Management Training Catalog
ROI offers a number of training and application seminars that are
of interest to managers. We will help you in putting together a training
schedule that is right for your company, with the right training at the right
time. But, the list of seminars below will help you see what we can offer, as
well as the depth and breadth of our courses. Please contact us for further information.
Our most popular courses designed for management are:
Business Performance Excellence
Overview | Six Sigma Champion Training |
Daily Management Overview | Strategic
Planning and Policy Deployment Overview | Cross-Functional
Management Workshop | Total Asset
Utilization/Customer Product Rationalization Overview
In addition to these courses, we have a full catalog
of courses that can be modified, customized, and combined to meet your
needs:
Table of Contents:
Business Performance Excellence
An Overview of Business Performance
Excellence
Purpose
This seminar will introduce the concepts of Business Performance
Excellence (BPE) and how it can help a business improve profit and
productivity. Case studies and in-depth discussion aid in showing how BPE will
help your business.
Time Requirement
1 day
Number of Participants
75 participants maximum
Prerequisites
None
Primary Resource Materials
An Overview of Business
Performance Excellence Slide Guide Back to
the top
Six Sigma Champion
Training
Purpose
This seminar trains mid- to upper-level management in the tools,
techniques, and terminology they will need to function as Champions in a Six
Sigma or Business Performance Excellence environment. Champions identify,
prioritize, resource, and provide support to teams working on high-impact
projects within the business. In addition, Implementation Champions design and
build the infrastructure that supports the activities of these problem-solving
teams.
Time Requirement
3 days, 5 days for Implementation
Champions
Number of Participants
25 participants maximum
Prerequisites
None
Primary Resource Materials
Six Sigma Champion Slide
Guide and Workbook Back to the top
Daily Management Overview
Purpose
This seminar introduces managers to the concept of Daily
Management. It introduces the "House of Daily Management" model and its
components, and shows how these components improve the organization and
efficacy of day-to-day operations.
Time Requirement
0.5 day
Number of Participants
75 participants maximum
Prerequisites
None
Primary Resource Materials
Introduction to Daily
Management Slide Guide Back to the
top
Strategic Planning and Policy
Deployment Overview
Purpose
This seminar introduces the concepts of Strategic Planning
(determining how the company will meet the demands of the market) and Policy
Deployment (how to turn the strategic plan into activities at all levels of the
business). It goes into more detail than the Business Performance Excellence
Overview and prepares managers for their role in developing and deploying the
business plan.
Time Requirement
0.5 day
Number of Participants
75 participants maximum
Prerequisites
None
Primary Resource Materials
Strategic Planning and
Policy Deployment Overview Slide Guide Back
to the top
Cross-Functional Management
Workshop
Purpose
This seminar shows how managers can build a system to coordinate
activities across traditional functional lines. Cross-functional management
(CFM) will improve communication across these barriers and help maximize the
company's performance. The seminar ends with a session where the attendees
begin building the infrastructure to support CFM.
Time Requirement
0.5 day
Number of Participants
75 participants maximum
Prerequisites
None
Primary Resource Materials
Cross-Functional Management
Workshop Slide Guide and Workbook Back to the
top
Total Asset Utilization/Customer
Product Rationalization Overview
Purpose
This seminar will show how Total Asset Utilization (TAU) and
Customer Product Rationalization (CPR) can improve your company's profits by
25% or more as well as providing a project-selection criterion. TAU measures
how well you are using assets to make saleable products and/or services. But
maximizing TAU can be a bad business move. By tying TAU to true costs
stratified by customer, product, region, etc., a model of the true
profitability of products and services is built that shows the contribution to
profit across these stratifiers, as well as the trade-offs between them. In
turn, this tells you what to sell to which customers and leads to an input into
the strategic plan to maximize profit at the business. Past CPR implementations
have improved profit at companies by 25% of revenues or more, all without
capital improvements.
The seminar focuses on the metric of TAU and the output of CPR
presented as case studies.
Time Requirement
0.5 day
Number of Participants
75 participants maximum
Prerequisites
None
Primary Resource Materials
Total Asset
Utilization/Customer Product Rationalization Overview Slide
Guide Back to the top
Orientation and Overview
Seminars
An Overview of Total Quality
Management
Purpose
The purpose of this seminar is to
provide all levels of management and supervision with a comprehensive
understanding of the integrated components of the Total Quality (TQ) model.
In-depth explanations, tied to profit and productivity, are provided to allow
the participants to appreciate how each of the model components "fit together"
and understand the benefits of such a model.
The philosophical and financial motivations and benefits
resulting from the implementation of TQ are provided in detail. Provided also
are specific guidelines for the implementation of TQ.
Time Requirement
1 day
Number of Participants
75 participants maximum
Prerequisites
None
Primary Resource Materials
An Orientation to Total
Quality transparency guide
Content Outline
- 1. An Overview of the Components of Total Quality Management
- A. The Management Technologies
- 1) Policy Deployment
2) Daily Management
3) The
PDCA Discipline
- B. The Supporting Technologies
- 1) Total Quality Assurance
2) Just-In-Time
Processing
3) Employee Involvement
- 2. A Breakdown of Customer-Driven Total Quality Assurance
- A. Supplier Quality Assurance
- B. Customer Quality Assurance
- C. Statistical Quality Control
- 1) Problem-Solving
- 2) Quality Improvement Strategy
- 3. A Suggested Model for TQ and case studies from
business and industry
- 4. Recommendations for the Successful Implementation of
TQ
- 5. Sustaining TQ: Recommendations for Management
-
- Back to the top
An Orientation to Total Quality
Assurance
Purpose
The purpose of this seminar is to provide
managers and supervisors at all levels with an understanding of the technical
requirements associated with the implementation of customer-driven quality
assurance in a TQ organization. Particular attention is provided to a quality
improvement strategy, designed to bring critical product and process
characteristics into a state of control and capability. The role of this effort
within the TQ model and its interrelationships is also explored in depth.
Case studies and applicable examples from a number of varied
industries and companies are utilized within the seminar to enhance
participants' understanding of the implementation of TQ in general, and
statistical quality assurance in particular.
Time Requirement
16 hours
Number of Participants
50 participants maximum
Prerequisites
None, although participation in An
Overview of Total Quality is desirable and recommended.
Primary Resource Materials
A Quality Improvement
Strategy for Critical Product and Process Characteristics and An Orientation to
Total Quality transparency guide
Content Outline
- 1. An Overview of the Components of Total Quality Management
(Brief)
- A. The Management Technologies
- 1) Policy Deployment
- 2) Daily Management
- 3) The PDCA Discipline
- B. The Supporting Technologies
- 1) Total Quality Assurance
- 2) Just-In-Time Processing
- 3) Employee Involvement
- 2. A Breakdown of Customer-Driven Total Quality Assurance
(Brief)
- A. Supplier Quality Assurance
- B. Customer Satisfaction and Quality Function Deployment
- C. Statistical Quality Assurance
- 3. The Structure and Purpose of the Total Quality Assurance
Function (Major Emphasis)
- A. Selecting Focal Points for the Implementation of TQM
- B. Problem-Solving versus Quality Improvement
- C. The Quality Improvement Strategy: A Road Map for
Bringing Critical Characteristics into a State of Control and Capability
- D. Case Studies from Industry
- Back to the top
Coursework and Seminars in the Management
Technologies
Daily
Management
Purpose
This overview will describe what
Daily Management is, how it works, why it is
needed, and how it fits with other management systems.
