq1  nr qr
Q
,
n  nr
where n and nr are the numbers of first time jobs and reworked
jobs, respectively, q1 and qr are first time quality and rework
quality, respectively.
May 2005 • JL • 26

Observations:


Minor repair capacity is limited.
Jobs that only need minor repair will be routed to rework
when the minor repair capacity is insufficient.

Often qr < q1.

When qr < q1, we obtain Q < q1.

When minor repair capacity is insufficient, rerouting the
jobs needing minor repair to rework reduces the quality
buy rate of the main line.

In addition, it will waste more materials and resources and
lead to loss of throughput.
May 2005 • JL • 27

Need for a quantitative model to analyze quality buy
rate as a function of minor repair capacity

Analysis results show that quality buy rate can be
improved by appropriate design of minor repair
capacity

The study has been applied in an automotive paint
shop
May 2005 • JL • 28
 nq  n(q  qr )(1  a x  xg )  Nqr (  sg   sx  xg )
n(1  q )a r '
,
if
N

,

n

n
(
q

q
)(
1

a

)

N
(




)
1

(
1

q
)
a
'
r
x xg
sg
sx xg
r
r

Q

q  (q  qr )a r '
n(1  q )a r '
,
if
N

,

1

(
q

q
)
a
'
1

(
1

q
)
a
'

r
r
r
r
n(1  q)a r '
 na s ' (1  q )  N [1  (1  qr )a r ' ]
(
1





),
if
N

,
ss
sx xs

1  (q  qr )(1  a x  xg )
1  (1  qr )a r '

na  

n(1  q)a r '
0
,
if
N

,

1

(
1

q
)
a
'
r
r

a s  a x  xs
where
as '
,
1   ss   sx  xs
ar ' ar 
a s (  sr   sx  xr )  a x (  xr   xs  sr   ss  xr )
.
1   ss   sx  xs
May 2005 • JL • 29

Illustration:
FTQ
QBR
May 2005 • JL • 30
6. CONCLUSIONS

Quality is critical. Manufacturing system design does
have a significant impact on product quality.

Need to fully understand how it impacts quality and how
to incorporate quality with productivity and flexibility in
making manufacturing system design choices.

Lack of research makes it be a largely unexplored area
with promising research opportunities, valued and
important to industry.

Need to motivate research in the interactions between
manufacturing system design and product quality. It will
open a new area of manufacturing systems engineering.
May 2005 • JL • 31
Thanks

Prof. Chris Papadopoulos

Prof. Semyon Meerkov

Prof. Stanley Gershwin
May 2005 • JL • 32

Backups
May 2005 • JL • 33






Assembly line movement – how assembly line progress likely
affects quality as well as throughput. Synchronous or
asynchronous line? Stationary station or continuous moving
line?
Assembly line balancing – not only from the point of view of
worker utilization, but also to identify quality bottlenecks.
Plant layout – how layout affects quality? e.g., U - shaped lines
produce better quality products.
Number and location of inspection stations – integrated quality
and productivity model, information feedback, etc.
Number and location of rework loops – more rework loops or
less? What should capacity of each be?
Feedback loops – feedback from inspection, production data
analysis, etc.
May 2005 • JL • 34




Buffer location and size – buffer accommodate variation, lean
inventory contributes to quality, what are tradeoffs?
Parallel versus serial lines – Parallel line improves productivity,
but increases variations. It is difficult to trace root cause, but it
may help quality due to slower speed.
Centralize versus decentralized equipment – centralized
operations benefit from economic scale, better utilization and is
easier for quality control, decentralized operations are
responsible for dedicated assembly plants, have less logistic
cost, less inventory and quicker feedback from assembly.
Batch size – large batch may improve quality by avoiding
disruptive changeovers, small batch sizes allow quick defect
detection but have frequent changeovers.
May 2005 • JL • 35



Flexibility – e.g.: fixtures on machines (loading/unloading) or on
conveyors (improve throughput but more variability and
degraded repeatability and reproducibility), need to delineate
tradeoffs between cost, flexibility, throughput and quality for
different strategies.
Agility – producing multiple products add variability which may
damage quality, machine maintenance may require highly
trained labors to obtain high quality, need to achieve both agility
and quality without huge investment.
Level of automation – automatic operation provides better
quality, manual has more flexibility, need to understand impact
of automation on productivity, quality and flexibility.
May 2005 • JL • 36




Scalability – capacity expansion by speeding up or adding new
machines or plants? Single large machines/plants or many small
ones?
Modularity – easier for final assembler, but difficult to control,
what is the impact on quality?
Outsourcing – American automakers spin off parts divisions,
Toyota rarely hands complex modules to outside suppliers due
to quality concerns.
Emerging technology – how to take advantage of data
collection, communication, analysis capabilities and intelligent
agents to design production system for improved quality?
May 2005 • JL • 37
k
No Andon
GNo Andon 
 (1   )
i
i 1
k
k
 k

c  (1  i )   i  (1  i )
i 1
j 1, j  i
 i 1

k
k
 (1   )    (1  e
i
Full Andon
GFull Andon 
i 1
i 1
 itm
i
k
)
 (1   )
i
j 1, j  i
 1  e  itm
c (1  i )   i  (1  i ) c 
i
i 1
i 1
j 1, j  i

k
k
k
k
k
 (1   )    a (1  e
i
Partial Andon GPartial Andon 
i 1
i 1
i
i
 i t m



k
)
 (1   )
i
j 1, j  i
k
k
k
 k
 k
1  e  itm
c  (1  i )   i  (1  i )   ia i  (1  i )
i
i 1
j 1, j  i
j 1, j  i
 i 1
 i 1
May 2005 • JL • 38
 1  
GNo Andon  
 .
 1    k 
M
No Andon
Full Andon
GFull Andon 
 1    k  ke  tm

