Purpose

The four-level sequence of courses in this series is intended to provide engineering, technical, and manufacturing personnel with an in-depth and working knowledge of industrial statistics and experimental design methods and techniques. Various aspects of this sequence combine to provide the most unique series of its type in the country, specifically:

• There are no prerequisites to initiating the series, and the participants are assumed to enter the first course in the series with no prior knowledge of statistical theory;
• The course sequence stresses applied versus theoretical methods and tools;
• The course uses over 85 industrial examples and data sets to explore the tools and methods taught, all of which have been gathered in actual industrial applications; and
• The course sequence is computer-based, to allow for the maximum amount of content to be covered, and ensures that participants will be capable of applying the knowledge and skills acquired in their own positions after the course sequence is successfully completed.

Participants completing the course sequence will be capable of properly gathering and analyzing data, as well as correctly designing and executing experiments in the industrial setting.

Time Requirement

5 days

Number of Participants

A maximum of 45 participants is recommended for this course sequence, with no more than two participants assigned to each computer.

Prerequisites

Experimental Design and Industrial Statistics — Level III

Primary Resource Materials

Experimental Design and Industrial Statistics — Level IV manual

Content Outline

• Factor and Level Selection for Effective Screening Experiments Utilizing Fractional Factorial Designs
  • Potential Factor Selection
  • Independent versus Response Variables
  • Avoiding Non-Independent Variables
  • Selecting the Number of Levels to be Tested
  • Extreme Level Selection
  • Known and Non-Manipulable Independent Variables
  • Studying Interaction Effects
• Experimental Designs for Screening Experiments: General Guidelines and Observations
• Designing Screening Experiments with Orthogonal Arrays — Case Studies
  • Analysis of a Plating Tank
  • Analysis of a Roll Coater
  • Analysis of Seating Force for Primers
  • Earing Analysis
  • Analysis of a Trimmer/Chopper
  • Self-Review Opportunities
    • Dome Strength Analysis
    • Ingot Casting Analysis
  • 3ⁿ Series Arrays
  • Analysis of a Wafer Processing Furnace
• Conducting Confirming Experiments

• experiment
• statistics
• experimental design
• data

Purpose

The four-level sequence of courses in this series is intended to provide engineering, technical, and manufacturing personnel with an in-depth and working knowledge of industrial statistics and experimental design methods and techniques. Various aspects of this sequence combine to provide the most unique series of its type in the country, specifically:

• There are no prerequisites to initiating the series, and the participants are assumed to enter the first course in the series with no prior knowledge of statistical theory;
• The course sequence stresses applied versus theoretical methods and tools;
• The course uses over 85 industrial examples and data sets to explore the tools and methods taught, all of which have been gathered in actual industrial applications; and
• The course sequence is computer-based, to allow for the maximum amount of content to be covered, and ensures that participants will be capable of applying the knowledge and skills acquired in their own positions after the course sequence is successfully completed.

Participants completing the course sequence will be capable of properly gathering and analyzing data, as well as correctly designing and executing experiments in the industrial setting.

Time Requirement

10 days

Number of Participants

A maximum of 45 participants is recommended for this course sequence, with no more than two participants assigned to each computer.

Prerequisites

Experimental Design and Industrial Statistics — Level II

Primary Resource Materials

Experimental Design and Industrial Statistics — Level III manual

Content Outline

Volume 1 — Planning and Conducting Designed Experiments in Industry

PLAN

• Introduction and Table of Contents
• Identifying the Type and Purpose of the Research Study
• Developing the Experimental Design
• Designing the Industrial Experiment: Case Studies

Volume 2 — Planning and Conducting Designed Experiments in Industry

• Sampling Procedures and Considerations
• Establishing the Validity of the Data

DO

• Managing the Execution of the Experiment

STUDY

• Designing the Plan for the Statistical Analysis of the Data

ACT

• Reporting the Results of the Research Study

Volume 3 — Advanced Statistical Methods

• The Design and Analysis of a Randomized Comparative Experiment
• The Design and Analysis of Factorial Experiments for 2 Factors
• Two-Way ANOVA Models for Random and Mixed Effects
• Disproportionate Frequency Analysis
• Analysis of a Nested Factorial Design
• The Design and Analysis of 2ⁿ Factorial Experiments
• Testing for Homogeneity of Variance and Dispersion in Factorial Models
• Simple and Multiple Regression Analysis
• Response Surface Methodology

