on Tools & Techniques

My new book titled Measuring Manufacturing Effectiveness develops a practical framework for understanding manufacturing effectiveness through the lens of performance metrics including how they are defined, how they are interpreted, and how they influence real operational behavior.

Chapter 5 turns attention to the first of the three components of Overall Equipment Effectiveness (OEE): Availability.

Availability addresses a deceptively simple question: Can the equipment run when it is scheduled to run?
Behind that question sits a wide range of losses related to downtime, changeovers, failures, maintenance practices, and scheduling decisions.

This article is adapted from Chapter 4 of my book, Measuring Manufacturing Effectiveness.

The book is organized as a structured, multi-chapter examination of how manufacturing organizations define, measure, and interpret “effectiveness.” Rather than focusing on isolated metrics or individual tools, it treats measurement as a system, one that directly influences operational decisions, improvement priorities, and management behavior across manufacturing organizations.

Each chapter is written to stand on its own, while also contributing to a larger, integrated framework for understanding manufacturing performance.

Chapter 4 introduces the core components that make up Overall Equipment Effectiveness (OEE). While OEE is often presented as a single number, it is actually the product of three distinct elements, each representing a different category of loss and a different dimension of system performance.

This chapter provides an orientation to those components, explains what each is intended to capture, and establishes the conceptual foundation needed before OEE can be used meaningfully as a measurement or improvement tool.

This article is adapted from Chapter 3 of my book titled Measuring Manufacturing Effectiveness.

The book is organized as a structured, multi-chapter exploration of how manufacturing organizations define, measure, and interpret “effectiveness.” Rather than focusing on isolated metrics or tools, it examines measurement as a system; one that shapes decisions, priorities, and behavior across operations, quality, reliability, and management.

Each chapter is written to stand on its own, while also contributing to a larger, integrated framework for understanding manufacturing performance.

Chapter 3 focuses on three of the most commonly used, and most frequently misunderstood, manufacturing effectiveness metrics:

• Total Effective Equipment Performance (TEEP)
• Overall Operations Effectiveness (OOE)
• Overall Equipment Effectiveness (OEE)

Although these measures are often treated as variations of the same idea, they differ in important and meaningful ways. This chapter clarifies what each metric is designed to measure, the assumptions embedded in each definition, and the types of questions each metric is and is not capable of answering.

Measuring Manufacturing Effectiveness – Chapter 2: Manufacturing Time as a System

Over the past several years, I’ve been discovering a structured framework for understanding and improving how manufacturing organizations define, measure, and interpret “effectiveness.”

Not efficiency. Not productivity in isolation. Not isolated KPIs. But manufacturing effectiveness as a system that integrates operations, quality, reliability, capacity, flow, decision-making, and management behavior into a coherent measurement model. It may sound like a lofty goal. But please stay with me.

This article is drawn from Chapter 2 of my book, Measuring Manufacturing Effectiveness, which focuses on understanding time as a resource that is systematically reduced by cumulative and irreversible losses, at the end of which remains the time needed to manufacture good parts.

Finding Weaknesses Before the Customer Does

Co-authored with Mike Vella

One of the most effective analytical tools in reliability and quality engineering is Environmental Stress Screening (ESS).

ESS is a process designed to force latent defects to reveal themselves. It does this by applying controlled environmental stresses to hardware, accelerating the transition from hidden weakness to detectable failure.

The goal is not to test whether a product meets specifications. The goal is to flush out defects that already exist but have not yet developed into failures under normal conditions.