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Statistical Quality Control and Process Capability Analysis

30 Chapters
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01
Foundations of statistical quality control
quality characteristics, variability, specification limits, and the role of SQC in manufacturing and service systems.
Foundationsstatistical
02
Descriptive statistics for quality data
measures of central tendency, dispersion, skewness, kurtosis, and graphical summaries using histograms, box plots, and run charts.
Descriptivestatistics
03
Probability distributions in quality engineering
normal, binomial, Poisson, exponential, and Weibull models with applications to defect and failure data.
Probabilitydistributions
04
Sampling distributions and the central limit theorem
implications for control charting and process capability estimation.
Samplingdistributions
05
Introduction to control charts
common and special causes, rational subgrouping, and the Shewhart control chart framework.
rationalsubgrouping
06
Variables control charts for subgroups
X-bar and R charts, X-bar and S charts, construction, interpretation, and revision of control limits.
Variablessubgroups
07
Variables control charts for individual measurements
I-MR charts, moving range estimation, and applications in low-volume or continuous processes.
Variablesindividual
08
Attributes control charts
p, np, c, and u charts for defectives and defects, with variable sample size considerations.
Attributesdefectives
09
Control chart performance evaluation
average run length, false alarm rates, and detection capability for shifts in process mean and variance.
performanceevaluation
10
Specialized control charts
CUSUM, EWMA, and Shewhart charts with warning limits for detecting small and sustained process shifts.
SpecializedCUSUM
11
Process capability analysis fundamentals
capability versus performance, specification spread, and the relationship between control and capability.
capabilityanalysis
12
Capability indices for normally distributed processes
Cp, Cpk, Cpm, and Cpmk with confidence intervals and sample size effects.
Capabilitynormally
13
Capability analysis for non-normal data
transformations, Box-Cox method, Johnson distributions, and non-parametric alternatives.
Capabilityanalysis
14
Performance indices
Pp, Ppk, and their distinction from capability indices in the presence of process instability.
Performancedistinction
15
Gage repeatability and reproducibility (GR&R)
measurement system analysis, ANOVA method, and impact on capability assessment.
repeatabilityreproducibility
16
Process capability for attributes data
defect rate capability, binomial and Poisson capability metrics, and Six Sigma metrics.
capabilityattributes
17
Statistical process control implementation
control plan development, sampling frequency, out-of-control action plans, and operator involvement.
Statisticalimplementation
18
Phase I and Phase II control charting
establishing baseline control limits and monitoring future production.
chartingestablishing
19
Multivariate statistical process control
Hotelling T2 charts, multivariate EWMA, and fault detection in correlated processes.
Multivariatestatistical
20
Process monitoring with autocorrelated data
time series models, residual charts, and batch process monitoring.
monitoringautocorrelated
21
Design of experiments for process improvement
factorial, fractional factorial, and response surface methods in SQC context.
experimentsimprovement
22
Acceptance sampling
OC curves, AQL, LTPD, single, double, and sequential sampling plans, and MIL-STD-105E/ANSI Z1.4.
Acceptancesampling
23
Reliability and life testing
censoring, hazard functions, Weibull analysis, and reliability estimation from quality data.
Reliabilitycensoring
24
Statistical quality control in service and transactional processes
adapting control charts and capability analysis to non-manufacturing environments.
Statisticaltransactional
25
Software tools for SQC
Minitest, JMP, R, Python, and Excel for control charts, capability analysis, and GR&R studies.
SoftwareSQC
26
Case study
implementing SPC in a discrete parts manufacturing line, from data collection to capability improvement.
implementingSPC
27
Case study
process capability analysis for a chemical batch process with non-normal data and measurement uncertainty.
capabilityanalysis
28
Case study
reducing defects in an electronics assembly using attribute control charts and root cause analysis.
reducingelectronics
29
Advanced topics
profile monitoring, functional data analysis, and machine learning approaches for process monitoring.
Advancedmonitoring
30
Integrating SQC with Six Sigma, Lean, and quality management systems
DMAIC, control plans, and continuous improvement culture.
IntegratingSQC