Index

American Society for Quality (ASQ), 18

assignable cause variation, 18

C_p, 94

lean production, 7

normal distribution, 119

p-chart, 76

process capability, 22

statistical process control (SPC), 1

assignable cause variation, 17, 32, 40, 49

attributes, 51

control charts for, 75–87

binomial distribution, 76, 126app

buffer stocks, 7

Cananiano, Donna, 109

central line (CL), 31–32, 41–42, 53

of delta chart, 67

MR chart, 53

in p-chart, 78

sample size and, 72

in u-chart, 86

on x-bar, 57–58

certainty, 38

chance cause variation, 17

code value chart, 66

common cause variation, 32

continuous process improvement programs, 2f

continuous quality improvement (CQI) programs, 11

control charts, 2–3, 9, 10, 21

data collection for creating, 34

defined, 31

delta, 65–67

in finance, 114–115

formulas for calculating, 123app–124app

general form of, 31, 32f

general theory of, 32–35

in healthcare, 111–113

individual and moving range, 51–55

for individuals, 34f

nonrandom patterns, 42–43

out-of-control signal, 37–39, 45–46

process of creating, 34

for rare events, 109–110

in retail service, 113–114

run rules, 40–42

selection guide, 52f, 74f, 87f

for services, 110–115

signals, 37–43

single point rule, 38–40

with unequal sample size, 71–72

using software, 34–35

zone rules, 42

control limit calculations, 125t

costs, 8–10

count chart, 82–86

for fixed-size sample, 82

np-chart vs., 82–84

per unit (u-chart), 85–86

for varying sample size, 84–85

cross-functional team, 47

customer dissatisfaction, 5

customer satisfaction, 26

deadlines, 5–6

defective (nonconforming) product, 75–76

defects per million opportunities (DPMO), 103

delta-bar, 67

delta control charts, 65–67, 67f

delta statistic, 67t

Deming, W. Edwards, 7, 21

funnel experiment, 21, 22f

distributions, 117app–121app, 118f, 118t, 126–127

of individual observations, 122f

of sample means, 122f

DNOM chart, 66

economic data, 52

effective capacity, 3

empirical rule, 120, 121t

employee empowerment, 13–14

end-of-line inspection processes, 6

Esar, Evan, 23

exponentially weighted moving average (EWMA) chart, 69–70, 70f, 73, 123app–124app

forecasts, 1, 4–6

accuracy of, 5–6

perfection, 6

fraction defective chart. See proportion defective control chart

fraction nonconforming chart. See proportion defective control chart

garbage in; garbage out (GIGO) effect, 23

Guaspari, John, 89

heating, ventilating, and air conditioning (HVAC) system, 20

histogram, 117, 118f–119f, 126app

individuals, 121–123

individuals (I-chart), chart for, 51–52, 53f–54f, 55

inventory management, 7

just-in-time (JIT) inventory level, 7, 65

key performance indicators (KPI), 34

key quality characteristics (KQC), 34, 47, 55, 66, 71, 76, 107, 110

Lawson, Edward, 89

lean production, 8

lower control limits (LCL), 31–33, 40, 42, 53

in p-chart, 78–79

in u-chart, 86

on x-bar, 56–58

lower specification limit (LSL), 91, 97

mean, 123f, 127app

measurements per unit of time, 51–52

measurement variation, 23–29

accuracy and precision, 24

Maddie’s Weenie Stand, case example, 26–28f

measurement scales, 26

micrometers, 25

survey instruments, 26–28

validity and reliability for qualitative measurements, 26–29

Metro Park-and-Ride system, 23

Minitab 22f, 31, 35, 36f–37f, 41, 44, 59, 119, 129app, 130f

mixed model production, 65, 66f

mode, 117

moving range (MR) chart, 51–55, 70

National Institute of Standards and Technology (NIST), 24

near-real-time system, 10–11

nominal chart, 66

Nom-I-Nal chart, 66

nonconformities, 75–76

normal distribution, 33f, 119–120f, 127app

Northwest Analytical Quality Analyst (NWA QA) 6.3, 31, 39f, 81f, 101f, 129app, 131f