We will present a unique, comprehensive model for Daily
Management and describe its various components.
We will conclude with guidelines for implementation and ongoing
operation.
At the conclusion of the overview, participants should be able
to define Daily Management and why it is needed, describe the purpose and
function of each component in the Daily Management model, and participate in
the planning, implementing, and ongoing operation of Daily Management
Systems.
Time Requirement
1 day
Number of Participants
Maximum of 30 participants
Primary Resource Material
Daily Management Overview
Guide
Content Outline
- Introduction
- Three Management Systems
- Basic Concepts
- House of Daily Management
- Roles and Responsibilities for Implementation
Back to the top
Strategic
Planning and Policy Deployment
Purpose
The purpose of this seminar is to provide
managers and supervisors, as well as quality personnel, with an overview of the
steps and procedures associated with policy deployment.
Specific topics reviewed, with practical and functional
examples, include Strategic Plan development, Strategic Product-Market
Analysis, Mission Statement requirements, and Customer
Quality Assurance system requirements.
This seminar has been designed as a two day seminar/working
session. The first day is primarily devoted to the presentation of the content.
The second day may be utilized as a guided working session for the development
of the components and procedures associated with the elements of a Policy
Deployment system.
Time Requirement
2 days
Number of Participants
30 participants maximum
Prerequisites
An Orientation to Total Quality
Primary Resource Materials
Elements of Strategic
Planning and Policy Deployment
National Label Company: A Strategic Planning
and Policy Deployment Case Study
Content Outline
- A review of the components necessary to properly execute a
Policy Deployment system (e.g., Vision and Beliefs Statement; Mission
Statement; and Focal Point Charts)
- A review of Strategic Planning, with coverage of the
essential elements required for a Strategic Plan so as to facilitate Policy
Deployment
- A review of Strategic (Product-Market) Analysis, with an
assessment of those data bases required for the Policy Deployment effort
- A review of those elements and data that must be
generated from a Customer Quality Assurance system to allow for the appropriate
development of a Strategic Plan
- A comprehensive presentation of a recommended design for a
Policy Deployment and Daily Management system
Back to the top
New Roles For Leadership In A TQ
Environment
Time Requirement
3 consecutive days
Number of Participants
30 participants
Prerequisites
No formal prerequisites are necessary
for this course, although participants may be asked to do some pre-work
assignments and some initial thinking about the changing roles of supervisors
in a TQ environment.
Primary Resource Materials
Any and all pre-readings
that may be disseminated prior to the session.
During the conduct of this
course, a training manual will be the primary resource.
Content Outline
- 1. Past Organizational Systems
- A. Organizational Culture
- B. Organizational Politics
- C. Values and Ethics
- 2. Present and
Future Organizations
- A. Transitions
- B. New Driving Forces
- C. Organizational Culture
- D. Organizational Politics
- E. Values and Ethics
- 3. Leadership
- A. Vision
- B. Empowerment
- C. Strategic Thinking
- D. Motivation
- E. Situational Leadership
- F. Business and Customer Requirements
- 4. Changing Roles
- A. Coaching
B. Facilitating
C. Negotiating
D.
Mentoring
- 5. Required Skills
- A. Problem Solving
- B. Coping with Difficult People
- C. Decision Making
- D. Communication Skills
- E. Stress Management
- F. Conflict Management
- G. Group Process
Back to the top
Foundations of Industrial Research and Experimental Design
Purpose
The purpose of this seminar is to provide
managers, supervisors, and technical personnel with an understanding and
appreciation of the industrial research process. This body of knowledge will
allow seminar participants to more appropriately direct and participate in the
conduct of industrial research in their areas of responsibility. Statistical
methods are de-emphasized in this seminar. The procedures and methods employed
in conducting sound and replicable research are highlighted, discussed, and
explained through the presentation of the applicable theory, followed by a
review of actual case studies.
Time Requirement
32 hours (4 days @ 7 hours and 1 day
@ 4 hours)
Number of Participants
25 participants maximum
Prerequisites
Statistical Methods for Managers
(Required)
An Introduction to Statistical Process Control and Capability
(Recommended)
Primary Resource Materials
Foundations of Industrial
Research and Experimental Design Volumes 1 and 2 (Dedicated manual, 425
pages)
Content Outline
- 1. Initially Describing the Research Study
2. Developing
the Theoretical Framework of the Study
3. Operationalizing the Statement of
the Problem: Research Questions and Hypotheses
4. Underlying Concepts and
Definitions of Experimental Design
5. The Basic Logic and Purpose of an
Experimental Design
6. Types of Experimental Designs
7. Designing the
Industrial Experiment
8. Assessing the Industrial Experiment for Adequacy
and Efficiency
9. Case Studies (8)
- A. Coolant Vendor Analysis
B. Maintenance Technique
Comparison
C. Hybrid Corn Comparison
D. Label Selection (Sales)
E.
Label Adherence Study
F. Injection Molding Study
G. Baked Cracker Package
Design
H. Product Design: Ammunition
- 10. Sampling Procedures and Considerations
11.
Establishing the Validity of the Data
12. Managing the Execution of the
Experiment
13. Designing the Plan for the Statistical Analysis of the
Data
14. Reporting the Results of the Research Study
Back to the top
Asking the Right Questions
Purpose
This seminar provides managers and supervisors
with an opportunity to apply statistical skills acquired in earlier courses.
Participants learn to synthesize and evaluate the results of research and
data-gathering efforts as intelligent consumers of data, ask correct and
appropriate questions, make appropriate observations, and suggest sensible
follow-up strategies when presented with the results of industrial research.
The participants will walk through the appropriate analyses of a number of
studies actually conducted in various plants. Analyses corresponding to both
the vendor and customer perspective are explored.
Time Requirement
2 to 3 days
Number of Participants
25 participants maximum
Prerequisites
Foundations of Industrial Research and
Experimental Design
Content Outline
- Improving Incoming Material for Our Can Plant Customers
- Analyzing Steam Line Performance on Our Local EMC Pit
- Understanding the Surface Quality of Work Rolls from Our
Local Roll Shop
- Selecting a Rolling Oil Vendor ... Statistically
- Why is Our Aerospace Customer Upset Over Elongation?
- Sampling Coolant Additives for Taste
- Should We Purchase the New Tester?
- An Exercise in Personnel Evaluation
- Selecting Saw Blade Vendors Based Upon Time to Failure
(Life)
- Understanding the Statistical Calibration of our Moisture
Analysis System
Back to the top
Coursework and Seminars in the
Supporting Technologies
Team Effectiveness
Time Requirement
3 consecutive days
Number of Participants
An ideal number would be 24. It
is recommended that teams participate as a group, with 6 to 8 people per
team.
Prerequisites
The team should meet at least once prior
to this session.
The team should be prepared to work on their own mission
during this session.
Primary Resource Materials
Any and all pre-readings
that may be disseminated prior to the session.
During the conduct of this
course, a Team Effectiveness manual will be the primary resource.
Content Outline
- 1. Teaming
- A. Definition
B. Structure
C. Foundations of
Teamwork
D. Stages of Team Development E. Major Team Problem Areas
- 2. Group Process
- A. Team Dynamics
B. Problem Solving Process
C.
Decision Making Process
D. Facilitation Skills
E. Participation
F.
Process Issues
G. Visual Aids
- 3. Communication
- A. Attitude
B. Listening
C. Speaking
D.
