
Explore a downloadable four-page glossary of terminology, covering availability, calendar time, choice-based losses, quality loss, planned downtime, and performance loss, to support your manufacturing effectiveness framework.
Distinguish choice-based losses from condition-based losses in manufacturing, from calendar time to planned downtime and breakdowns, and relate these losses to the major metrics OEE, OOE, and TEEP.
Master measuring manufacturing effectiveness with the downloadable key formulas sheet, covering OEE, OOE, and TEEP, input factors like availability, performance, quality, and reliability and maintainability.
Discover good output time as the numerator of oee, ooe, and teep by subtracting availability, performance, and quality losses from scheduled production time to identify good parts.
Analyze a calendar-based case study to compute operating time, planned downtime, and unplanned downtime. Determine the availability percentage by dividing available production time by scheduled production time, revealing 87.2 percent.
Define quality as good output divided by total output and examine yield loss and stability loss, including startup scrap, first piece adjustment, tool seeding and warm up.
Identify stability loss as unpredictable, non-repeatable losses during nominal operation that signal system instability and drive quality engineers to perform root cause analysis of special cause variation.
Identify how quality loss governs the final transition in the manufacturing time funnel and how maintenance, operating windows, recovery protocols, and organizational decisions determine sellable output.
Analyze a mini quality case to calculate quality loss and yield: 1,039 parts produced, 39 lost, yielding 3.8% quality loss and 96.2% good parts.
Explore special topics that help you interpret manufacturing effectiveness metrics as a diagnostic, root cause analysis system, covering planned versus unplanned downtime, availability, downtime behavior, and reporting significant digits.
Apply significant digits to measuring manufacturing effectiveness, including trailing zeros rules and the fewest digits rule in division, to report four significant digits for speed and accurate availability percentages.
Downtime behavior reveals how planned versus unplanned downtime affects availability and OEE, comparing long downtime events to frequent short faults and their distinct impacts on performance and quality.
Tackle a two-part practice problem set to reinforce measuring manufacturing effectiveness. Use your glossary, formula sheet, and notes for fill-in-the-blank items and analytical problems, with PDFs and answer key.
Discover how measuring manufacturing effectiveness ties to quality, inventory, and supply chain analytics, and explore related Excel-based courses in supply chain analytics, capacity planning, and inventory management.
In manufacturing, it's easy to focus on a single metric and assume it tells the whole story. OEE is a good example. It is widely used and widely discussed. But often misunderstood.
This course is designed to help you go beyond isolated formulas and learn the full system of manufacturing effectiveness metrics that gives those formulas real meaning.
In Measuring Manufacturing Effectiveness, you will learn how to evaluate manufacturing effectiveness using a practical, structured framework built around time, losses, and output. Rather than treating OEE as a standalone number, this course shows you how OEE, OOE, and TEEP work together as part of a broader measurement system that can help leaders and technical professionals better understand performance, identify hidden capacity, and make better decisions.
This course follows the same practical framework presented in my book Measuring Manufacturing Effectiveness, but it is taught with busy professionals in mind who want clear explanations, useful examples, and a logical path from concept to application.
You will learn how to:
Understand the manufacturing time funnel and the logic of time-based effectiveness measurement
Separate different types of losses and see how they affect output and utilization
Calculate and interpret OEE, OOE, and TEEP with confidence
Break effectiveness down into Availability, Performance, and Quality
Recognize why the misuse of isolated metrics can lead teams toward the wrong conclusions
Use a complete measurement system to uncover hidden capacity and prioritize improvement efforts more effectively
This is a practical course built for the real world. The emphasis is not on academic theory or unnecessary complexity. Instead, the focus is on clear thinking, sound metric interpretation, and practical application in manufacturing environments.
To help you apply what you learn, the course includes:
Downloadable Excel templates for workplace application
A full end-to-end case study
Intermediate topics such Availability Analysis, Significant Digits, Why Effectiveness Systems Fail, and Downtime Behavior.
Two sets of downloadable practice problems
A downloadable Key Formulas Sheet
A downloadable Glossary of Terminology PDF
LIFETIME ACCESS to the course contents
Q&A access to the course instructor
The course is organized into concise, focused lessons that build on one another. Most lectures are intentionally short and direct, making the material easier to absorb and revisit later.
Please remember: The real value of these metrics comes from understanding the full system ... not just memorizing a few formulas. Students who work through the entire course will be in a much stronger position to interpret results correctly and use these metrics at their facilities.
This course is especially valuable for:
Operations Managers
Plant Managers
General Managers
Production Managers
Manufacturing Engineers
Industrial Engineers
Process Engineers
Maintenance Managers
Reliability Engineers
Quality Engineers
Continuous Improvement Professionals
Supervisors and Engineers preparing for leadership roles
If you work in manufacturing and want a practical framework for understanding equipment effectiveness, capacity, utilization, and performance, this course was built for you. I would be glad to have you in the course.