1    k

Partial Andon






,

1
1  e  t m
 c  c  kc  k
1    k 


,

k[2(1    k )(1  e  tm  t m e  tm )  k (1  e  tm ) 2 ]
c  c  kc  k (1  e  tm )
GPatial Andon 
where T 
CV 
M


1.67( M  1)CV
T 1 
 1  M  0.31CV  1.67 MN

2CV

where T 
CV 



 1    ka  kae tm

1    k




.
M


1.67( M  1)CV
T 1 
 1  M  0.31CV  1.67 MN

2CV







,

1
1  e tm
 c  c  kc  ka
1    k 


,

ka [2(1    k )(1  e tm  t me tm )  ka (1  e tm ) 2 ]
.
c  c  kc  ka (1  e tm )
May 2005 • JL • 39
0.8
0.79
0.78
0.77
0.76
0.75
0.74
0.73
0.72
3.
6
4.
2
4.
8
3
System with no
Andon
System with full
Andon
System with partial
Andon
0.
6
1.
2
1.
8
2.
4
0
0.9
1.2
Good Production Rate
One machine system
t_m
May 2005 • JL • 40
0.8
0.79
0.78
0.77
0.76
0.75
0.74
0.73
0.72
3.
6
4.
2
4.
8
3
System with no
Andon
System with full
Andon
System with partial
Andon
0.
6
1.
2
1.
8
2.
4
0
0.85
0.9
Good Production Rate
One machine system
t_m
May 2005 • JL • 41
0.8
0.79
0.78
0.77
0.76
0.75
0.74
0.73
0.72
3.
6
4.
2
4.
8
3
System with no
Andon
System with full
Andon
System with partial
Andon
0.
6
1.
2
1.
8
2.
4
0
0.7
0.9
Good Production Rate
One machine system
t_m
May 2005 • JL • 42
0.8
0.79
0.78
0.77
0.76
0.75
0.74
0.73
0.72
3.
6
4.
2
4.
8
3
System with no
Andon
System with full
Andon
System with partial
Andon
0.
6
1.
2
1.
8
2.
4
0
0.7
0.8
Good Production Rate
One machine system
t_m
May 2005 • JL • 43

Theorem: Under assumptions,

If (k-1)cµ +  + cµ > 1, then
GNo Andon < GPartial Andon < GFull Andon

If (k-1)c +  + c < 1 < (k-1)cµ +  + cµ, then
GPartial Andon < GNo Andon < GFull Andon

If (k-1)c +  + c < (k-1)cµ +  + cµ < 1, then
GFull Andon
< GNo Andon
GPartial Andon < GNo Andon
May 2005 • JL • 44


Rules of thumb

If average repair time is less than cycle time plus average
time within a cycle working on defective jobs, Full Andon
improves throughput of good quality jobs.

If average time to repair severe defects is less than cycle
time plus average time within a cycle working on defective
jobs, then any type of Andon will improve throughput of good
quality jobs.

It is worth repairing all defects rather than severe ones only.
Right way: Stop line for all problems.
May 2005 • JL • 45
Extensions

Non-identical machines

System with multiple Andon cords
Andon cord
Buffer
May 2005 • JL • 46
Andon cord

Assumptions:





A job can be reworked/repaired multiple times. No scrap.
Constant percentages of good quality jobs.
All reprocessed jobs have identical good job ratio.
All routing probabilities are constants.
Notation:



αx, αr, αs: routing probabilities after main line inspection.
βsx, βss, βsr, βxs, βxr: routing probabilities after minor repair
and component exchange.
N: minor repair capacity..
May 2005 • JL • 47

Need to develop a quantitative model to



analyze quality buy rate as a function of minor repair
capacity
design appropriate repair capacity to achieve desired
quality buy rate
investigate the trade-offs between investment costs and
saving from productivity and quality improvement
May 2005 • JL • 48

Theorem: Under assumption, the quality buy rate
can be calculated as:
 nq  n(q  qr )(1  a x  xg )  Nqr (  sg   sx  xg )
, if

 n  n(q  qr )(1  a x  xg )  N (  sg   sx  xg )
Q

q  (q  qr )a r '
,
if

1  (q  qr )a r '


N
n(1  q )a r '
,
1  (1  qr )a r '
N
n(1  q )a r '
.
1  (1  qr )a r '
a s  a x  xs
,
where
1   ss   sx  xs
a (    sx  xr )  a x (  xr   xs  sr   ss  xr )
a r '  a r  s sr
.
1   ss   sx  xs
as '
May 2005 • JL • 49

Corollary: Under assumptions, the quality buy rate
is monotonically increasing with respect to q, qr and
N (when minor repair capacity is insufficient).
FTQ
QBR
May 2005 • JL • 50

Corollary: Under assumptions, the number of rerouted
jobs can be calculated as:
 na s ' (1  q)  N [1  (1  qr )a r ' ]
(1   ss   sx  xs ), if

1  (q  qr )(1  a x  xg )

na  

0,
if


May 2005 • JL • 51
N
n(1  q)a r '
,
1  (1  qr )a r '
N
n(1  q)a r '
.
1  (1  qr )a r '

Corollary: Under assumptions, the number of rerouted
jobs is monotonically decreasing with respect to q, qr
and N (when the minor repair capacity is insufficient).
May 2005 • JL • 52