The Six Big Losses in OEE: Manufacturing Guide

In manufacturing, being efficient is what keeps you ahead of the competition — there’s just no getting around it. One of the key things to measure and work on improving in that regard is Overall Equipment Effectiveness (OEE). If you want to get the most out of OEE, you need to be aware of the “Six Big Losses” — those common production problems that can bring down a manufacturing operation in any industry.

This in-depth guide will take you right through the nitty gritty of OEE in manufacturing, the six big losses that are a hallmark of lean manufacturing, and how you can tackle them to get better results for your business. We’ll also look at how putting your weight behind targeted efforts to eliminate these losses can really boost productivity and profit margins through making smart maintenance choices and sticking to the principles of Total Productive Maintenance (TPM).

What is Overall Equipment Effectiveness?

Overall Equipment Effectiveness (OEE) is a measure of just how well production equipment is holding up during the production process. It boils down to three key components:

OEE components	What it measures
Availability	How much of the planned production time the equipment is actually available to runUptime vs. downtime (including scheduled stops and planned stops)
Performance	How fast the equipment is operating as a percentage of its designed speedActual output vs. ideal output (includes slow cycles and minor stoppages)
Quality	What percentage of good parts are produced out of the total number of partsGood units vs. total units (includes production rejects and startup rejects)

The OEE Formula: Availability × Performance × Quality

This gives you a clear picture of the three OEE factors that determine overall operational efficiency. These three categories provide a comprehensive framework for understanding productivity loss and identifying improvement opportunities. OEE gives you a clear picture of how well your production process is running and where there’s room for improvement.

An OEE of 100% is basically impossible to achieve — it means no losses at all. In reality, world-class OEE is considered to be 85% or higher, while many facilities operate between 60-75%, showing there’s a lot of room for improvement.

The Six Big Losses in Manufacturing (OEE Framework)

The six big losses in lean are a universal framework within Total Productive Maintenance (TPM) and lean principles that categorize the top causes of production inefficiencies. Understanding these OEE losses is mission-critical if you want to improve overall machine performance and minimize downtime.

Here’s how the six big losses map to OEE components:

Loss category	OEE component affected	Types of losses
Availability Loss	Availability	Equipment Failure, Setup & Adjustment
Performance Loss	Performance	Small Stops, Reduced Speed
Quality Loss	Quality	Process Defects, Startup Losses

These big losses in manufacturing directly impact the three OEE factors and create measurable productivity losses. Let’s dive into each of them in more detail.

1. Equipment Failure

You know that feeling when your machinery just up and stops working because something unexpected has gone wrong? Maybe it’s a breakdown, or a tool fails, or something — whatever, the point is its completely halted production and that’s a big problem because it means you’re not producing anything while it’s down. That creates availability loss and before you know it you’ve lost loads of time and client satisfaction takes a hit.

So, what causes it?

• Mechanical wear and tear (I mean, we all know it’s gonna happen eventually).
• Poor lubrication and a lack of regular maintenance (I mean, come on, you should be doing that).
• Inexperienced operators who don’t know how to handle the equipment properly (training is key here, folks).
• Component fatigue (things get old and break, it’s just the way it is).
• Substandard materials which just get worn out way too fast (using cheap stuff is gonna come back to bite you).

When your equipment just gives up the ghost for a bit, it not only brings the current production line to a complete standstill but can also back up the machines that rely on that work-in-process coming through in a steady stream. Downtime reason codes can help you figure out the patterns and root causes behind all this and put in place some targeted maintenance strategies to keep it from happening again. If you’re using condition monitoring systems, you get real-time insights on the equipment’s health before it all goes wrong.

Tracking down some key metrics:

• Get a solid maintenance routine going — regular inspections and part replacements can really cut down on these breakages
• Use some proactive maintenance tools — that OEE data and condition monitoring can really help you spot potential problems before they turn into unplanned maintenance events.
• Train your operators to spot the early warning signs of equipment issues — they can make a big difference.
• Look into autonomous maintenance — empower your operators with CIL routines that include quick cleaning to catch problems early.

2. Setup and Adjustment Losses

Setup and adjustment losses are the ones that come about when you’re doing changeovers or adjusting tooling for a new production run, resulting in longer changeover times. These planned stops can really eat into your available scheduled production time and contribute to those availability losses. Sure, it’s a pain in the neck.

If you’ve got a packaging line that takes 45 minutes to switch between products, that’s 45 minutes you’re losing that you could be using to get more stuff done with some smart procedures.

So, what’s the fix?

• Standardize & simplify changeovers — SMED is the way to go here to cut those setup times way back.
• Schedule those setup activities — do them during planned downtime so you can minimize the impact.
• Get some automation going — that way you can cut down on manual adjustments and human error.
• Try some quick changeover techniques — just convert those internal tasks to external ones where possible.

3. Small Stops

You know, those little idling periods when equipment just stops — the ones that are only a minute or so but seem to add up to a bigger problem. Those are the small stops. They’re also known as idling and minor stoppages. They’re those tiny little pauses that cause lost production time.

