Lecture Business statistics in practice (7/e): Chapter 17 - Bowerman, O'Connell, Murphree

Chia sẻ: Fff Fff | Ngày: | Loại File: PPT | Số trang:14

Thêm vào BST

Báo xấu

55
lượt xem 2
download

Download Vui lòng tải xuống để xem tài liệu đầy đủ

Chapter 17 - Process improvement using control charts. After mastering the material in this chapter, you will be able to: Discuss the principles and importance of quality improvement, distinguish between common causes and assignable causes of process variation, sample a process by using rational subgrouping.

Chủ đề:

Bình luận(0) Đăng nhập để gửi bình luận!

Lưu

Nội dung Text: Lecture Business statistics in practice (7/e): Chapter 17 - Bowerman, O'Connell, Murphree

Chapter 17 Process Improvement Using Control Charts McGrawHill/Irwin Copyright © 2014 by The McGrawHill Companies, Inc. All rights reserved.
Process Improvement Using Control Charts 17.1 Quality: Meaning and Historical Perspective 17.2 Statistical Process Control and Causes of Variation 17.3 Sampling a Process, Rational Subgrouping and Control Charts 17.4  and R Charts 172
Process Improvement Using Control Charts Continued 17.5 Comparison of a Process with Specifications: Capability Studies 17.6 Charts for Fraction Nonconforming 17.7 Cause and Effect, Defect Concentration Diagrams (Optional) 173
LO17-1: Discuss the principles and importance of quality improvement. 17.1Quality: Meaning and Historical Perspective Quality ◦Fitness for use ◦Extent to which customer expectations are met Types of quality ◦Quality of design ◦Quality of conformance ◦Quality of performance 174
LO17-1 History of the Quality Movement 1924 Statistical Quality Control/Control Charts, Shewart/Bell Telephone 1920’s Statistical Acceptance Sampling, Bell Telephone 1946 American Society for Quality Control created 1950 W. Edwards Deming introduces statistical quality control in Japan 1951 Deming Prize established in Japan 1980’s Total Quality Management (TQM) 1988 Malcolm Baldrige National Quality Awards established 1990’s ISO 9000, international quality standards adopted 175
LO17-2: Distinguish between common 17.2 Statistical Process Control and Causes causes and assignable causes of process variation. of Process Variation Historical inspection approach ◦Inspection of output ◦Action on output  Scrap, rework, downgrade (expensive!) Statistical process control ◦Monitor and study process variation ◦Goal: Continuous process improvement ◦Preventing by quality through process improvement 176
LO17-2 Causes of Process Variation Common causes ◦Typical (random) variation inherent in process design ◦Process in statistical control Assignable causes ◦Unusual process variation ◦Intermittent or permanent process changes ◦Not common to all process observations ◦Process not in statistical control 177
LO17-3: Sample a process by using rational subgrouping. 17.3 Sampling a Process and Rational Subgrouping and Control Charts Must decide which process variables to study ◦Best to study a quantitative variable  This means we are employing measurement data We will take a series of samples over time ◦Usually called subgroups ◦Usually of size two to six ◦Usually observed over a short period of time Want to observe often enough to detect important process changes 178
LO17-3 Control Charts A control chart employs a center line, upper control limit and lower control limit The center line represents average performance The upper and lower control limits are established so that when in control almost all plot points will be between the limits 179
LO17-4: Use  and R charts to establish process control. 17.4  and R Charts  and R charts are the most commonly used control charts for measurement data ◦ chart plots subgroup means versus time ◦R chart plots subgroup range versus time  chart monitors the process mean R chart monitors the amount of variability These two charts must be used together 1710
LO17-5: Detect the presence of assignable causes through pattern Pattern Analysis analysis. An observation beyond the control limits indicates the presence of an assignable cause Other types of patterns also indicate the presence of an assignable cause These patterns are more easily described in terms of control chart zones ◦A, B, C 1711
LO17-6: Decide whether a 17.5 Comparison of a Process with process is capable of meeting specifications. Specifications: Capability Studies  Natural tolerance limits for a normally distributed process in statistical control will contain about 99.73 percent of the process observations and is given by R R R x 3 x 3 , x 3 d2 d2 d2  If the natural tolerance limits are inside the process specification limits, we say that the process is capable of meeting specifications 1712
LO17-7: Use p charts to monitor process quality. 17.6 Charts for Fraction Nonconforming Sometimes we inspect items and simply decide if they conform to standards or not ◦Nonconforming: does not meet standards  Defective ◦Conforming: meets standards Use a p chart Observe subgroups of n units over time ◦Determine the number nonconforming 1713
LO17-8: Use diagrams To discern the causes of quality problems (Optional). 17.7 CauseandEffect Concentration Diagrams (Optional) A causeandeffect diagram for “why tables are not cleared quickly in a restaurant” Also known as Ishikawa diagrams or fishbone charts Figure 17.26 1714