Feedback
E. Personality Types
F. Managing Conflict
- 4. Meeting Effectiveness
- A. Parts of a Meeting
B. Planning Meetings
C.
Conducting Meetings
D. Rules and Guidelines
E. Informal Meetings
F.
Problem Situations in Meetings
Back to the top
An Overview of Just-In-Time Processing
Purpose
The purpose of this seminar is to familiarize
all levels of management and supervision with the tools, techniques, and
methods associated with Just-In-Time (JIT) processing. Explanations are
provided on how JIT processing contributes to profit and productivity. Each JIT
tool, method, and technique is described in detail to assist the participant in
how they would be used in their applications.
The philosophical and financial motivations and benefits
resulting from the implementation of JIT processing are explained in detail.
Specific planning on how the organization would go about undertaking a JIT
processing implementation can be accomplished by combining this overview with
the three day JIT seminar.
Time Requirement
1 day
Number of Participants
25 participants
Prerequisites
An Overview of Total Quality
Commitment
Primary Resource Materials
An Overview of Just-In-Time
Processing
- Content Outline
- 1. Benefits of Just-In-Time Processing and Cycle Time
Reduction
- 2. The Just-In-Time Processing Model and Definitions
- 3. The Seven Wastes
- 4. Visual Control and the 5 S's Improvement Strategy
- 5. Continuous Flow Processing
- a. Focused Factories
b. Cellular Manufacturing
- 6. Load Leveling and Balanced Operations
- a. Load Leveling
b. Balanced Operations
- 7. Pull Systems
- 8. Total Productive Maintenance (TPM)
- 9. Set-up Time Reduction
- 10. Autonomation
- 11. Supplier Relationships
- a. Single-Source Suppliers
b. Long-term
Partnerships
c. Supplier Quality Assurance
Back to the top
Just-In-Time
Processing
Purpose
The purpose of this seminar is to provide
management, supervision, support personnel, and shop floor employees with the
skills necessary to use the tools, techniques, and methods associated with
Just-In-Time (JIT) processing. Explanations are provided of how JIT processing
contributes to profit and productivity. Each JIT tool, method, and technique is
explained in detail, followed by group-based work sessions that assist the
students to transfer the classroom lesson to their own manufacturing
environment. In some cases, the planning and work associated with JIT
processing implementation can be accomplished.
Time Requirement
3 days
Number of Participants
Maximum of 25 participants
Prerequisite
An Overview of Total Quality
Primary Resource Materials
Just-In-Time Processing
Workbook
Pull System Exercise
- Content Outline
- Benefits of JIT Processing and Cycle Time Reduction
- JIT Processing Model and Definitions
- Waste Elimination
- Visual Control and the 5 S’s Improvement Strategy
- Continuous Flow Processing
- Load Leveling and Balanced Operations
- Pull Systems
- Total Productive Maintenance
- Setup Time Reduction
- Autonomation
- Supplier Relationships
- Putting It All Together
Back to the top
Coursework and Seminars in the
Supporting Technology of Total Quality Assurance
Statistical Methods for
Procurement
Purpose
A course for the procurement professional, the
participant will learn to use the tools necessary to (1) statistically analyze
incoming raw materials and supplies for potential capability; (2) statistically
analyze incoming raw materials and supplies for short- and long-term control
and capability; (3) perform and/or understand those studies necessary to
purchase valid and reliable measurement devices and/or systems; and (4)
statistically compare vendors/suppliers based upon quality, reliability, total
cost, and delivery and service.
Time Requirement
4 days
Number of Participants
No limit
Prerequisites
An Introduction to Statistical Process
Control and Capability, Advanced Statistical Process Control and Capability,
Guidelines for a Practical Approach to Gauge Capability Analysis, and
Statistical Methods for Management or Experimental Design and Industrial
Statistics, Level I.
Primary Resource Materials
Statistical Methods for
Procurement manual
Content Outline
- 1. An Overview of Supplier Quality Assurance
- A. Model Premises
- B. Supplier Selection and Qualification
- C. Cost of Quality Accounting System
- D. Critical Characteristic Approval and Review System
- 2. Statistically Assessing Incoming Materials
- A. Assessment Model
- B. Case Study I: Purchasing Oil-Based Coolant/Lubricant
- C. Case Study II: Purchasing Steel Wire (Coils)
- 3. Statistically and Financially Comparing Incoming Materials
and Suppliers
- 4. A Comprehensive Model and Procedures for Vendor/Supplier
Selection
- A. Case Study III: Purchasing Coated End Stock
- 5. A Suggested Model for Acceptance Criteria for Purchased
Machinery and Equipment
Back to the top
An Overview of Customer
Quality Assurance
Purpose
This seminar provides a broad and
comprehensive overview in the area of Customer Quality Assurance (CQA). It is
intended to provide personnel in the Sales, Marketing, and other administrative
areas with an understanding of the major elements associated with the design,
implementation, and maintenance of a CQA system. Distinctions are drawn between
Customer Satisfaction processes and CQA; the systemic requirements associated
with moving beyond Customer Satisfaction (i.e., meeting the needs of the
customer) into the realm of Customer Delight (i.e., exceeding the needs
of the customer) are also discussed.
Time Requirement
1 day
Number of Participants
30 participants maximum
Prerequisites
None
Primary Resource Materials
Elements of Customer
Quality Assurance
Content Outline
- The Evolution of Customer Quality Assurance
- A Breakdown of the Customer Satisfaction Improved
Process
1. Identifying Served Markets
2. Selecting/Identifying Key
(Critical) Customers
3. Determining Customer Requirements
4. Identifying
Corresponding Design Requirements
5. Designing and Engineering the
Product/Service
6. Planning for Manufacture/Delivery
7. Planning for
Process Control
8. Sales and After-Sale Service Considerations
9.
Tracking Customer Satisfaction
- Premises and Requirements for a Customer Feedback System
- The Role of CQA in Product Design and Advanced Quality
Planning
Back to the top
Statistical Methods for
Marketing
Purpose
This seminar provides sales and marketing
personnel with the ability to use statistical methods in the collection and
analysis of data related to field studies, strategic product development
(SPD/QFD) studies, market surveys, and customer surveys. The primary emphasis
in this seminar is placed upon those statistical tools associated with the
analysis of discrete data; specifically, nominal and ordinal data scales.
Time Requirement
4 days
Number of Participants
No limit
Prerequisites
Statistical Methods for Managers
Primary Resource Materials
Statistical Methods for
Marketing manual
Content Outline
- 1. A Review of Hypothesis Testing
(Discussed if all
participants have not completed the necessary prerequisite or require a review)
- A. Basic Assumptions and Concepts
- B. Testing Hypotheses
- C. The Significance Level and Risk
- D. One- and Two-Tailed Tests
- 2. Hypothesis Tests for Single Sample Analyses
- A. One Sample Analyses for Nominal Data
- 1) The One-Sample Binomial Test
- 2) The Chi-Square Goodness-of-Fit Test
- B. One Sample Analyses for Ordinal Data
- 1) The Wilcoxon-Signed Rank Test for Location
- 2) The Sign Test for Location
- 3) The Kolmogorov-Smirnov One-Sample Test
- 3. Hypothesis Tests for the Analysis of Two and k Sample
Cases
- A. Independent Sample Tests
- 1) Two-Sample Tests for Nominal Data
- 2) Two-Sample Tests for Ordinal Data
- 3) Chi-Square: A k Sample Test for Nominal Data
- 4) A k Sample Test for Ordinal Data: the Kruskal-Wallis
ANOVA
- B. Dependent Sample Tests
- 1) A Two-Sample Test for Nominal Data: McNemar's Test of
Change
- 2) Two-Sample Tests for Ordinal Data
- 3) Chi Square: A k Sample Test for Nominal Data
- 4) A k sample Test for Ordinal Data: The Kruskal-Wallis
ANOVA
- 4. Introduction to Conjoint Analysis
Back to the top
Coursework and Seminars in the
Supporting Technology of Total Quality Assurance
Introduction to Statistical Process Control and Capability
Purpose
This introductory course includes instruction
from a comprehensive, applied training manual. The examples used throughout the
seminar are actual examples using data collected by personnel involved in
developing and implementing process control systems and conducting capability
analyses. A modified course is available for operator training, which
emphasizes a hands-on approach.