We’ll be taking a closer look at all the big losses, and what you can do to fix ’em, so keep watching this space. These micro-stops can seem like no big deal individually, but over time they’re gonna start adding up and you’ll be looking at some serious performance losses. And the thing is those little hiccups might seem like just a minute blip on the radar but they can start stacking up and really cut into your efficiency.

The thing is, these short pauses often get left out of the manual tracking systems (you know, the ones where you just track it all down on paper) but they can have a huge impact on how much you actually get done. Short interval control (SIC) is the answer here — it helps figure out where these losses are coming from by taking a closer look at how the equipment is doing every 60-120 minutes.

So, what causes these annoying little stops?

• Misfeeds or jams — just plain old technical issues.
• Sensor issues — when the sensor gets clogged up and stops working.
• Gates or chutes get stuck — you see what I mean, just technical problems.
• Minor adjustments needed — maybe the machine just needs a tweak.

So how do you deal with these problems?

1. Find out what went wrong in the first place — use Pareto analysis and the 5-Why technique to figure it all out.
2. Fix the equipment — make sure it’s all calibrated and the sensors are where they need to be.
3. Train your operators — teach them how to handle these little stoppages so they don’t turn into big problems.
4. Use short interval control — check on the equipment regularly so you can catch the little problems before they get out of hand.
5. Get some digital performance boards going — that way you can make the losses visible in real-time and take action right away.

4. Reduced Speed

If your equipment is running slower than it should be, you’ve got a problem on your hands. It means it takes longer to get the job done and that’s causing performance loss. You’re left with a gap between what the equipment can do and what it’s actually producing.

Common causes are:

• Your equipment just gets old and worn out.
• Maintenance isn’t being done right.
• Equipment gets dirty or worn out (you’d think regular cleaning would be a given).
• The process is just plain inefficient (is it time to rethink how things are being done?).
• You’re running slow just to be safe ( cons are being played here, my friend).

The gap between what the machine can do and what you need it to do is the hidden capacity in your facility. It’s one of the big problems holding your equipment back.

Now, how do you deal with reduced speed?

• Get the equipment sorted out: Make sure its all running smoothly and properly maintained.
• Keep on top of the OEE data: See if any trends are emerging for speed reductions.
• Upgrade or replace old equipment because if its struggling to keep up, its time to consider a newer model.
• Get your equipment to take care of itself: Implement some kind of autonomous maintenance to cut down on downtime.
• Question everything: Think about whether your equipment is running as fast as it could be, and challenge any assumptions you might have been making about it.

5. Process Defects

You’re sitting there with a production line that’s churning out rejects — things that just don’t meet the quality standards. This usually happens because the machines are being operated incorrectly, or because there are process errors that need to be ironed out. And this all results in waste not just a bunch of materials getting thrown away, but also the lost production time that could have been spent making something good.

Looking at the scrap rate and first-pass yield (FPY) gives you a better idea of where these problems are coming from. When you understand where the defective parts are coming from, you can start to work out whether its the upstream equipment or just some issue with the current operation. From a first pass yield perspective, every single defect is a case of not getting it right the first time.

Some common problems that we see:

• We see people getting the equipment settings wrong.
• Equipment gets worn out from lack of maintenance.
• They’re using substandard raw materials.
• The staff hasn’t had enough training.
• The whole process is just a bit of a mess.

Ways to deal with defects:

• Take quality control seriously: we need to be using SPC and real-time monitoring.
• Go back and figure out what went wrong: the 5-Why technique can be really useful for getting to the root cause of a problem.
• Make sure the staff are properly trained: we need to be confident that the people working on the line know what they’re doing.
• Track first pass yield: this is a great indicator of where quality issues are coming from.
• Get the machines to detect problems in real time: we can automate the inspection process to cut down on human error.

6. Startup Losses

To be fair, its not surprising that there’s a bit of waste during the initial start-up of production. The process takes a little while to find its feet, and so we get a load of defective parts before things calm down and the process gets steady.

Some common causes of this:

• Startup procedures are a bit of a mess, people are doing things their own way.
• Equipment isn’t at the right temperature which can cause all sorts of problems.
• The process parameters aren’t stable yet, so we get a load of variants in quality.
• The operators are probably making a few mistakes along the way.

Ways to deal with startup problems:

• Get a handle on the startup procedures: make sure they’re the same every time.
• Have a look at those OEE data: use it to see where we can improve the efficiency of the start-up process.
• Automate the startup process if you can: advanced process control can be a real game-changer here.
• Get the equipment ready for production a little before the scheduled start time : sometimes its just easier to get a head start.
• Document the best practices: so the next person can follow the same procedure.

How to use OEE Data to Address the Six Big Losses

Using OEE data to identify and fix the biggest problems is a great way to turn your production around. By looking at the trends in your OEE data you can see what’s causing the biggest problems and fix them first.

• If OEE data shows frequent breakdowns then you’ve got to get on board with preventive maintenance — it’s a priority.
• If you’re consistently running at reduced speed then you’ll probably need to consider either upgrading your equipment or optimizing your process — one or both are probably needed.