np-chart. See number-defective control chart

number-defective control chart, 80–82

count chart vs., 82, 83t, 84f

number of nonconformities chart. See count chart

outliers, 19

out-of-control signal on a control chart, 38–42

action plan for, 45, 46f

out-of-specification product, 99

parts per million (ppm), 103

parts per million defective (ppmd), 103

p-chart. See proportion defective control chart

percent chart. See proportion defective control chart

Poisson distribution, 127app

population standard deviation, 127app

predictability of SPC, 4

predictable processes, 3

process capability, 22–23, 89, 93f, 126app

for attributes data, 103–104

formulas for calculating, 124app–126app

measurement of, 90

for nonnormal distributions, 100, 101f, 101–103

one-sided specification limit, 99–100

for variable data, 90–99

process instability, 6

process operating in control, 89, 90f

process out of control, 37, 39f, 40, 41f, 42, 43f

process performance indices, 91

C_p, 91, 92t, 94, 97, 98f

C_pk, 97, 98f

C_pm, 98–99

process standard deviation, 122

process variation

control and minimization of, 12–13

in control or out of control, 18–23

operator-to-operator differences, 14

production schedules, 3–4

proportion defective control chart, 76–78, 78f, 80f, 103, 113f, 114f

in an injection molding operation, 76–78

for varying sample size leads, 79–80

Purchasing Managers Index (PMI), 52

quality control (QC), 6–7

random samples, 58

range, 118, 127app

range chart (R-chart), 55–61

rare events, 109–110

rational subgroup concept, 47

R-chart(s), 59t, 60f, 67f, 68, 96f

real-time SPC, 3

repeatability, 24

reproducibility, 24

return on investment (ROI), 10

risk, 38

run rules, 40–42

safety stocks, 7–8

sample means, 122–123

samples, 121–123

sample size, 47, 58, 123

control charts with variable, 71, 72t

p-chart for varying sample size leads, 79–80

sample standard deviation, 127app

sample statistics vs. process statistics, 122f

sampling, 59

frequency, 47

plans, 7, 59

s-chart, 57, 60, 61f

service quality, dimensions of, 108, 108t,

Shewhart, Walter, 17

single point out-of-control signal, 54

single point rule, 38–40

Six Sigma quality program, 103

special causes, 18

specifications, 31

standard deviation, 33, 119, 120f, 122, 123f, 127app

of individuals, 122f, 127app

of sample means, 122f, 127app

standard operating procedures (SOP) for actions, 14, 45, 78

statistical process control (SPC)

case example of hospitals, 11–12

control and minimization of variation in processes, 12–13

control charts used by, 2–3

costs and, 8–9

CQI programs and, 11–12

defined, 1

deployment of, 107

employee empowerment and, 13–14

forecasts and, 4–6

implementation in injection molding facility, 13, 76–78, 95t, 96f

implementing, 46–48

production schedules and, 3–4

quality control, 6–7

real-time, 3

significance of, 1

supply chain management and, 8

Universal Machining, implementation at, 68

supply chain management, 8

survey response scale, 111f

sustainable production rate, 3

Taguchi, Genichi, 12

Taguchi loss function, 12, 99

thermostat, 20–21

time series analysis, 4

u-chart, 84, 85t, 86f, 103

uncertainty, 1, 4

upper control limits (UCL), 31–33, 40, 42

on MR chart, 53

in p-chart, 78–79

in u-chart, 86

on x-bar, 56–58f

upper specification limit (USL), 91, 97

variables, 51

variation, 8. See also process variation

ASQ defined, 18

assignable cause, 17

chance cause, 17

examples of common cause, 17–18

in measurement, 23–29

shift-to-shift variation pattern, 43, 44f, 45

Weibull distribution, 101, 102f, 109

worker productivity, 19–20

x-bar charts, 55, 56f–58f, 59t, 60f–61f, 65, 71f, 94, 95t, 96f

zone rules, 42