Time Requirement
4 days
Number of Participants
30 participants maximum
Prerequisites
None
Primary Resource Materials
An Introduction to
Statistical Process Control and Capability manual
Quality with Confidence in
Manufacturing
Process Control Technology workbook
Content Outline
- 1. The Graphical Representation of Data and Basic Descriptive
Statistics
- A. Ungrouped and Grouped Frequency Distributions
- B. Frequency Polygons and Histograms
- C. Measures of Central Tendency
- D. Measures of Variability
- E. The Normal Distribution and z Scores
- 2. Control Chart Theory
- A. Process Variation
- B. Control Chart Theory
- C. Statistical Control Conditions
- 3. Process Control and Capability for Variables Data
- A. Developing and Interpreting X-Bar and R Charts
- B. Introduction to Process Capability
- C. Developing and Interpreting X-Bar and s Charts
- D. Process Capability Analysis utilizing the X-Bar and s
Chart
- 4. Process Control and Capability for Attribute Data
- A. Control Charts for Defectives
- 1) Developing and Interpreting p Charts
- 2) Developing and Interpreting np Charts
- B. Control Charts for Defects
- 1) Developing and Interpreting c Charts
- 2) Developing and Interpreting u Charts
- 5. How to Get Started in Statistical Process Control
Back to the top
Introduction to Statistical Process Control and Capability — Floor
Applications
Purpose
This introductory course includes instruction
from a comprehensive, applied training manual. The examples used throughout the
seminar are actual examples using data collected by personnel involved in
developing and implementing process control systems and conducting capability
analyses. This modified course is generally utilized for operator training,
emphasizing a hands-on, applied approach.
Time Requirement
4 days
Number of Participants
30 participants maximum
Prerequisites
None
Primary Resource Materials
Introduction to Statistical
Process Control and Capability Floor Applications manual
- Content Outline
- 1. The Graphical Representation of Data and Basic
Descriptive Statistics
- A. Ungrouped and Grouped Frequency Distributions
B.
Frequency Polygons and Histograms
C. Measures of Central Tendency
D.
Measures of Variability
E. The Normal Distribution and z Scores
- 2. Control Chart Theory
- A. Process Variation
B. Control Chart Theory
C.
Statistical Control Conditions
- 3. Process Control & Capability for Variables Data
- A. Developing and Interpreting X-Bar and R Charts
B.
Introduction to Process Capability
C. Developing and Interpreting X-Bar and
s Charts
D. Process Capability Analysis utilizing the X-Bar and s Chart
- 4. Process Control and Capability for Attribute Data
- A. Control Charts for Defectives
- 1) Developing and Interpreting p Charts
2)
Developing and Interpreting np Charts
- B. Control Charts for Defects
- 1) Developing and Interpreting c Charts
2) Developing
and Interpreting u Charts
- 5. How to Get Started in Statistical Process Control
Back to the top
An Introduction to Statistical Process Control for Administrative and Services
Personnel
Purpose
This course provides those personnel working
in administrative and service functions with the information necessary to
understand and apply statistical quality control tools to their process(es)
using actual data. The course also emphasizes the importance of the quality
cost/loss function analyses that relate to all administrative functions,
particularly in the area of accounting. Personnel completing the course learn
that their processes are quite variable and that they do have supplier/customer
relationships that require continuous improvement.
Time Requirement
4 days
Number of Participants
No limit
Prerequisites
None
Primary Resource Materials
An Introduction to
Statistical Process Control for Administrative and Services Personnel
manual
- Content Outline
- 1. Quality Costs and the Need for Continuous Improvement
- A. The Quality Cost Concept
B. Quality Costs
Defined
C. Quality Cost Categories
D. The Need for Continuous
Improvement
- 2. The Graphical Representation of Data and Basic
Descriptive Statistics
- A. Ungrouped Frequency Distributions
B. Grouped
Frequency Distributions
C. Frequency Polygons and Histograms
D. Measures
of Central Tendency
E. Measures of Variability
F. The Normal Distribution
and z Scores
- 3. Control Chart Theory
- A. Process Variation
B. Control Chart Theory
C.
Statistical Control Conditions
- 4. Process Control and Capability for Variables Data
- A. Introduction
B. Developing and Interpreting X-bar
and R Charts
C. Introduction to Process Capability
D. Process Capability
Analysis from the X-bar and R Chart
- 5. Process Control and Capability for Attribute Data
- A. Introduction
B. Developing and Interpreting p
Charts
C. np, c, and u Charts
- 6. Problem Solving and Basic Tools for the Problem-Solving
Process
- A. Introduction
B. Problem Statements
C. Pareto
Charts
D. Flow Charts
E. Brainstorming
F. Fishbone Charts
Back to the top
Advanced Statistical Process Control and
Capability
Purpose
This advanced course includes instruction from
a comprehensive, applied training manual. The examples used throughout the
seminar are actual examples using data gathered by personnel involved in
developing and implementing process control systems and conducting capability
analyses. Unique aspects of this course include short-term and process
capability analysis for non-normal distributions, employing the X and
Moving R chart for the control of non-normal processes, and computer
applications for specialized functions.
Time Requirement
4 days
Number of Participants
30 participants maximum
Prerequisites
An Introduction to Statistical Process
Control and Capability
Primary Resource Materials
Advanced Statistical
Process Control and Capability manual
Content Outline
- 1. Special Purpose Control Charts
- A. The Median and Range Chart
- 2. Special Purpose Control Charts
- A. The X and RM Chart for Applications Based Upon the
Normal Distribution
B. Comparison of Mean (X) and Individuals (X) Control
Charts
C. Testing for Normality
D. The X and RM Chart for Applications
Based Upon Non-Normal Distributions
- 3. Standardized-Values Charts for Attribute Control
- 4. Tool Wear and Trend Analysis Using the X and R Control
Chart
- 5. Statistical Analysis of Control Conditions
- A. Statistical Analysis of Runs
B. Statistical Analysis
of Trends
- 6. Procedures for Conducting Potential, Short-Term, and
Long-Term Capability Analyses
- A. Forms of Capability Studies
B. Procedures for the
Conduct of a Process Potential Study
C. Process Potential Analyses
- 1) Probability Plotting Methods
2) Conducting Process
Potential Studies Utilizing Computer Analyses
- D. Long-Term Analytical Methods and Procedures
- 1) Normal Model Applications
2) Non-Normal Model
Applications
Back to the top
Practicum in Statistical Quality Control
Purpose
This seminar provides an opportunity to apply
statistical skills acquired in earlier courses. Participants learn to
synthesize and evaluate the results of research and data gathering efforts as
intelligent researchers, presenters, and consumers of data; and ask correct and
appropriate questions, make appropriate observations, and suggest sensible
follow-up strategies when presented with the results of industrial research.
