QUAL08001 2019 Statistical Process Control

General Details

Full Title

Statistical Process Control

Transcript Title

Statistical Process Control

Code

QUAL08001

Attendance

N/A %

Subject Area

QUAL - Quality Control

Department

MEMA - Mech and Manufact Eng

Level

08 - Level 8

Credit

05 - 05 Credits

Duration

Semester

Fee

€

Start Term

2019 - Full Academic Year 2019-20

End Term

9999 - The End of Time

Author(s)

JOHN DONOVAN

Programme Membership

SG_EADVA_E08 201900 Certificate in Advanced Lean Sigma Quality SG_EPOLY_K08 201900 Bachelor of Engineering (Honours) in Polymer Processing SG_EQLTY_K08 201900 Bachelor of Science (Honours) in Engineering in Quality Management and Technology SG_EPOLP_K08 202200 Bachelor of Engineering (Honours) in Polymer Process Engineering SG_EPOLY_K08 202200 Bachelor of Engineering (Honours) in Polymer Process Engineering SG_EPOLZ_K08 202400 Bachelor of Engineering (Honours) in Polymer Process Engineering SG_EPOLA_K08 202500 Bachelor of Engineering (Honours) in Polymer Process Engineering

Description

Provides the student with a comprehensive understanding and knowledge of the use of statistical methods and techniques for monitoring and controlling processes.

Learning Outcomes

On completion of this module the learner will/should be able to;

Use and apply the basic problem solving techniques of quality to analyse data.

Apply qualitative tools for problems solving, prioritising problems and improving processes.

Develop, plot and analyse both variable and attribute Shewhart control charts.

Construct and use a EWMA chart

Apply short run and standardised control charts.

Conduct process and gauge capability analysis and develop the capability indices.

Conduct acceptance sampling by attribute and by variable data using ANSI/ASQC Z1.4 and ANSI/ASQC Z1.9 respectively.

Apply skip-lot, continuous and chain sampling procedures.

Teaching and Learning Strategies

Real world examples, case studies and published peer reviewed papers will be utilised, where possible. Minitab statistical software will be used.

Module Assessment Strategies

Students will be required to complete two assignments.

Repeat Assessments

Module Dependencies

Prerequisites

MATH08005 201300 Statistics

Indicative Syllabus

Review of Quantitative Tools - Incl. The Seven Tools of Quality

Histograms: How to prepare and use a Histogram. Mean, Mode, Median. Meaning of variation.

Cause and Effect Diagrams : Making CE diagrams. How to use CE diagrams.

Check Sheets: Function of check sheets. Types and uses of check sheets.

Graphs : Types of graphs. How to make and use graphs.

Pareto Analysis : How to make and use a Pareto diagram. Inclusion of cost on y-axis.

Scatter Diagrams:How to make and use a scatter diagram. The meaning of correlation

Boxplots : How to make and use boxplots. Comparing batches of data using boxplots.

Stem-and-Leaf Displays :How to make and use stem-and-leaf displays to see patterns in data.

Review of Qualitative Tools

Brainstorming and Nominal Group Technique.

Affinity diagram - gathering and grouping ideas

Interrelationship Diagrams - looking for drivers and outcomes

Radar Chart - rating organisation performance

Force Field Analysis - positives and negatives of change

Tree Diagram - Mapping the tasks for implementation

Prioritisation matrices - weighing options

Control charts

Introduction to Statistical Process Control. Review of Common cause and Special cause variation and X-bar and R variable control chart. Attribute control charts i.e. p, np, c and u charts. Individual X and Moving Range charts. Average Run Length, Short Run SPC, Standardised Run Charts - both attribute and variable. EWMA charts. Group charts and multiple stream processes. SPC for Low Defect Environments. Six Sigma and the DMAIC process. 3.4 ppm with a 1.5 standard deviation shift.

Process and Guage Capability

Review of Cp, Cpk, Cpm, Pp and Ppk. Calculation of capability and performance indices. Measurement Systems Analysis.. Gauge capability studies. The components of measurement error - repeatability and reproducibility. Precision-to-Tolerance ratio. Use of X-bar and R method for determining gauge capability. Combination of linear dimensions.

