04 Statistical Process Control

No description available.

Statistical Process Control :Statistical Process Control Douglas M. Stewart, Ph.D. The Anderson Schools of Management The University of New Mexico

Quality Control (QC) :Quality Control (QC) Control – the activity of ensuring conformance to requirements and taking corrective action when necessary to correct problems Importance Daily management of processes Prerequisite to longer-term improvements

Designing the QC System :Designing the QC System Quality Policy and Quality Manual Contract management, design control and purchasing Process control, inspection and testing Corrective action and continual improvement Controlling inspection, measuring and test equipment (metrology, measurement system analysis and calibration) Records, documentation and audits

Example of QC: HACCP System :Example of QC: HACCP System Hazard analysis Critical control points Preventive measures with critical limits for each control point Procedures to monitor the critical control points Corrective actions when critical limits are not met Verification procedures Effective record keeping and documentation

Inspection/Testing Points :5 Inspection/Testing Points Receiving inspection In-process inspection Final inspection

Receiving Inspection :6 Receiving Inspection Spot check procedures 100 percent inspection Acceptance sampling

Acceptance Sampling :7 Acceptance Sampling

Pros and Cons of Acceptance Sampling :Pros and Cons of Acceptance Sampling Arguments for: Provides an assessment of risk Inexpensive and suited for destructive testing Requires less time than other approaches Requires less handling Reduces inspector fatigue Arguments against: Does not make sense for stable processes Only detects poor quality; does not help to prevent it Is non-value-added Does not help suppliers improve

In-Process Inspection :9 In-Process Inspection What to inspect? Key quality characteristics that are related to cost or quality (customer requirements) Where to inspect? Key processes, especially high-cost and value-added How much to inspect? All, nothing, or a sample

Economic Model :10 Economic Model C1 = cost of inspection and removal of nonconforming item C2 = cost of repair p = true fraction nonconforming Breakeven Analysis: p*C2 = C1 If p > C1 / C2 , use 100% inspection If p < C1 / C2 , do nothing

Slide 11:Human Factors in Inspection complexity defect rate repeated inspections inspection rate Inspection should never be a means of assuring quality. The purpose of inspection should be to gather information to understand and improve the processes that produce products and services.

Gauges and Measuring Instruments :12 Gauges and Measuring Instruments Variable gauges Fixed gauges Coordinate measuring machine Vision systems

Examples of Gauges :Examples of Gauges

Slide 14:Metrology - Science of Measurement Accuracy - closeness of agreement between an observed value and a standard Precision - closeness of agreement between randomly selected individual measurements

Repeatability and Reproducibility :Repeatability and Reproducibility Repeatability (equipment variation) – variation in multiple measurements by an individual using the same instrument. Reproducibility (operator variation) - variation in the same measuring instrument used by different individuals

Repeatability and Reproducibility Studies :Repeatability and Reproducibility Studies Quantify and evaluate the capability of a measurement system Select m operators and n parts Calibrate the measuring instrument Randomly measure each part by each operator for r trials Compute key statistics to quantify repeatability and reproducibility

Reliability and Reproducibility Studies(2) :Reliability and Reproducibility Studies(2)

Reliability and Reproducibility Studies(3) :Reliability and Reproducibility Studies(3)

R&R Constants :R&R Constants

R&R Evaluation :R&R Evaluation Under 10% error - OK 10-30% error - may be OK over 30% error - unacceptable

R&R Example :R&R Example R&R Study is to be conducted on a gauge being used to measure the thickness of a gasket having specification of 0.50 to 1.00 mm. We have three operators, each taking measurement on 10 parts in 2 separate trials.

Calibration :Calibration Calibration - comparing a measurement device or system to one having a known relationship to national standards Traceability to national standards maintained by NIST, National Institute of Standards and Technology

Statistical Process Control (SPC) :24 Statistical Process Control (SPC) A methodology for monitoring a process to identify special causes of variation and signal the need to take corrective action when appropriate SPC relies on control charts

Slide 25:Common Causes Special Causes

Slide 26:Histograms do not take into account changes over time. Control charts can tell us when a process changes

Control Chart Applications :27 Control Chart Applications Establish state of statistical control Monitor a process and signal when it goes out of control Determine process capability

Commonly Used Control Charts :28 Commonly Used Control Charts Variables data x-bar and R-charts x-bar and s-charts Charts for individuals (x-charts) Attribute data For “defectives” (p-chart, np-chart) For “defects” (c-chart, u-chart)

Developing Control Charts :Developing Control Charts Prepare Choose measurement Determine how to collect data, sample size, and frequency of sampling Set up an initial control chart Collect Data Record data Calculate appropriate statistics Plot statistics on chart

Next Steps :Next Steps Determine trial control limits Center line (process average) Compute UCL, LCL Analyze and interpret results Determine if in control Eliminate out-of-control points Recompute control limits as necessary

Typical Out-of-Control Patterns :36 Typical Out-of-Control Patterns Point outside control limits Sudden shift in process average Cycles Trends Hugging the center line Hugging the control limits Instability

Shift in Process Average :Shift in Process Average

Identifying Potential Shifts :Identifying Potential Shifts

Cycles :Cycles

Trend :Trend

Final Steps :Final Steps Use as a problem-solving tool Continue to collect and plot data Take corrective action when necessary Compute process capability

Process Capability :Process Capability Capability Indices

Process Capability (2) :Process Capability (2)

Capability Versus Control :44 Capability Versus Control

Process Capability Calculations :Process Capability Calculations

Excel Template :Excel Template

Special Variables Control Charts :Special Variables Control Charts x-bar and s charts x-chart for individuals

Charts for Attributes :Charts for Attributes Fraction nonconforming (p-chart) Fixed sample size Variable sample size np-chart for number nonconforming Charts for defects c-chart u-chart

Control Chart Selection :64 Control Chart Selection Quality Characteristic variable attribute n>1? n>=10 or computer? x and MR no yes x and s x and R no yes defective defect constant sample size? p-chart with variable sample size no p or np yes constant sampling unit? c u yes no

Control Chart Design Issues :65 Control Chart Design Issues Basis for sampling Sample size Frequency of sampling Location of control limits

Pre-Control :67 Pre-Control

SPC Implementation Requirements :68 SPC Implementation Requirements Top management commitment Project champion Initial workable project Employee education and training Accurate measurement system