Participants conduct analyses for case studies with actual data collected in
the past from both the customer and vendor perspective and from actual
plant/engineering research studies.
Time Requirement
4 days
Number of Participants
30 participants maximum
Prerequisites
An Introduction to Statistical Process
Control and Capability, Advanced Statistical Process Control and Capability,
Experimental Design and Industrial Statistics (Levels I through III)
Primary Resource Materials
Practicum in Statistical
Quality Control manual
Content Outline
- Case Studies for Participant Analyses
- Improving Incoming Material for Our Can Plant Customers
- Analyzing Steam Line Performance on an EMC Casting Pit
- Analyzing the Surface Quality of Work Rolls Produced in a
Roll Shop
- Statistically Selecting a Rolling Oil Vendor
- An Analysis of End-of-Line Elongation Values for Aerospace
Applications
- Conducting Appropriate Taste Analyses as Associated with
Coolant Additives
- Making a Purchasing Decision for a New Laboratory Test
Device Based Upon an Appropriate Statistical Analysis (Class I Destructive
Test)
- Comparative Analysis of Saw Blade Vendors Based Upon Time
to Failure (Life Analysis)
Back to the top
Introduction to Statistical
Methods for Managers
Purpose
This course provides individuals in
decision-making positions with a basic understanding of data collection and
description, inferences about processes and populations based upon samples, and
the design of appropriate experiments. Emphasis in this course is placed on the
understanding of statistical methods and concepts, as well as the uses and
importance of these methods. The interpretation of the results of statistical
analyses are explored in-depth. Special emphasis in the area of the design of
industrial research is placed upon risk (Type I and II errors), sample sizes,
the implications of the use of discrete versus continuous data, sampling
techniques, and their relationship to the conduct of reliable and valid
industrial research.
Time Requirement
4 days
Number of Participants
No limit
Prerequisites
None
Primary Resource Materials
Statistical Methods for
Managers manual
Content Outline
- 1. Basic Statistical Theory
- A. Frequency Distributions
B. Basic Descriptive
Statistics
- 2. Probability and Probability Distributions
- A. Introduction to Probability
B. Theoretical
Probability Distributions
- 1) The Binomial Distribution
2) The Poisson
Distribution
3) The Normal and Log-Normal Distribution
4) The Exponential
Distribution
5) The Weibull Distribution
- 3. Sampling and Estimation
- A. Sampling and Random Sampling Distributions
B. Point
and Interval Estimation: An Introduction
- 4. An Overview of Statistical Decision-Making Techniques
and Tools
- A. An Introduction to Hypothesis Testing
B.
Significance, Importance, Confidence, Power, and Risk
C. Process Control
Charts
D. Capability Analyses: Short and Long-Term Methods and
Considerations
Back to the top
Understanding Variation
Purpose
An understanding of variation is critical to
management decision making. We are constantly surrounded by numbers giving us
the current status of the business in terms of profit, sales, cost, safety,
environmental compliance, etc. This course is designed to increase managers'
understanding of the use of data and to provide them with the necessary tools
for differentiating between sources of variation that can be addressed locally
(by their employees) and those that will require a management decision for
change. The course emphasizes the importance of data integrity, of selecting
the appropriate metrics, and of the correct use of data and appropriate
strategies to effectively manage in the TQ environment.
Time Requirement
2 days
Number of Participants
25 participants maximum
Prerequisites
None
- Primary Resource Materials
Understanding Variation
manual and
Understanding Variation — The Key to Managing Chaos by
Donald J. Wheeler
- Content Outline
- 1. Selecting Appropriate Metrics
- A. Data Validity
B. Guidelines for Selecting Metrics
- 2. Definition of Variation
- A. Common vs. Special Causes of Variation
B. Deming's
Red Bead Example
- 3. Common Mistakes in Reacting to Variability
- A. Reacting When They Shouldn't (Tweaking)
B. Using the
Average to Describe the Distribution
C. Not Reacting When They Should
- 4. Correct Use of Data
- A. Control Charts
B. Guidelines for Out-of-Control
Conditions
C. Reaction Plans
- 5. Problem-Solving Strategy and Quality Improvement Strategy
- A. Difference Between Tools and Strategies
B.
Plan-Do-Study-Act
C. Quality Improvement Strategy
D. Problem-Solving
Strategy
- 6. Avoiding the Risk of Suboptimization and Data-based
Management Decisions
Back to the top
Problem
Solving
Purpose
This course provides organizations with the
knowledge, tools, and techniques that allow individuals to manage and
effectively participate in systematic problem elimination and performance
improvement. The participants will acquire a foundation in the principles of
the scientific method, the use of data, and the nature of problems and causes
which face an organization. A unique distinction is made in this course between
the elimination of incidents and breakthrough performance improvement. A
Problem Elimination System is introduced as a system for recurrence prevention
of unwanted incidents such as safety accidents, out-of-control conditions,
machine failures, customer complaints, and excess scrap losses. A recognized
seven-step Problem-Solving Strategy is provided to address chronic problems and
performance improvement. Participants will learn how to use these strategies
and apply various quality tools and techniques. A final discussion gives the
obligations of managers which are required to effectively manage teams.
Time Requirement
2 days
Number of Participants
Maximum of 30
Prerequisites
None
Primary Resource Materials
Problem Solving, Quality
Tools and Techniques
Content Outline
- 1. Introduction
- A . An Analysis of Product and Service Quality and
Complaints
B. Course Outline
- 2. Scientific Method
- A. An Outline of the Scientific Method
B. Industrial
Mythology
C. The Preconditioned Mind
D. Elimination of Industrial
Mythology
- 3. Using Data
- A. Using Numbers to Represent Observations
B. Criterion
Measures and Operational Definitions
C. Types of Data
D. Time, Shape,
Spread, and Location
E. Data Must Support Decisions
F. Process Measures
vs. Result Measures
G. Efficient and Effective Data
- 4. Problems and Causes
- A. Performance Improvement
B. Incidents
C.
Causes
D. Elimination/Improvement
E. Process Improvement Stages
- 5. Problem Elimination System-System Highlights
- 6. Launching a Problem-Solving Team
- A. Initiation Source
B. Role of the Sponsor
C. The
Mission Statement
D. Team Commissioning Meeting
- 7. Problem-Solving Strategy
- A. Introduction
B. The Need for a Structured
Approach
C. What Kind of Activities Should Use a Problem-Solving
Strategy?
D. Overview
E. A Warning from Juran
F. The Elimination of
Multiple Subproblems
G. Problem-Solving Strategy Steps
- 8. Management Obligations
Back to the top
Quality Tools and Techniques
The Quality Tools and Techniques course allows participants to
recognize each of 18 quality tools and techniques and understand their
application. In-class use of selected tools will be provided as needed. This
course is integrated into the Problem-Solving course, but may also be presented
as a stand-alone course.
- 1. Process Definition
- A. SIPOC Models
B. Flowcharts
- 2. Generating and Organizing Ideas and Knowledge
- A. Brainstorming
B. Affinity Diagrams
C. Tree
Diagrams
D. Cause-and-Effect Diagrams
E. Matrix Diagrams
F. Ranking
Techniques
- 3. Collecting and Organizing Data
- A. Check Sheets
B. Pareto Diagrams
C. Graphing
Techniques
- 4. Understanding Variation
- A. Histograms
B. Run Charts
C. Control Charts
D.