• experiment
• statistics
• experimental design
• data

Purpose

The four-level sequence of courses in this series is intended to provide engineering, technical, and manufacturing personnel with an in-depth and working knowledge of industrial statistics and experimental design methods and techniques. Various aspects of this sequence combine to provide the most unique series of its type in the country, specifically:

• There are no prerequisites to initiating the series, and the participants are assumed to enter the first course in the series with no prior knowledge of statistical theory;
• The course sequence stresses applied versus theoretical methods and tools;
• The course uses over 85 industrial examples and data sets to explore the tools and methods taught, all of which have been gathered in actual industrial applications; and
• The course sequence is computer-based, to allow for the maximum amount of content to be covered, and ensures that participants will be capable of applying the knowledge and skills acquired in their own positions after the course sequence is successfully completed.

Participants completing the course sequence will be capable of properly gathering and analyzing data, as well as correctly designing and executing experiments in the industrial setting.

Time Requirement

5 days

Number of Participants

A maximum of 45 participants is recommended for this course sequence, with no more than two participants assigned to each computer.

Prerequisites

Experimental Design and Industrial Statistics — Level I

Primary Resource Materials

Experimental Design and Industrial Statistics — Level II manual

Content Outline

• The Seven-Step Procedure for Statistically Testing Hypotheses and Assumptions
• Testing for Differences/Changes in a Single Process or Population
  • Changes in Central Tendency
  • Changes in Dispersion
  • Changes in Proportions
  • An Introduction to Correlation and Association: 20 Major Measures (Indices) for Assessing Relationships
  • Changes in Correlation
  • Assessing Changes in Levels of Association
• Testing for Differences/Changes in Two Processes or Populations
  • The Concept of Independent versus Dependent Data Sets: Implications and Constructs
  • Testing for Differences in Central Tendency-Independent and Dependent Data
  • Testing for Differences in Dispersion-Independent and Dependent Data
  • Testing for Differences in Proportions-Independent and Repeated Measures
  • Testing for Differences in Two Associative Levels-Independent and Dependent Correlation Coefficients
• In-Class Group Review Activity: A Case Study for the Design of a Small Motor

• experiment
• statistics
• experimental design
• data

Purpose

The four-level sequence of courses in this series is intended to provide engineering, technical, and manufacturing personnel with an in-depth and working knowledge of industrial statistics and experimental design methods and techniques. Various aspects of this sequence combine to provide the most unique series of its type in the country, specifically:

• There are no prerequisites to initiating the series, and the participants are assumed to enter the first course in the series with no prior knowledge of statistical theory;
• The course sequence stresses applied versus theoretical methods and tools;
• The course uses over 85 industrial examples and data sets to explore the tools and methods taught, all of which have been gathered in actual industrial applications; and
• The course sequence is computer-based, to allow for the maximum amount of content to be covered, and ensures that participants will be capable of applying the knowledge and skills acquired in their own positions after the course sequence is successfully completed.

Participants completing the course sequence will be capable of properly gathering and analyzing data, as well as correctly designing and executing experiments in the industrial setting.

Time Requirement

5 days

Number of Participants

A maximum of 45 participants is recommended for this course sequence, with no more than two participants assigned to each computer.