Acceptance Sampling

Principles of Acceptance sampling. Single sampling plans and their associated OC curves. Use of statistical tables to develop both the sampling plan and the OC curve. Calculation of OC curve etc. using cumulative Poisson tables.

Lot formation considerations. Single, and double sampling plans. Calculation of Average Sample Numbers (ASN). Average Outgoing Quality (AOQ and AOQL), Average Total Inspected (ATI).

Sampling Standards

Detailed focus on ANSI/ASQC Z1.4 (Acceptance Sampling by Attributes). Acceptance sampling by Variables - detailed focus on ANSI/ASQC Z1.9. Skip Lot sampling. Continuous Sampling plans. Chain Sampling.

Coursework & Assessment Breakdown

Coursework & Continuous Assessment

20 %

End of Semester / Year Formal Exam

80 %

Coursework Assessment

	Title	Type	Form	Percent	Week	Learning Outcomes Assessed
1	Assignment work	Coursework Assessment	Assignment	20 %	OnGoing	1,2,3,4,5,6,7

End of Semester / Year Assessment

	Title	Type	Form	Percent	Week	Learning Outcomes Assessed
1	Final Exam - One written 2.5 hour paper	Final Exam	Closed Book Exam	80 %	End of Term	1,2,3,4,5,6,7,8

Full Time Mode Workload

Type	Location	Description	Hours	Frequency	Avg Workload
Lecture	Not Specified	Lecture	2	Weekly	2.00
Tutorial	Not Specified	Tutorial	2	Weekly	2.00
Independent Learning	UNKNOWN	Independent Learning	4	Weekly	4.00

Total Full Time Average Weekly Learner Contact Time 4.00 Hours

Part Time Mode Workload

Type	Location	Description	Hours	Frequency	Avg Workload
Lecture	Not Specified	Lecture	2.5	Weekly	2.50
Tutorial	Not Specified	Tutorial	0	Weekly	0.00
Independent Learning	UNKNOWN	Independent Learning	4	Weekly	4.00

Total Part Time Average Weekly Learner Contact Time 2.50 Hours

Required & Recommended Book List

Required Reading
2013 Statistical Quality Control John Wiley & Sons
ISBN 1118322576 ISBN-13 9781118322574

This Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.

Recommended Reading
2018-10-24 Statistical Process Control Routledge
ISBN 1138064262 ISBN-13 9781138064263

The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control - a practical guide in the mid-eighties. Then people were rediscovering statistical methods of 'quality control' and the book responded to an often desperate need to find out about the techniques and use them on data. Pressure over time from organizations supplying directly to the consumer, typically in the automotive and high technology sectors, forced those in charge of the supplying production and service operations to think more about preventing problems than how to find and fix them. Subsequent editions retained the 'took kit' approach of the first but included some of the 'philosophy' behind the techniques and their use. The theme which runs throughout the 7th edition is still processes - that require understanding, have variation, must be properly controlled, have a capability, and need improvement - the five sections of this new edition. SPC never has been and never will be simply a 'took kit' and in this book the authors provide, not only the instructional guide for the tools, but communicate the management practices which have become so vital to success in organizations throughout the world. The book is supported by the authors' extensive and latest consulting work within thousands of organisations worldwide. Fully updated to include real-life case studies, new research based on client work from an array of industries, and integration with the latest computer methods and Minitab software, the book also retains its valued textbook quality through clear learning objectives and end of chapter discussion questions. It can still serve as a textbook for both student and practicing engineers, scientists, technologists, managers and for anyone wishing to understand or implement modern statistical process control techniques.

Recommended Reading
2011-08-02 Statistical Methods for Quality Improvement John Wiley & Sons
ISBN 9780470590744 ISBN-13 0470590742

"In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools. The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures"--

Recommended Reading
2010-01-01 Understanding Statistical Process Control Spc Press
ISBN 0945320698 ISBN-13 9780945320692

Module Resources

Non ISBN Literary Resources

Journal Resources

URL Resources

Other Resources

None

Additional Information

None