Scatter Diagrams
- 5. Project Management Tools
- A. CPM Diagrams and Gantt Charts
B. Responsibility
Matrices
C. Storyboards
Back to the top
Process and Equipment
Reliability Methods
Purpose
The purpose of this seminar is to provide all
levels of engineering and manufacturing personnel with an understanding of
reliability and how they can make productive use of the discipline and related
tools to enhance product or process reliability. Emphasis is placed on the
planning for and the execution of process and equipment reliability
improvements with an intensive review of these tools useful in making any
reliability plan meet its stated objectives.
Time Requirement
5 days
Number of Participants
30 participants maximum
Prerequisites
Design and Industrial Statistics Level I
or Statistical Methods for Managers
Primary Resource Materials
Reliability Methods for
Processes and Equipment manual
Content Outline
- Planning for Reliability
- Reliability Data Collection, Processing, and Reporting
- Design Verification, Production Validation, and In-Process
Testing
- Design Reviews
- Reliability Predictions
- Reliability Mathematics
- Reliability Modeling
- Reliability Specifications
- Failure Mode and Effects Analysis
- Reliability Growth Analysis
- Weibull Analysis
- Reliability Testing
- Monte Carlo Simulation
Back to the top
Failure Mode and Effects Analysis (FMEA)
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
- 1. Introduction
- A. FMEA Timing
B. Commonly Used Failure Effects
Analysis Techniques
C. FMEA Forms
D. FMEA Evaluation Criteria
E. Note
on Ranking Criteria
- 2. Instructions for Performing an FMEA
- A. Product Design FMEA
- Planning Stage
- Conducting the FMEA
- Study the RPN's
- Acting on Results
- 3. FMEA PDSA Cycle
- A. Process FMEA
- Planning Stage
- Conducting the FMEA
- Study the RPN's
- Acting on Results
- 4. Job Safety Hazard Analysis (JSHA)
- Planning Stage
- Conducting the FMEA
- Study the RPN's
- Acting on Results
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Standardizing Manufacturing
Operations
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
Back to the top
Coursework and Seminars in the Supporting Technology of Total
Quality Assurance
Experimental Design and
Industrial Statistics
A Four Course Sequence
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.
Back to the top
Experimental Design and Industrial
Statistics — Level I
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
- 1. Frequency Distributions
- A. Ungrouped, Relative, and Grouped Frequency
Distributions
B. Frequency Polygons and Histograms
- 2. Descriptive Statistics
- A. Measurement Scales
B. Descriptive Measures of
Frequency
C. Formulas and Calculations
- 3. Introduction to Probability
- A. Types of Probability
B. Probability Rules/Conditions
- 4. Probability Distributions
- A. Definitions and Configuration
B. Random
Variables
C. The Binomial and Poisson Distribution
D. The Normal and
Log-Normal Distributions
E. The Exponential Distribution
F. The Weibull
Distribution
- 5. Sampling and Sampling Distributions
- A. Populations/Processes and Random Sampling
B. Types
of Sampling
C. Random Sampling Distributions and Statistical Inference
- 6. Estimation
- A. Types and Criteria of Estimators
B. Point and
Interval Estimates
C. Confidence Levels and Intervals
- 7. Hypothesis Testing
- A. Assumptions and Concepts
B. Testing Hypotheses
C.
The Significance Level and Risk
D. One- and Two-Tailed Tests
- 8. Error and Power in Hypothesis Testing
- A. Type I and II Error and Power
B. Calculating Type II
Error and Power
- 9. Sample Size Calculations
- A. Factors to be Considered
B. Associated
Formulas
C. Relationship of Error, Power, n, Variance, and Effect Size on
Sample Size
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Experimental Design and Industrial
Statistics — Level II
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
- 1. The Seven-Step Procedure for Statistically Testing
Hypotheses and Assumptions
- 2. Testing for Differences/Changes in a Single Process or
Population
- A. Changes in Central Tendency
B. Changes in
Dispersion
C. Changes in Proportions
D. An Introduction to Correlation
and Association: 20 Major Measures (Indices) for Assessing Relationships
E.
Changes in Correlation
F. Assessing Changes in Levels of Association
- 3. Testing for Differences/Changes in Two Processes or
Populations
- A. The Concept of Independent versus Dependent Data Sets:
Implications and Constructs
B. Testing for Differences in Central
Tendency-Independent and Dependent Data
C. Testing for Differences in
Dispersion-Independent and Dependent Data
D. Testing for Differences in
Proportions-Independent and Repeated Measures
E. Testing for Differences in
Two Associative Levels-Independent and Dependent Correlation Coefficients
- 4. In-Class Group Review Activity: A Case Study for the
Design of a Small Motor
-
- Back to the top
Experimental Design and Industrial
Statistics — Level III
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
- 1. Introduction and Table of Contents
2. Identifying
the Type and Purpose of the Research Study
3. Developing the Experimental
Design
4. Designing the Industrial Experiment: Case Studies
- Volume 2 — Planning and Conducting Designed
Experiments in Industry
- 5. Sampling Procedures and Considerations
6.
Establishing the Validity of the Data
- DO
- 7. Managing the Execution of the Experiment
- STUDY
- 8. Designing the Plan for the Statistical Analysis of
the Data
- ACT
- 9. Reporting the Results of the Research Study
- Volume 3 — Advanced Statistical Methods
- 1. The Design and Analysis of a Randomized Comparative
Experiment
2. The Design and Analysis of Factorial Experiments for 2
Factors
3. Two-Way ANOVA Models for Random and Mixed Effects
4.
Disproportionate Frequency Analysis
5. Analysis of a Nested Factorial
Design
6. The Design and Analysis of 2n Factorial Experiments
7. Testing
for Homogeneity of Variance and Dispersion in Factorial Models
8. Simple and
Multiple Regression Analysis
9. Response Surface Methodology
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Experimental Design and Industrial
Statistics — Level IV
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
- 1. Factor and Level Selection for Effective Screening
Experiments Utilizing Fractional Factorial Designs
- A. Potential Factor Selection
B. Independent versus
Response Variables
C. Avoiding Non-Independent Variables
D. Selecting the
Number of Levels to be Tested
E. Extreme Level Selection
F. Known and
Non-Manipulable Independent Variables
G. Studying Interaction Effects
- 2. Experimental Designs for Screening Experiments: General
Guidelines and Observations
- 3. Designing Screening Experiments with Orthogonal Arrays
— Case Studies
- A. Analysis of a Plating Tank
B. Analysis of a Roll
Coater
C. Analysis of Seating Force for Primers
D. Earing Analysis
E.
Analysis of a Trimmer/Chopper
F. Self-Review Opportunities
- 1) Dome Strength Analysis
2) Ingot Casting Analysis
- G. 3n Series Arrays
H. Analysis of a Wafer Processing
Furnace
- 4. Conducting Confirming Experiments
Back to the top
Guidelines for a Practical Approach to
Gauge
Capability Analysis
Purpose
This seminar presents a series of definitions
and procedures for developing a sensible approach to the evaluation of existing
gauges as well as providing a basis for the intelligent purchase of new gauging
systems. Additionally, the seminar includes a hands-on segment for the
evaluation of standard gauges, which brings home the concepts and clarifies the
principles of capability analysis for process and product measurement. The
major thrust of the content in this seminar is non-destructive measurement
processes as associated with variables (continuous) data.
