10 1 Quality Control Operations Management William J

10 -1 Quality Control Operations Management William J. Stevenson 8 th edition

10 -2 Quality Control CHAPTER 10 Quality Control Mc. Graw-Hill/Irwin Operations Management, Eighth Edition, by William J. Stevenson Copyright © 2005 by The Mc. Graw-Hill Companies, Inc. All rights reserved.

10 -3 Quality Control Phases of Quality Assurance Figure 10. 1 Inspection before/after production Acceptance sampling The least progressive Inspection and corrective action during production Process control Quality built into the process Continuous improvement The most progressive

10 -4 Quality Control Inspection Figure 10. 2 How Much/How Often · Where/When · Centralized vs. On-site · Inputs Acceptance sampling Transformation Process control Outputs Acceptance sampling

10 -5 Quality Control Inspection Costs Cost Figure 10. 3 Total Cost of inspection Cost of passing defectives Optimal Amount of Inspection

10 -6 Quality Control Where to Inspect in the Process · Raw materials and purchased parts · Finished products · Before a costly operation · Before an irreversible process · Before a covering process

10 -7 Quality Control Examples of Inspection Points Table 10. 1

10 -8 Quality Control · Statistical Process Control: Statistical evaluation of the output of a process during production · Quality of Conformance: A product or service conforms to specifications

10 -9 Quality Control Chart · Purpose: to monitor process output to see if it is random · A time ordered plot representative sample statistics obtained from an on going process (e. g. sample means) · Upper and lower control limits define the range of acceptable variation

10 -10 Quality Control Chart Figure 10. 4 Abnormal variation due to assignable sources Out of control UCL Mean Normal variation due to chance LCL Abnormal variation due to assignable sources 0 1 2 3 4 5 6 7 8 9 Sample number 10 11 12 13 14 15

10 -11 Quality Control Statistical Process Control · The essence of statistical process control is to assure that the output of a process is random so that future output will be random.

10 -12 Quality Control Statistical Process Control · The Control Process · Define · Measure · Compare · Evaluate · Correct · Monitor results

10 -13 Quality Control Statistical Process Control · Variations and Control · Random variation: Natural variations in the output of a process, created by countless minor factors · Assignable variation: A variation whose source can be identified

10 -14 Quality Control Sampling Distribution Figure 10. 5 Sampling distribution Process distribution Mean

10 -15 Quality Control Normal Distribution Figure 10. 6 Standard deviation Mean 95. 44% 99. 74%

10 -16 Quality Control Limits Figure 10. 7 Sampling distribution Process distribution Mean Lower control limit Upper control limit

10 -17 Quality Control Charts for Variables generate data that are measured. · · Mean control charts · Used to monitor the central tendency of a process. · X bar charts Range control charts · Used to monitor the process dispersion · R charts

10 -18 Quality Control Mean and Range Charts Figure 10. 10 A (process mean is shifting upward) Sampling Distribution UCL Detects shift x-Chart LCL UCL R-chart LCL Does not detect shift

10 -19 Quality Control Mean and Range Charts Figure 10. 10 B Sampling Distribution (process variability is increasi UCL x-Chart LCL Does not reveal increase UCL R-chart Reveals increase LCL

10 -20 Quality Control Chart for Attributes · p-Chart - Control chart used to monitor the proportion of defectives in a process · c-Chart - Control chart used to monitor the number of defects per unit Attributes generate data that are counted.

10 -21 Quality Control Use of p-Charts Table 10. 3 · When observations can be placed into two categories. · Good · Pass or bad or fail · Operate · or don’t operate When the data consists of multiple samples of several observations each

10 -22 Quality Control Use of c-Charts Table 10. 3 · Use only when the number of occurrences per unit of measure can be counted; nonoccurrences cannot be counted. · Scratches, chips, dents, or errors per item · Cracks or faults per unit of distance · Breaks or Tears per unit of area · Bacteria or pollutants per unit of volume · Calls, complaints, failures per unit of time

10 -23 Quality Control Use of Control Charts · At what point in the process to use control charts · What size samples to take · What type of control chart to use · Variables · Attributes

10 -24 Quality Control Process Capability · Tolerances or specifications · · Process variability · · Range of acceptable values established by engineering design or customer requirements Natural variability in a process Process capability · Process variability relative to specification

10 -25 Quality Control Process Capability Figure 10. 15 Lower Specification Upper Specification A. Process variability matches specifications Lower Specification Upper Specification B. Process variability Lower Upper well within specifications Specification C. Process variability exceeds specifications

10 -26 Quality Control Process Capability Ratio specification width Process capability ratio, Cp = process width Cp = Upper specification – lower specification 6

10 -27 Quality Control 3 Sigma and 6 Sigma Quality Upper specification Lower specification 1350 ppm 1. 7 ppm Process mean +/- 3 Sigma +/- 6 Sigma

10 -28 Quality Control Improving Process Capability Simplify · Standardize · Mistake-proof · Upgrade equipment · Automate ·

10 -29 Quality Control Limitations of Capability Indexes 1. Process may not be stable 2. Process output may not be normally distributed 3. Process not centered but Cp is used

10 -30 Quality Control CHAPTER 10 Additional Power. Point slides contributed by Geoff Willis, University of Central Oklahoma.

10 -31 Quality Control Charts in General Are named according to the statistics being plotted, i. e. , X bar, R, p, and c · Have a center line that is the overall average · Have limits above and below the center line at ± 3 standard deviations (usually) · Upper Control Limit (UCL) Center line Lower Control Limit (LCL)

10 -32 Quality Control Variables Data Charts · Process Centering X bar chart · X bar is a sample mean · · Process Dispersion (consistency) R chart · R is a sample range ·

10 -33 Quality Control X bar charts Center line is the grand mean (X double bar) · Points are X bars · -OR-

10 -34 Quality Control R Charts Center line is the grand mean (R bar) · Points are R · D 3 and D 4 values are tabled according to n (sample size) ·

10 -35 Quality Control Use of X bar & R charts Charts are always used in tandem · Data are collected (20 -25 samples) · Sample statistics are computed · All data are plotted on the 2 charts · Charts are examined for randomness · If random, then limits are used “forever” ·

10 -36 Quality Control Attribute Charts · c charts – used to count defects in a constant sample size

10 -37 Quality Control Attribute Charts · p charts – used to track a proportion (fraction) defective

10 -38 Quality Control Process Capability The ratio of process variability to design specifications Natural data spread -3σ -2σ -1σ µ +1σ +2σ +3σ Lower Upper Spec The natural spread of the data is 6σ

10 -39 Quality Control Training MQ 4 Job rotation/quality fatigue at Honda

10 -40 Quality Control Quality Measurement STA 10 Monitoring

10 -41 Quality Control Services/Measurement STAO 3 Survey/Efficiency, Admission/Discharge