6/9/2015 ieng 486: statistical quality & process control 1 ieng 486- lecture 01 introduction to...

04/18/23IENG 486: Statistical Quality &

Process Control 1

IENG 486- Lecture 01

Introduction to Statistical Process Control

04/18/23 IENG 486: Statistical Quality & Process Control 2

Agenda

Introductions Learning Objectives Materials Expectations Questions & Issues Data Collection


IENG 486

Instructor: D. H. Jensen

322 Civil Mechanical Bldg (605) 394 – 1278 [email protected]

Office Hours: M, W, F: 8:30 – 9:30 AM http://webpages.sdsmt.edu/~djensen/Schedule

Class Meetings: Monday, Wednesday, Friday: 11:00 – 11:50 CB 204E


Background

Academic: Industrial & Manufacturing Engineering

Oregon State University Ph.D. Industrial Engineering

University of Iowa M.A. Technology - Supervision & Management

University of Northern Iowa B.S. Computer Engineering

Iowa State University


Background

Industry Experience: Land Surveying Crew Data Systems Manager

Programmer Network Engineering

Plant Engineering Manufacturing

Engineering Design Engineering Hazardous Waste

Management

Plant Administration 7 plants, 3 towns

Consulting Commercial Avionics Medical Supplies Naval Fleet

Maintenance Facilities Die Cast Foundry Farm Toys Semiconductor Fab Aging Aircraft Repair


Learning Objectives

Students will demonstrate: a knowledge of the philosophy of quality – terms,

dimensions, the linkage between quality and productivity, and strategies for implementing quality systems.

a knowledge of the fundamentals of statistical process control – chance and assignable causes, the meaning of statistical control, average run length (ARL), operating characteristic (OC) curve, the principles of rational subgroup formation, and runs tests.


Learning Objectives

Students will demonstrate: the ability to construct, implement and interpret X-

bar and R control charts for variables from standards or data; and the ability to use the corresponding OC and ARL curves.

the ability to construct, implement and interpret p, c, and u control charts for attributes from standards or data; and the ability to use the corresponding OC and ARL curves.


Learning Objectives

Students will demonstrate: the ability to construct, implement and interpret

EWMA control charts for individual measurements from standards or data; and the ability to use the corresponding OC and ARL curves.

the ability to calculate and apply process capability ratios: Cp, Cpk, Cpm; and to perform a gage capability study – calculating the components of variability due to product, measurement error and its’ components (repeatability and reproducibility of the gage).


Learning Objectives

Students will demonstrate: a knowledge of acceptance sampling principles and

the ability to design, implement, and use acceptance sampling plans for attributes, variables; and military standards.

a knowledge of the principles of making physical measurements – equipment operation, calibration; to develop and document a measurement methodology; and the ability to operate calipers,and a micrometer.


Materials

Textbook: Montgomery, D. C. (2005). Introduction to

Statistical Quality Control (6th ed).

New York NY: John Wiley & Sons.

ISBN 978-0-470-16992-6 (required)


Materials

Required: Engineering Problems Paper – 8-1/2" x 11",

three hole drilled, ruled five squares/division, 50 pp. (approx.).

Engineering Notebook – 9-3/4" x 7-1/2", 5x5 quad-ruled, 80-100 pp. (approx.).


Materials

Recommended: Mechanical pencil – 0.5 mm, HB or B lead

with comfortable grip

Plastic-based eraser (clickable pen-style suggested)

Engineering/Scientific calculator.


Expectations

Grading Scale:A 90% B 80% C 70% D 60%

F < 60%

Weighting: Homework 25% Midterm Exam I 25% Midterm Exam II 25% Final Exam 25% Bonus Pts 5%


Expectations

Assignments & Laboratories: Each question / lab component is graded on a 10

point basis. Each assignment is equally weighted.

Exams: Exams are open Engineering notebook; and closed

textbook and homework. Necessary tables are NOT ALWAYS provided.


Reference Tables & Software

Online References Materials Page Download & print out

Textbook Photocopy for your reference, only

Follow copyright / acceptable use guidelines

Software Materials page

Copy & download to your machine Work ONLY with your copy Be able to do the calculations manually, too


Expectations

Due Dates / Late Work: Assignments are due at the start of class on the

due date (see Schedule page).

Late assignments will receive 50% of the earned credit until 24 hours have passed, and will be graded and returned at instructor convenience. Work submitted more than 24 hours past the due date will not be accepted.


Expectations

Make-up Work: Make-Up work is the student’s responsibility, and is

arranged at the lecturer’s discretion. Policies:

Foreseeable Circumstances - contact the lecturer as far in advance as possible (e-mail).

Unforeseeable Circumstances - contact the lecturer as soon as practical (leave phone message).

Note that it is NOT possible to arrange a make-up FINAL for anything other than University approved circumstances (medical, disability, multiple exams).


Expectations

Academic Honesty: OK to work together on HW

as long as what appears on your sheet is your work, your words, and your writing

Exams are always individual work


Questions & Issues

Students with special needs or requiring special accommodations should contact the instructor, Dr. Jensen, at 394-1278 and/or the campus ADA coordinator, Jolie McCoy, at 394-1924 at the earliest opportunity.


Data Collection

Name Course IDPreferred name Term / YearSDSM&T E-mail address

Your majorWhat you did during summer Hometown

Anything else the instructor should know about you


Next Class

Red Bead Experiment Meet by Archway

If weather is too bad, meet at classroomBring sunglasses / caps if sunny

No notes necessary Class participation is required

The experience is important Will take most of the time – be on-time!

6/9/2015 ieng 486: statistical quality & process control 1 ieng 486- lecture 01 introduction to...

Documents

quality systems

meaning of statistical

process capability ratios

e slide

philosophy of quality

u control charts

r control charts

ewma control charts