Fracture Mechanics 3 - Applied Quality Control

This third book of a 3-volume set on Fracture Mechanics adds a pragmatic and supportive character to the previous volumes by focusing on case studies using corrected exercises that teachers, students or engineers will find extremely useful. Due to the wide themes approached in this series, it can also be used to organize work in this field in a new way, as well as in the maintenance of industrial plants.
Several cases of sampling plans and their applications in industry are presented, as well as several solved case studies on the main indicators of capability according to ISO/TS 16949, ISO 8258 and FORD.
This book distinguishes itself from other works in the field through its originality in presenting an educational approach which aims at helping practitioners both in academia and industry. It is intended for technicians, engineers, designers, students, and teachers working in the fields of engineering and vocational education. The main objective of the author is to provide an assessment of indicators of quality and reliability to aid in decision-making. To this end, an intuitive and practical approach, based on mathematical rigor, is recommended.

List of contents

Preface爄x
Glossary爔vii
Chapter 1. Quality Control�/b>
1.1. Introduction to statistical process control�/p> 1.2. Classical tolerancing and quality control�/p> 1.2.1. ISO norms in quality control�/p> 1.2.2. QS9000 approach�/p> 1.2.3. Capabilities of CNOMO E41.36.110.N control means�/p> 1.2.4. Some capability indicators according to ISO/TS 16949, ISO 8258 and FORD 10
1.2.5. Metrological audits�
1.3. The Pareto law - ABC method�
1.3.1. Practical application�
1.3.2. Malfunction spread over 16 so-called "nevralgic" points�
1.4. Lot inspection by attributes�
1.4.1. Areas on which lot inspection operates�
1.4.2. (np) chart for controlling the number of defects�
1.4.3. (c) card to control the number of defects�
1.4.4. Average lot quality after control�
1.4.5. Choosing a sample plan�
1.4.6. Wald plan case study�
1.4.7. Average long-term controlled quantity�
1.4.8. Case study of a simple sampling plan�
1.4.9. Poisson distribution of cumulative probabilities�
1.5. Theoretical basics of control by measurement�
1.5.1. Choosing a simple sampling plan�
1.5.2. Choosing a simple or double sampling plan�
1.6. Analysis of process capability�
1.6.1. Capability indices for a normally distributed variable: X (�, �)�
1.6.2. Machine capability Cm and Cmk�
1.7. Capability for a non-normal distribution�
1.8. Control by measurement charts�
1.8.1. Size of the samples to be taken and the frequency of control�
1.8.2. Factor for control of X (mean) and range (R)�
1.9. Production and reception control�
1.9.1. Machine adaptation with respect to production tolerances 64
1.9.2. Proportion of faulty units�
1.10. Control charts�
1.10.1. Control by measurements charts for the mean and the range R�
1.10.2. Calculating control limits and case study�
1.10.3. Study of /R control charts - quality control lab�
1.10.4. Graphical representation of the rejections due to non-conformity to TI�
1.10.5. Performance case study: Capabilities�
1.10.6. Calculating machine capability indices: Cm and Cmk�
1.11. Conclusion�
1.12. Bibliography�
Chapter 2. Quality Control Case Studies�
2.1. The tools of quality, as per W. Deming�
2.2. Failure modes, effects and criticality analysis�
2.3. Total productive maintenance method�
2.4. The LMMEM "5M" process method�
2.5. Estimations of times in mechanical productions (machining) 94
2.5.1. Optimizing times and costs in mechanical production�
2.6. Stock management and supply methods�1
2.6.1. Hypothesis of a general method to improve stock management�3
2.7. Short summary of control charts�6
2.7.1. The various control charts�7
2.7.2. Measurement control charts - stability control charts (Shewhart)�8
2.7.3. Estimating �and 򠩿19
2.7.4. Efficiency - chart of the average�0
2.7.5. Control chart by attributes - determining the limits�1
2.8. CUSUM charts�3
2.8.1. EWM charts�4
2.8.2. Shewhart charts for the average, the range R and the standard deviation (s)�6
2.8.3. Control charts for the average and the range R�7
2.9. Individual control charts�0
2.9.1. Average lengths or CUSUM-Run�2
2.10. EWMA statistics - comparison between Shewhart graph control and the EWMA chart control techniques�3
2.10.1. Poisson normal distribution approximation�8
2.10.2. Decision limits of the X / R control chart through the SPC method�1
2.11. Main statistical tests used in quality control 144
2.11.1. So-called "Henry Line" or probability diagram test 144
2.12. Partial conclusion�9
2.13. Bibliography�9
Chapter 3. Case Studies�3
3.1. Quality control case study: calculating and plotting efficiency curves in simple/double control�3
3.1.1. Simple binomial distribution�3
3.1.2. Calculation results�4
3.2. Calculating the efficiency curves of simple/double control�6
3.2.1. Calculation results�7
3.3. Calculating efficiency curves in double control: binomial distribution, double efficiency plan (Excel version) 159
3.3.1. Calculation results�9
3.4. Progressive control (Excel) 160
3.4.1. Calculating the acceptance and refusal curves in progressive control�0
3.4.2. Calculation results 161
3.4.3. Graph 162
3.4.4. Measurement acceptance test when sigma (�*) is known 163
3.4.5. Determining the efficiency curve and the acceptance limits 163
3.4.6. Acceptance: known standard deviation, sigma = 0.01�4
3.4.7. Measurement acceptance test when sigma* (SD) is known�5
3.4.8. Choosing a plan�6
3.4.9. Plot (Excel)�7
3.5. R&R study in quality control and dimensional metrology 168
3.5.1. R&R (EV Repeatability and AR reproducibility)�8
3.5.2. R&R study�9
3.6. X/S control chart study (average and standard deviation, � )�3
3.7. Case study: capability of a specific control method�8
3.7.1. Measurements from a digital micrometer�8
3.7.2. Definition drawing or clear picture�8
3.7.3. Table of the measurements taken using a digital micrometer (directly read the value from Caliper)牋 179
3.7.4. Table of calculation results (Excel and MathCAD) 180
3.8. Case study on type A and B uncertainties�1
3.8.1. Uncertainties guide to the expression of uncertainties in measurements (GUM) 181
3.8.2. Estimating the compound uncertainty UC�4
3.9. Case study: uncertainties�4
3.9.1. Uncertainty study as per GUM�5
3.9.2. Graph�0
3.10. Conclusion�0
3.11. Bibliography�1
Appendix 203
Index�7

About the author

Ammar Grous is Teacher of Mechanical Engineering at CéGEP de l'Outaouais (Academic College), Gatineau, Quebec, Canada.

Summary

This third book of a 3-volume set on Fracture Mechanics adds a pragmatic and supportive character to the previous volumes by focusing on case studies using corrected exercises that teachers, students or engineers will find extremely useful.

Product details

• Authors: A Grous, Ammar Grous, Ammar (CEGEP de l'Outaouais Grous
• Publisher: ISTE Ltd and John Wiley & Sons Inc
• Languages: English
• Product format: Hardback
• Released: 14.12.2012
• EAN: 9781848214422
• ISBN: 978-1-84821-442-2
• No. of pages: 288
• Dimensions: 163 mm x 241 mm x 20 mm
• Weight: 572 g
• Series: Mechanical Engineering and Sol; Mechanical Engineering and Sol
• Subject: Natural sciences, medicine, IT, technology > Technology > General, dictionaries