on Tools & Techniques

This article is adapted from Chapter 8 of my book, Measuring Manufacturing Effectiveness.

The book explores how manufacturing organizations define and use performance metrics, and how those definitions influence operational decisions, improvement efforts, and management behavior. While the chapters form a connected framework, each is written to address a specific aspect of manufacturing effectiveness and can be read independently.

Performance loss is often described in overly simple terms—the equipment is running slower than it should. While speed is certainly part of the story, this narrow view hides a much broader set of losses that affect output, flow, and stability.

Chapter 8 expands the discussion of performance loss beyond basic speed shortfalls. It examines how interruptions, minor stops, micro-downtime, variability, and operating practices contribute to lost performance—even when equipment appears to be running continuously.

By broadening how performance loss is defined and observed, this chapter aims to improve how organizations diagnose problems and select effective improvement actions.

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This article is adapted from Chapter 8 of my book, Measuring Manufacturing Effectiveness.

The book explores how manufacturing organizations define and use performance metrics, and how those definitions influence operational decisions, improvement efforts, and management behavior. While the chapters form a connected framework, each is written to address a specific aspect of manufacturing effectiveness and can be read independently.

Performance loss is often described in overly simple terms—the equipment is running slower than it should. While speed is certainly part of the story, this narrow view hides a much broader set of losses that affect output, flow, and stability.

Chapter 8 expands the discussion of performance loss beyond basic speed shortfalls. It examines how interruptions, minor stops, micro-downtime, variability, and operating practices contribute to lost performance—even when equipment appears to be running continuously.

By broadening how performance loss is defined and observed, this chapter aims to improve how organizations diagnose problems and select effective improvement actions.

[Read more…]

This article is adapted from Chapter 6 of my book, Measuring Manufacturing Effectiveness.

The book examines how manufacturing organizations define and use performance metrics, and how those measurement choices influence decisions, priorities, and behavior on the shop floor and in management. While the chapters are organized as a cohesive framework, each one is written to address a specific aspect of manufacturing effectiveness and can be read independently.

Chapter 6 focuses on a critical but often oversimplified topic: downtime.

Most organizations track downtime in some form, but far fewer distinguish meaningfully between how often downtime occurs and how long it lasts. These two dimensions — frequency and duration — are frequently combined, averaged, or summarized in ways that mask important operational realities.

This chapter explores why separating downtime frequency from downtime duration matters, how each dimension points to different underlying causes, and how failing to distinguish between them can lead to ineffective or misdirected improvement efforts.

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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.

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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.

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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.

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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.

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