SPC

STATISTICAL PROCESS CONTROL TRAINING

Dear Quality Professional,

Do you know your SPC?  Don't lose money due to poor statistical analysis.  With our SPC training you could learn the skills to interpret and employ the valuable data in which you have invested time and resources; producing meaningful savings in your processes.  Join us for this opportunity to learn about SPC from a statistical expert, Donald S. Holmes, President, Stochos, Inc.

Trainer 

Don Holmes is currently President of Stochos Incorporated which he founded in 1968.  He is widely recognized as an authority in the field of applying mathematics and statistics to manufacturing operations.  He has more than fifty years experience in industry, graduate and undergraduate teaching and government.  He has published (and continues to publish) many papers in professional journals related to applications in the area of Statistical Process Control (SPC).  These papers have led, in turn, to the development and marketing of Stochos' technical software products.  The newest of these products is the ProActive Process Improvement system.  This system provides for dynamic on-line statistical analysis of a database that integrates laboratory data, PLC data and other factory floor data for the purpose of providing improved plant optimization.

Mr. Holmes' experience includes:

One year in the role of Quality Engineer for General Electric's corporate quality systems consulting group.

Nine years as Business Logician for a General Electric Operations Research team at the Large Steam Turbine Generator Department.  In this position he was responsible for mathematical and statistical analysis projects for finance, manufacturing, marketing and engineering components of that department.  

Professor at many colleges and universities including: Union College (Schenectady, N.Y.), State University of New York (Albany, N.Y.), Rensselaer Polytechnic Institute (Troy, N.Y.), Georgia Institute of Technology ( Atlanta , Georgia ) and Emory University ( Atlanta , Georgia ).  He taught courses, primarily at the graduate level, in Operations Research, Operations Management, Quality Control, Statistics, Decision Theory and Strategic Planning.  While at Union College he was responsible for establishing the Operations Research and Statistics Program and the Health Studies Program.  He supervised many Master's and Ph.D. students working in the area of statistical analysis.  The most recent thesis involved the use of statistical control principles to the analysis of the economic effect of changes in tax laws of the state of New York .

Mr. Holmes has participated in several large cost reduction projects over the last few years.  One of the projects saved a company approximately one million dollars annually by decreasing the number of rebuild cycles of a major machine from twice a year to once a year.  Another project added 50% to the life of the lining of steel ladles, which produced savings of approximately one hundred thousand dollars per year per ladle.  The third project demonstrated the ability to save a quarter of a million dollars annually with decreased energy costs - with no deleterious effect on quality.  It was also shown that the throughput of the system could be increased with no added capital investment.

He is a Fellow of the American Society for Quality and serves on the Editorial Board of Quality Engineering.  He has co-authored more than 50 articles in the field of statistical process control and has received several prestigious awards from regional and local sections of ASQ.  He has been active in local and regional section management activities or ASQ for many years. 

Mr. Holmes is a regular member of the faculty of the Center for Professional Advancement.  In this capacity he developed and is the course director for their course "Statistical Process Control: Basics and Advanced Topics for the Chemical Process, Pharmaceutical and Allied Industries."  This course is given once a year in the Netherlands and once a year in the U.S.A.   The students are mature engineers of wide assortment of degrees - BS to Ph.D.  He also serves as a member of the CFPA advisory board.

He is active as a consultant and trainer in a variety of chemical, pharmaceutical and related industries.

Ø      Descriptive Statistics

Ø      Characterizing the Frequency Curve

Ø      Measure of Process Center

Ø      Measures of Curve Width

Ø      Other Measures of Process Width

Ø      Divide by n or Divide by n-1?

Ø      MSSD approach 

Ø      Which Standart Deviation

Ø      Symmetry -  Another Curve Characteristic

Ø      Peakedness of the Curve

Ø      The Normal Curve

Ø      Several % Points to Remember

Ø      Stability

Ø      Using the MSSD to Check for Process Stability

Ø      Review and Amplify Meaning of Specifications

Ø      A Process Capability Measure and One More “Standard Deviation”

Ø      Comparison of Desired Process Width With Observed Process Width

Ø      Other Process Performance Measures

Ø      Relationship of Measures

Ø      One Sided Specs and Performance Measures

Ø      Non-Normal Distributions

Ø      Sampling Distributions

Ø      SAMPLE versus UNIVERSE

o       Sampling Distribution for Sample Averages

o       Here’s what could happen to AVERAGES of samples of size two

o       Here’s what could happen to VARIANCES of samples of size two (using n-1)

Ø      CONTROL CHARTS

o       Potential Risks In Use Of Control Charts

o       The Usual Risk Selection and Some Other Rules

o       More About Risk

o       Average Run Length As A Risk Assessment Tool

o       Average Run Length and the Number of Rules Used

Ø       XBAR CHARTS

o       How to Make an XBAR  Chart

o       Continuing the Control Limit Calculation

Ø      Standard Deviation Charts

Ø      The General Control Chart Approach

Ø      Other Control Charts for VARIABLES

Ø      X And Moving Range Chart

Ø      Moving Range Charts

Ø      Moving Xbar Charts

Ø      Exponentially Weighted Moving Average Charts (EWMA)

Ø      CuSum Control Charts

Ø      The Run Sum Chart

Ø      Short Run Charts

Ø      To Make a Z chart

Ø      Two Related Variables

Ø      The Linear Model

Ø    Method of Least Squares

Ø      Correlation Coefficients

Ø      Another Definition of r 2

Ø      The Correlation Matrix

Ø      Dispersion Matrix

Ø    A Control Chart for Two Correlated Variables (T^2)

Ø      T² for Two Variables

Ø    Attributes Charts

o       P Charts

o       NP Charts

o       C Charts

o       U Charts

Ø      Process Acceptance Charts

o       The Upper Spec Limit Only Case

o       The Two Distributions:

o       The distribution of the individual data points (the x's)

o       The distribution of the sample averages (the Xbar’s)

o       The Calculations for the Process Acceptance Charts

Ø    MIL STD 414 Acceptance Sampling by Variables

o       The Sampling Plan Table

o       Sample Size Calculation

Ø    Lot Acceptance Sampling Plans by Attributes

o       Definition of Sampling Plan Risks ‑ Two Types

o       Evaluation of Sampling Plan Risks – Hypergeometric

o       Evaluation of Sampling Plan Risks - Binomial

o       Evaluation of Sampling Plan Risks - Poisson

Ø    Operating Characteristic Curve

Ø    Finding a Sampling Plan for a Desired OC Curve Shape

Ø    The Average Outgoing Quality  

Ø    The Average Outgoing Quality LIMIT

Ø     Military Standard 105E

Ø     Sampling Plan Workshop