OEE data also lets you benchmark performance, which means you can compare how different shifts, lines or facilities are doing and start implementing the best practices you find. When it comes to getting machines to run at their best its all about making improvement effort that addresses the Six Big Losses.

Real-World Examples

Loads of manufacturers have used the six big losses framework and OEE optimization to get some really significant results:

A packaging company got some great results:

• They found that small stops (micro-stoppages) were costing them 15% of their potential productivity.
• They put in short interval control and operator training to sort the problem.
• Their OEE went from 65% to 80% in six months and they recovered loads of lost production time.
• They got their return on investment within a year.
• They even got some happier customers in the deal thanks to their improved delivery reliability.

Automotive parts manufacturer:

• They got rid of yield loss in manufacturing by standardizing their equipment startup procedures.
• They sorted out reject starts by improving process control.
• They managed to get a 10% reduction in defective parts and some serious cost savings.
• They bumped their first pass yield up by 12%.
• They minimized the impact on the downstream equipment.

Food processing plant:

• They cut equipment failures by 20% with a predictive scheduled maintenance program.
• They set up condition monitoring and autonomous maintenance.
• They got a big bump in availability and reduced unplanned stops.
• They managed to increase overall production capacity without having to make any capital investment.
• They got a lot happier clients thanks to consistent quality.

These real world examples show just how much OEE improvement you can get by systematically addressing the 6 big losses. Reducing equipment handling errors and operators who aren’t skilled enough has been especially key to OEE improvement by cutting down on rejects.

OEE through Cultural and Technological Change

Building a Culture of Continuous Improvement

Where production excellence starts is with creating a culture that’s all about ongoing improvement. Everyone in the organization should be engaged in identifying and wiping out waste. Getting employees involved in initiatives like Kaizen events and Gemba walks creates an environment that’s really conducive to ongoing improvement.

Key cultural elements:

• Empowerment: Give your operators the power to make decisions and get involved with autonomous maintenance that includes regular quick cleaning.
• Visibility: Use digital performance boards to make performance transparent across all three categories.
• Accountability: Get in place short interval control so the team can jump on minor stops pretty quickly.
• Learning: Conduct systematic fundamental cause analysis to stop waste happening in the first place and to cut down on equipment downtime.

Digital Transformation

Technology plays a huge role in OEE optimization, getting production equipment to run at its best all through the manufacturing cycle. Solutions like real time monitoring systems, AI based analytics and predictive maintenance platforms give manufacturers a load more visibility into their operations than they used to have and lets them eliminate the need for hand-operated data gathering.

Key technologies:

• Real time monitoring: Keeps track of all three components all the time.
• Condition monitoring: Tells you when a piece of equipment is about to fail.
• Downtime code categorization: Standardizes loss categorization.
• Advanced analytics: Uses Pareto analysis to show you where to put your improvement effort first.
• Digital performance boards: Lets you visualize losses to get immediate action.

These systems can keep track of problems before they happen and give you actionable recommendations to stop downtime, increase productivity and improve quality so you can get happier customers.

Training the Workforce

Even the best tech is useless without skilled operators. Training programs need to equip employees with the knowledge and tools to operate equipment efficiently, troubleshoot issues and maintain high standards and address gaps in operator skills systematically.

Key areas to focus on:

• Autonomous maintenance: How to clean inspect and lubricate efficiently (CIL).
• Quick changeover: SMED principles and techniques.
• Quality awareness: Understanding first pass yield and defect prevention.
• Problem solving: Root cause analysis and 5 Whys.
• Data literacy: Understanding downtime reason codes and OEE metrics.

Cross training also gives you flexibility and reduces the impact of labour variability on production.

Advanced Insights: Reducing Production Losses

The Role of Automation in Fighting OEE Losses

Automation is key to reducing production losses across all six categories — it eliminates human error, reduces cycle times and improves consistency.

Automation applications:

• Automated inspection: Detects defects in real time and reduces production rejects.
• RPA (Robotic Process Automation): Streamlines setup and changeover by implementing SMED principles.
• Auto adjusting systems: Stops small stops by self correcting minor issues.
• Predictive algorithms: Stopped unplanned stops through condition monitoring.

Automating these processes stops human error, reduces cycle times and improves consistency throughout your operations.

Short-Interval Control (SIC)

Short interval control involves reviewing performance metrics every 60-120 minutes, not just waiting for shift or daily reports. This approach lets you catch and fix deviations while they’re still hot, preventing small stops and slow cycles from turning into major losses.

Steps to implement SIC:

1. Set clear interval targets — every hour or every two hours for example.
2. Track actual vs target at each interval.
3. Investigate deviations now, not later.
4. Take action to sort the problem before the next interval.
5. Document what you learn and any patterns that emerge.

Downtime Reason Codes

Having a standardized downtime reason codes in place creates a level playing field for tracking stoppages, making it easier to compare analytics and do some meaningful Pareto analysis across shifts, lines, and facilities.

Benefits of reason codes:

• A much more consistent way of classifying losses.
• Being able to accurately identify patterns is a huge deal.
• You can actually make informed decisions on where to make improvements.
• Benchmarking across different operations is a big plus.
• Looking at trends over time is really valuable.

FAQ