Prerequisites

None

Primary Resource Materials

Experimental Design and Industrial Statistics — Level I manual

Content Outline

• Frequency Distributions
  • Ungrouped, Relative, and Grouped Frequency Distributions
  • Frequency Polygons and Histograms
• Descriptive Statistics
  • Measurement Scales
  • Descriptive Measures of Frequency
  • Formulas and Calculations
• Introduction to Probability
  • Types of Probability
  • Probability Rules/Conditions
• Probability Distributions
  • Definitions and Configuration
  • Random Variables
  • The Binomial and Poisson Distribution
  • The Normal and Log-Normal Distributions
  • The Exponential Distribution
  • The Weibull Distribution
• Sampling and Sampling Distributions
  • Populations/Processes and Random Sampling
  • Types of Sampling
  • Random Sampling Distributions and Statistical Inference
• Estimation
  • Types and Criteria of Estimators
  • Point and Interval Estimates
  • Confidence Levels and Intervals
• Hypothesis Testing
  • Assumptions and Concepts
  • Testing Hypotheses
  • The Significance Level and Risk
  • One- and Two-Tailed Tests
• Error and Power in Hypothesis Testing
  • Type I and II Error and Power
  • Calculating Type II Error and Power
• Sample Size Calculations
  • Factors to be Considered
  • Associated Formulas
  • Relationship of Error, Power, n, Variance, and Effect Size on Sample Size

• experiment
• statistics
• experimental design
• data

Purpose

A critical component in the development of a culture based upon the Total Quality model is effective Daily Management. Daily Management is a management technology composed of activities and tasks that prevent backsliding and allow for the continuous improvement in safety, quality, delivery, cost, and employee satisfaction. Standardization is an improvement strategy that lies within Daily Management and its purpose is to reduce the variability of the methods used to operate a process.

The purpose of this publication is to provide managers, supervisors, facilitators, and team members with guidelines for standardizing their manufacturing operations. This material is laid out in a stand-alone manner in which practitioners can study the material and apply the principles. Throughout the technical aid, scenarios adapted from actual situations assist the student in understanding standardization concepts.

A course, supplemented with Technical Aid VIII: Quality Tools and Techniques, is available as an in-house training program designed to teach the principles of standardization. The course can be structured as a one day class intended to either: 1) prepare team members for standardizing a manufacturing operation, or 2) prepare supervisors, managers, and lead teams for the vital support that standardization efforts require.

Number of participants

Standardization Team Members: Maximum of 25 participants in five separate teams, each with a standardization project.
Managers, Supervisors, and Lead Teams: Maximum of 25 participants.

Prerequisite

Total Quality Overview

Primary Resource Materials

Standardizing Manufacturing Operations and
Quality Tools and Techniques manuals

Content Outline

• Introduction
• The Hierarchy of Improvement
• Management Controllable and Operator-Controllable Errors
• Process Control
• Management and Supervision Support for Standardization Efforts
• Standardizing a Process
• Guidelines for Measurement and Inspection Standard Operating Procedures

• sop
• standard operating procedures
• work instructions

Purpose

This course is designed to provide a wide understanding of the use of the FMEA process. This process may be considered a quantum leap strategy for improving equipment, processes, initial design, and work environment safety. The application of the FMEA tools is relatively simple, and when properly applied, FMEA provides effective and timely improvements toward attaining desirable goals.

This technical aid includes instructions on three types of FMEAs: Product Design, Process, and Job Safety Analysis. There are separate instructions on Equipment FMEAs in the course titled Process and Equipment Reliability Methods.

Time Requirement

4 - 6 hours on each type of FMEA. The instructions are best applied when linked to an initial analysis of an improvement project

Prerequisites

None

Primary Resource Materials

Failure Mode and Effects Analysis manual and additional material linked to the project. This could include, but is not limited to, flowcharts of the process, job and work area descriptions, equipment parts lists, and standard operating procedures.

Content Outline

• Introduction
  • FMEA Timing
  • Commonly Used Failure Effects Analysis Techniques
  • FMEA Forms
  • FMEA Evaluation Criteria
  • Note on Ranking Criteria
• Instructions for Performing an FMEA
  • Product Design FMEA
    • Planning Stage
    • Conducting the FMEA
    • Study the RPN's
    • Acting on Results
• FMEA PDSA Cycle
  • Process FMEA
    • Planning Stage
    • Conducting the FMEA
    • Study the RPN's
    • Acting on Results
• Job Safety Hazard Analysis (JSHA)
  • Planning Stage
  • Conducting the FMEA
  • Study the RPN's
  • Acting on Results

• fmea
• failure mode effects analysis