Time Requirement
1 day
Number of Participants
30 participants maximum
Prerequisites
An Introduction to Statistical Process
Control and Capability
Primary Resource Materials
Guidelines for a Practical
Approach to Gauge Capability Analysis manual
Content Outline
- Gauge Capability: Concepts, Terminology, and Definitions
- General Procedures for the Collection of Data
- Procedures for a Process Potential Study for Gauges
- Procedures for Short-Term Capability Analyses
- Procedures for Long-Term Capability Analyses
- Computer Applications
Back to the top
Advanced Gauge Control and Capability
Analysis
Purpose
This course is intended to provide a practical
experience in the advanced analysis of measurement systems for statistical
facilitators, engineering personnel, technical and laboratory personnel, and
all others engaged in the evaluation of measurement errors and bias analysis.
The problems presented are intended to provide the practitioner with a set of
basic and straightforward tools associated with the analysis of measurement
systems. All of the case studies have been drawn from actual industrial
applications that represent the complex issues and occurrences often facing the
practitioner.
Time Requirement
5 days
Number of Participants
25 participants maximum
Prerequisites
An Introduction to Statistical Process
Control and Capability, Advanced Statistical Process Control and Capability,
Guidelines for a Practical Approach to Gauge Capability Analysis, and
Experimental Design and Industrial Statistics — Levels I, II, and III
Primary Resource Materials
Advanced Gauge Control and
Capability Analysis manual
Content Outline
- The Case of the Tool Room Depth Gauge
- The Case of the Pallet Shipping Scale
- The Case of the Laboratory Containment Tester (Class I
Destructive Test)
- The Case of the Modified Substrate Length Gauge
- The Case of the Surface Quality Multiple Gauging System
- The Case of the Comparative Laboratory Analysis (Two Class
I Destructive Tests)
- The Case of the New Moisture Analyzer
Back to the top
Gauge Control and Capability for
Discrete Data Systems
Purpose
The purpose of this course is to provide the
participants with the methods and techniques necessary to determine whether
measurement systems yielding discrete (rather than continuous) data are in a
state of control and capability.
This course introduces the concepts and implications of
measurement control for all discrete data systems. The methods stressed within
this course correspond to systems which generate nominal data. Examples of
these systems include go/no-go gauging systems, categorical (e.g.,
bitter/sweet/sour) sensory scales, and low resolution continuous data
systems.
After completing this seminar, the participant will be capable of
assessing the precision and accuracy of all nominal data measurement systems,
regardless of the number of scale categories or the number of judges and
inspectors.
Time Requirement
5 days
Number of Participants
25 participants maximum
Prerequisites
An Introduction to Statistical Process
Control and Capability, Advanced Statistical Process Control and Capability,
Guidelines for a Practical Approach to Gauge Capability Analysis, Advanced
Gauge Control and Capability Analysis, Experimental Design and Industrial
Statistics — Levels I, II, and III
Primary Resource Materials
Guidelines for a Practical
Approach to the Assessment of Discrete Data Measurement Systems — Volume
I: Nominal Data Applications
Content Outline
- 1. Introduction to the Issue of Discrete Data Measurement
Analysis
- 2. The Measurement of Agreement (Precision): An Overview of
Statistical Indices of
Agreement for Nominal Data Scales
- 3. Guidelines and Procedures for Measurement Processes
Yielding Nominal Data
- A. General Guidelines and Observations
B. A recommended
Procedure for a Short-Term Agreement Study
- 4. The Statistical Analysis of Agreement-Two
Inspectors/Judges
- A. Two Inspectors-Two Categories
B. Two Inspectors-More
Than Two Categories
C. Testing Hypotheses Associated with Kappa
- 1) Testing the Hypothesis that K'=0
2) Testing the
Hypothesis that K' Equals a Value Other than 0.
3) Statistically Comparing
Two Independent Kappa Values
- 5. The Statistical Analysis of Validity (Accuracy) for
Nominal Data Systems
- 6. The Statistical Analysis of Agreement: Light's Extension
to More than Two Inspectors/Judges
- A. Procedures for Two Scale Categories
B. Procedures
for Scales with More Than Two Categories
C. Testing Hypotheses Associated
with K'
- 7. The Statistical Analysis of Agreement: Fleiss Extension to
More Than 3 Inspectors
- A. Procedures for Two Scale Categories
B. Procedures
for Scales with More Than Two Categories
C. Testing Applicable Hypotheses
- 8. Assessing Control and Capability of Measurement Systems
Yielding Nominal Data
Back to the top
Available Publications
A Procedure for the Statistical
Start-Up of New and Existing Production Systems
Click here to read a PDF
paper presented by ROI President Steven Ouellette on this subject. This
publication was the first in a series of Technical Aids published at variable
dates by Luftig & Warren International. The purpose of the documents in
this series is to provide practitioners with focused documentation or
strategies which may be employed in the effort to implement Total Quality. The
documents share a number of common elements:
- They are short, focused guides associated with a specific
problem or issue.
- They are based upon (to some degree) course material provided
to the practitioner through courses/seminars offered by The ROI Alliance.
- They are a direct response to needs expressed by
practitioners for materials or guidelines associated with the solution of
specific problems or the facilitation of practical and technical opportunities.
Content Outline
- 1. Introduction
- A. Statistically Qualifying New and Rebuilt Equipment and
Machinery
B. Statistical Start-Ups for New Systems, Lines, and Plants
C.
Advanced Quality Planning
- 2. Procedures for Statistical Start-Ups and General Screening
Experiments
- A. Critical Product/Process Characteristic
Identification
B. Initial QFD Table Development
C. Criterion Measure
Classification
D. Independent Variable Selection
E. Interaction Table and
Selection
F. Selected Experimental Design
G. Alias Structures
H.
Experiment Notification
I. Gauging Review, and Assessment
J. Assignment
of Responsibilities
K. Nonmanipulable Variable Monitoring
L. Sample
Engineering Log
M. Summary of Results
N. Final QFD Table
O. Procedure
Change Check sheet
P. Final Report Check sheet
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Elements of Strategic Planning and
Policy Deployment
This publication is the second in a series of Technical Aids
published at variable dates by Luftig & Warren International. As an
additional component in this series, this document serves as a Transparency
Guide and Resource Document in conjunction with a one day overview on this
topic.
While not intended as a stand-alone document, this guide
provides the Quality Practitioner and seminar participants alike with a number
of models, forms, and documentation details which may be employed in creating a
Policy Deployment system commensurate with the targeted culture and
organization.
Content Outline
- 1. Introduction
- 2. Basic Definitions and Premises
- 3. Developing the Strategic Planning and Policy Deployment
System
- A. Vision Statements
B. Mission Statements
C.
Strategic Plans
D. Business Plans
E. Focal Point Charts
F. Strategic
Product-Market Analysis
G. Customer Quality Assurance Guidelines
- 4. Forms and Checklists for the Management of a Policy
Deployment System
- 5. Daily Management Interface
- 6. PDCA Discipline Interface
- 7. Case study: The National Label Company: A Strategic
Planning and Policy Deployment Case Study
Back to the top
National Label Company: A Strategic
Planning and Policy Deployment Case Study
The purpose of this publication is to provide an exemplary model
of Strategic Planning and Policy Deployment. This document is intended to be
used as a supplement to Elements of Strategic Planning and Policy Deployment as
an illustrative example to be used in conjunction with the seminar.
