The document discusses total quality management (TQM) and statistical quality control (SQC), noting that both views are important. It also examines the link between internal and external quality, describing how measures to improve internal quality will translate to higher external quality for customers. Statistical quality control involves three major areas: acceptance sampling, process control to monitor mean and variability, and design of experiments to determine the effect of controllable variables on quality.

1. TOTAL QUALITY
MANUFACTURING

2. Quality and Operations
• Two categories of Quality Literature
• Total Quality Management (TQM)
Focuses on quality in qualitative management terms
• Statistical Quality Control (SQC)
focuses on quality in quantitative engineering terms
(compliance with specs.)
• Both views are important
• All TQM with no SQC produces talk without substance -
all SQC with no TQM produces numbers without purpose

3. Quality and Operations
Link of Internal Quality to External Quality :
• Measures and controls for higher internal quality will be
translated to high external quality based on customer concerns
• Error prevention:
• fewer errors - fewer defects go out , "quality at the source"
• Inspection improvement:
• Quality assurance require inspect few to detect and reject or correct
items. More time to find Root cause.
• Net effect will be an upward quality spiral
• Environment enhancement.
• Environmental factors - Supportive management attitudes, tangible
rewards for improvements, sophisticated tracking and control systems,
and effective training can help to create environment

4. Quality and Operations
• Statistical Quality Control 03 major areas
• Acceptance sampling
• Process control
mean and variability of performance continuously
monitored to seek special problems or out of control
situations
• Design of experiments
Systematically vary controllable variables to determine
their effect on quality measures
Statistical tools: block designs, factorial designs, nested
designs, response surface analysis

5. Quality and Operations
• Effect of Cost on Quality
• Cost increase with Quality
Traditional industrial engineering view
"Optimal defect level"
• Cost decreases with Quality
TQM view- zero defects and continuous improvement
"doing things right the first time"
• Neither view is universally correct.
Question is how far market will pay for the increased
quality. Quality affects operations and operations affect
quality

6. Quality and Operations

7. Quality – Effects of rework
• Effect of rework
• Variability creates congestion
• Congestion increases non linearly with utilization
• It increases
• TT
• WIP
• Utilization

8. Quality – Effects of rework
Effective Processing Time: Total time taken to
produce a good part = te
U= ra x te

13. Quality – Effects of rework
• Effect of rework
1. Utilization increases nonlinearly with rework
rate
2. Variance of process time, given by σe
2
increases with rework rate. More unpredictable
the completion time
3. ce
2 may increase or decrease with rework rate,
depending on c0
2. (see the difference when
c0
2<1 and >1)

14. Quality – Effects of rework
• Law (Rework): For a given throughput level,
rework increases both the mean and standard
deviation of the cycle time of a process.
Let: to
deterministic,
c0=0 and ca=1

15. Quality – Effects of rework

16. Quality – Effects of rework

17. Quality Supports Operations
• Throughput effects. rework can be high enough to
cause a resource to become a bottleneck thus it can
substantially alter the capacity (highly cost effective to
improve quality in this line.)
• WIP effects. increased variability may require higher
WIP (and throughput time)
Reduction in rework can facilitate reductions in WIP.
• Lead time effects. additional WIP in the line lead to
longer average cycle times. Also increase the variability
of cycle times may require longer quoted lead times or
poorer service to the customer.
The competitive advantage can be increased through
shorter leadtimes and more reliable delivery.
P422

18. Quality Supports Operations
• Further observations
• the longer the rework loop, the more pronounced the
consequences
• Scrap loss is equivalent to rework loop of whole line.
• Scrap loss caused by variable yields is costly and
disruptive
P422

19. Operations Supports Quality
• In Deter. Q=0.05
curve high TH at
low WIP but high
scrap loss
• In Expo. Q=.05
max TH at
WIP=9
• q- probability of
machine
producing bad
part
P422

20. Problem
• Consider a single machine that requires 1 hour to
process parts. With probability p, a given part must
be reworked, which requires a second 1-hour pass
through the machine. However, all parts are
guaranteed to be good after a second pass, so none
go through more than twice.
• (a) Compute the mean and variance of the effective
processing time on this machine as a function of p.
• (b) Use your answer from (a) to compute the squared
coefficient of variation (SCV) of the effective
processing times. Is it an increasing function of p?
Explain. (FP 4)

21. Problem
Suppose a cellular telephone plant purchases electronic components
from various suppliers. For one particular component, the plant has a
choice between two suppliers: Supplier 1 has delivery lead times with a
mean of 15 days and a standard deviation of 1 day, while supplier 2
has delivery lead times with a mean of 15 days and a standard
deviation of 5 days. Both suppliers can be assumed to have normally
distributed lead times.
• Assuming that the cellular plant purchases the component on a lot-
for-lot basis and wants to be 99 percent certain that the component is
in stock when needed by the production schedule, how many days of
lead time are needed if supplier 1 is used? Supplier 2?
• How many days will a typical component purchased from supplier 1
wait in inventory before being used? From supplier 2? How might this
information be used to justify using supplier 1 even if it charges a
higher price?