# Operations Management Unit 7: Managing Quality (2) 授課教師： 國立臺灣大學工商管理學系 黃崇興 教授 本課程指定教材為 Operations Management: Processes and Supply Chains, 10th ed., Lee.

## Presentation on theme: "Operations Management Unit 7: Managing Quality (2) 授課教師： 國立臺灣大學工商管理學系 黃崇興 教授 本課程指定教材為 Operations Management: Processes and Supply Chains, 10th ed., Lee."— Presentation transcript:

Operations Management Unit 7: Managing Quality (2) 授課教師： 國立臺灣大學工商管理學系 黃崇興 教授 本課程指定教材為 Operations Management: Processes and Supply Chains, 10th ed., Lee J. Krajewski, Larry P. Ritzman, and Manoj K Malhotra, Pearson Education, ©2013 本講義僅引用部分內容，請讀者自行準備。 1 【本著作除另有註明外，採取創用 CC 「姓名標示 －非商業性－相同方式分享」台灣 3.0 版授權釋出】創用 CC 「姓名標示 －非商業性－相同方式分享」台灣 3.0 版

Six Sigma Improvement Model 2 p.185 Figure 5.4

Acceptance Sampling 3 Acceptable quality level (AQL) p.185

Acceptance Sampling Interface 4 p.186 Figure 5.5

Statistical Process Control (SPC) 5 Performance measurement  Variables  Attributes Sampling Sampling distributions p.186, 187

Sampling Statistics 6 Sample Mean Standard deviation where σ = standard deviation of a sample x i = observation of a quality characteristic (such as time) n = total number of observations = mean parameter 參數 statistic 統計值 s

Sample and Process Distributions 7 p.188 Figure 5.6

Causes of Variation 8 p.188 Common causes Assignable causes

Assignable Causes 9 p.189 Figure 5.7 (c) (d) 峰度 Kurtosis

Control Charts 10 Time-ordered diagram of process performance  Mean  Upper control limit  Lower control limit Steps for a control chart p.189

Control Limits and Sampling Distribution 11 p.189 Figure 5.8 Nominal 應然值

Control Charts - Normal 12 p.190 Figure 5.9

Control Chart Errors 13 Two types of error are possible with control charts  A type I error occurs  A type II error occurs p.190

Variable Control Charts (1) 14 UCL R = D 4 R and LCL R = D 3 R where R =average of several past R values and the central line of the control chart D 3, D 4 =constants that provide three standard deviation (three-sigma) limits for the given sample size R-Chart

Variable Control Charts (2) 15 UCL x = x + A 2 R and LCL x = x – A 2 R x -Chart where x =central line of the chart, which can be either the average of past sample means or a target value set for the process A 2 =constant to provide three-sigma limits for the sample mean

Calculating Control Chart Factors 16 p.191 Table 5.1

Example 5.1 Using x- and R-Charts 17 p.192, 193

An Alternate Form 18 UCL x = x + z σ x and LCL x = x – zσ x where σ x = σ / n σ = standard deviation of the process distribution n = sample size x = central line of the chart z = normal deviate number p.193

EXAMPLE 5.2 Using Process Standard Deviation 19 p.194

Control Charts for Attributes 20 p = the center line on the chart UCL p = p + zσ p and LCL p = p – zσ p and p-charts p.194, 195

EXAMPLE 5.3 Using a p-Chart 21 p.195, 196

Control Charts for Attributes 22 p.196 UCL c = c + z  c and LCL c = c – z  c c-charts The mean of the distribution is c and the standard deviation is  c

EXAMPLE 5.4 Using a c-Chart 23 p.197

Process Capability 24 p.197, 198 Figure 5.14, 5.15 板書圖示： 綠線表示顧客要求規格； 廠商的規格若為： ※藍線 → 不符合規格， ※黃線 → 符合規格。

Process Capability Index 25 C pk = Minimum of, x – Lower specification 3σ Upper specification – x 3σ where σ = standard deviation of the process distribution p.198

Process Capability Ratio 26 C p = Upper specification – Lower specification 6σ p.199

Determining Process Capability 27 4 Steps p.199

Determining Process Capability Step 4. 28 C pk The process is capable. Continue to monitor the output. Calculate C p Process variability is fine and management should focus on centering the process. Management should focus on reducing the variability in the process until it passes the test Acceptable Unacceptable Acceptable

EXAMPLE 5.5 Assessing Process Capability 29 p.200

Quality Engineering 30 p.199, 200

Quality Loss Function 31 p.201 Figure 5.16

International Quality Documentation Standards 32 ISO 9001:2008 ISO 14000:2004 ISO 26000:2010 Benefits of ISO Certification p.201, 202

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