Due to our proprietary requirements and our desire to protect
our clients' competitive positions, we are unable to provide examples from our
wide array of experiences in various industries. Therefore, we have created a
"factitious" company, known as the National Label Company, as a means to
illustrate the type of work undertaken in a deployment effort. This case study
is, in effect, the deployment of a single critical strategic issue into a
vertical slice of the organization. Though the example may be factitious, it is
representative of actual activities and practices undertaken on a routine basis
by companies practicing TQ as a means to manage their businesses.
While not intended as a stand-alone document, this guide
provides the Quality Practitioner and seminar participants with a comprehensive
example of Strategic Planning and Policy Deployment. Also included with the
technical aid is a 23 - 35 inch multicolored map of the various elements,
forms, documents, and analyses used to illustrate the deployment process.
Content Outline
- Visions, Values, Guiding Principles, and Corporate Mission
Statement
- Strategic Product-Market Analysis
- Customer Quality Assurance
- Strategic Plan
- Operating Plan
- Division Level
- Plant Level
- Department Level
- Section Level
Back to the top
Elements of Customer
Quality Assurance
This publication serves as the support documentation and
transparency guide for the Overview course in Customer Quality Assurance. It
provides a broad and comprehensive overview in the area of Customer Quality
Assurance (CQA).
Content Outline
- The Evolution of Customer Quality Assurance
- A Breakdown of the CQA Process
- The 9-Step Product Design and Planning Process
- 1. Identifying Served Markets
2.
Selecting/Identifying Key (Critical) Customers
3. Determining Customer
Requirements
4. Identifying Corresponding Design Requirements
5.
Designing and Engineering the Product/Service
6. Planning for
Manufacture/Delivery
7. Planning for Process Control
8. Sales and
After-Sale Service Considerations
9. Tracking Customer Satisfaction
- Premises and Requirements for a Customer Feedback System
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A Quality Improvement Strategy for
Critical Product and Process Characteristics
This publication is designed to provide the quality
practitioner, engineer, and other technical personnel with a comprehensive
description of the methodology associated with bringing critical product and
process characteristics into a state of control and capability. The methodology
is divided into four basic sections, and the procedures to be employed are
presented on a series of flowcharts.
While the flowcharts are generally self-explanatory, a
significant amount of understanding as related to industrial statistics and
experimental design on the part of the reader is assumed. This manual, in fact,
serves as a capstone document for the Experimental Design and Industrial
Statistics series offered by The ROI Alliance.
Content Outline
- Introduction to the Product/Process Quality Improvement
Strategy: Underlying Concepts and Assumptions
- Phase I — Measurement Analysis
- A. Accuracy Analysis
B. Precision Analysis
- Phase II — Product Characteristics Control and
Capability Analysis (Continuous/Variables and Discrete/Attribute Data)
- A. Control Chart Selection
B. Assessment of Process
Control
C. Assessment of Process Capability
- Phase III — First Order Critical Process
Characteristic Control and Capability Analysis: Assessment and Countermeasures
- Phase IV — Second and Third Order Critical Process
Characteristics Control and Capability Analysis: Assessment and Countermeasures
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Excursion Analysis
Most individuals working in industry are familiar with the
periodic "excursions" that plague a company from time-to-time. These
excursions, or "flares," may be those events which result in large batches,
lots, or groups of product generated with a uniform defect rendering large
quantities of material unacceptable to the customer. One can easily envision
how this type of event results in high scrap costs, as well as delivery
problems. Still other excursions are equipment related. Catastrophic failures,
and even explosions, are manifestations of these events.
The alarming part of these conditions, apart from the excursions
themselves, is that many personnel in the affected organization believe these
events to be "one ofs;" or completely unrelated. Few individuals see that there
may be a relationship, for example, between a thermocouple failure on a heat
treat furnace, a bearing failure on a rolling mill, and a shrink wrap machine
in a downstream facility hundreds of yards away. Root cause analysis performed
on each of these individual events may, in fact, draw no parallels between the
three incidents.
Excursion analysis is a unique model for systemic analysis which
allows management to understand that a root cause analysis is only a "first
step" in understanding failure patterns inherent to an industrial system.
Pioneered by Luftig & Warren International personnel working in the field
of Reliability Engineering, Excursion Analysis is a tool which allows personnel
to uncover the systemic, horizontally integrated "common threads" which
systemically allow the root causes to occur; and in turn allow the events to
erupt. A further unique aspect of this process is that occurrence and duration
are evaluated separately; allowing a company which implements this process to
see significant reductions in the financial effects of these excursions sooner,
rather than later. This Technical Aid provides the practitioner with an
explanation and step-by-step guide related to performing this activity in their
own company or administrative unit with limited consultative
assistance.
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Guidelines and Recommendations for
an Employee Suggestion System Within a TQM Model
This publication serves as a comprehensive guideline and
implementation plan for an appropriate Employee Suggestion System. This System
has been designed so as to allow for the full philosophical and mechanical
integration with the TQ model as designed by Luftig & Warren
International.
The recommended guidelines and strategies have been successfully
launched and tested at a number of companies across the United States; sample
experiences from these implementation efforts are also presented within this
Technical Aid.
Content Outline
- Introduction
- Elements of Problem-Solving with Suggestions
- Administrating the Employee Suggestion System
- Span of Control
- Implementing the Suggestion System
- Roles and Responsibilities of Managers, Supervisors, and
Employees
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Recommended Guidelines for Quarterly
Quality Reviews
This publication is the third in a series of Technical Aids
published at variable dates by Luftig & Warren International. This document
provides the Quality Practitioner with a tested and proven set of guidelines
for the conduct of Quarterly Quality Reviews.
In the implementation of any
Total Quality Management system, the Quarterly Quality Review (QQR) plays a
critical and central role in the "CHECK" component of the implementation
process. This document presents an outline for the conduct of the review; as
well as a comprehensive description of the documentation which should be
provided for the associated review. The documentation detailed conforms to
those elements contained in the Luftig & Warren model for Total Quality
Management (Reference: An Orientation to Total Quality transparency guide).
Content Outline
- 1. Introduction
2. General Description
3. Structure
of the Reviews
4. Documentation Requirements
- A. Focal Point Chart
B. Product/Process Improvement
Matrix
C. Dissatisfier Progress Reports
D. Internal Business Needs
E.
Projects
F. Team Management Sheets
G. Personnel Training and
Participation Matrix
H. Employee Suggestion System Report
- 5. Documentation Requirements for Designed Experiments
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Reliability Roadmap
The Reliability Roadmap is a Technical Aid developed to support
and enhance the course work associated with Process and Equipment Reliability
Methods. Equivalent to the flowcharts presented in the Quality Improvement
Strategy publication, this document contains a series of flowcharts intended to
allow the trained practitioner to take advantage of the "hidden factory" that
may exist in their current facility. Key sections provided allow the reader to
understand and deploy the methods required to select appropriate reliability
improvement tools, improve equipment purchasing procedures, specify new
equipment or machinery, and writing improved reliability
specifications.
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Total Quality: Key Terms and
Concepts
A Glossary of terms, phrases, and expressions associated with
Total Quality , and all of the other sub-categories of the Total Quality model.
Definitions of terms of a technical nature associated with the individual
elements comprising the field of Total Quality Assurance are also provided.
Published through the American Management Association.
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