Imagine that a small manufacturing company has a CNC machine that is constantly running. Management assumes that the unit is operating efficiently, but when they pull actual production data they discover something to the contrary: not only does the machine stop several times per shift due to small jams, the operators frequently have to slow it down to avoid quality problems.
The data also reveals that shift changeovers take 45 minutes, and once the machine starts up again, it produces several scrap parts. Despite spending most of the day running, the machine is actually much less productive than assumed.
Management needs to understand what is causing those losses. One of the best methods for them to understand exactly what is causing the inefficiency is a metric called Overall Equipment Effectiveness (OEE).
Calculating OEE helps manufacturers measure equipment performance, identify the biggest sources of loss, and target specific problems without necessarily overhauling their entire operation. A 90-day improvement cycle provides a practical timeframe for an organization to establish a baseline, implement targeted actions, and measure the results.
What is Overall Equipment Effectiveness?
Overall Equipment Effectiveness is a manufacturing KPI designed to give organizations a clearer picture of how effectively their equipment is operating. OEE compares actual production performance with the equipment’s potential to produce good product and assigns a percentage score based on three factors: availability, performance, and quality.
Availability measures downtime: Is the equipment actually running when it is supposed to?
Performance looks at whether the machine is operating at its intended speed or capacity.
Quality examines how much of what is produced is actually good product and how much was waste or scrap.
Then, a simple formula is used to calculate OEE: Availability x Performance x Quality. For example:
- Availability = 90%
- Performance = 85%
- Quality = 98%
OEE = 90% x 85% x 98% = 75%
The OEE framework lets manufacturers stop guessing at a machine’s efficiency and start to get a realistic idea of where to focus improvement efforts.
Say a machine is operating 90% of its scheduled time, but its performance is running slower than its ideal cycle time, and produces some scrap. OEE doesn’t necessarily tell you why you’re losing productivity, but it helps you understand where to look.
What is a Good OEE Score?
In a perfect world, a 100% OEE score would mean equipment is producing only good product, at the ideal rate, with no downtime. In reality, that is impossible to achieve.
An OEE score of 85% is cited as a “world-class” benchmark for discrete manufacturing, representing a high output to quality ratio. A score around 60% is considered a typical OEE level. It represents solid output and quality, but acknowledges there is room for improvement. A company who is just beginning to measure OEE might see initial scores closer to 40%. Typical OEE scores vary significantly by industry and by product lines. There are several OEE benchmarking platforms that publish industry-specific OEE ranges and world-class targets.
These figures are reference points, and should not be treated as universal targets.
What Should OEE Improvement Look Like?
An 85% OEE score is a commonly cited benchmark, but isn’t necessarily the right target for every manufacturer.
OEE is highly dependent on factors like the specific equipment, production environment, batch size, product mix, changeover requirements, and the industry itself.
A small manufacturer who is just beginning to track OEE can see a great deal of success simply by moving from 45% OEE to 60%.
Improving OEE in manufacturing is about continuous, long-term improvement, reducing equipment downtime and scrap. Manufacturers shouldn’t get so caught up in chasing arbitrary percentages, and instead focus on small steps forward that can produce bigger benefits over time.
Identifying the Losses Behind an OEE Score
Within the OEE framework, there is the concept of the “Six Big Losses”. These six losses are split across the three OEE components of availability, performance and quality.
Availability Losses
The first loss is equipment failures and breakdowns. These are considered unplanned stops, and create downtime. Availability losses can be caused by motor failures, electrical faults, sensor failures or other mechanical breakdowns.
Second is setup and adjustment losses. These are planned stops. When equipment is being cleaned, adjusted, calibrated, or otherwise prepared for production during scheduled active time, it is not producing, thereby creating loss.
Performance Losses
The third type of loss includes idling and minor stops, when equipment stops for a short period of time. This can be because of a material jam, a minor adjustment, clearing a sensor, or waiting for material. These interruptions may seem insignificant, but they can add up to a surprising amount of lost production time.
The fourth type of loss is reduced speed. The machine may be running, but it is operating below its ideal production time. Suboptimal operational settings, improper line balancing, poor maintenance, excessive machine wear, or compensation for poor quality materials or product are some of the factors that reduce speed.
Quality Losses
The fifth loss includes startup rejects. When a machine starts up after a changeover, adjustment, or other interruption, it may potentially produce defective products before the process reaches stable production.
The sixth loss involves defective or scrapped products produced during normal operation. These are known as production rejects that require the product to be scrapped or reworked. These involve incorrect assembly, material defects, dimensional defects, surface defects, and contamination.
Together, the Six Big Losses framework helps manufacturers identify the sources of inefficiency that create low OEE scores and gives management an idea of where to focus their improvement efforts.
The 90-Day OEE Improvement Playbook
Manufacturers that are new to OEE measurement may find that their initial scores are lower than expected. That’s because the process often reveals losses that were previously undetected. However, OEE improvement isn’t about reaching a “magic number”. It’s about establishing a system of continuous improvement that will improve efficiency over months and years.
The core of OEE improvement follows a repeatable loop: measure performance, identify and prioritize the biggest losses, take corrective action, and measure again.
Organizations that follow this repeatable framework will begin to see real improvement.
Day 1–30: Establishing a Baseline
Week 1: Define How OEE is Measured in Your Operation and Select a Target
Whether it’s a machine with a known problem, a production line producing too much scrap, or a known bottleneck, select one initial target for OEE improvement. Before collecting data, define consistent OEE definitions for planned production time, changeover time, downtime, good parts, rejected parts, line speed standards, and other OEE inputs. Operators, supervisors, and management need to all be on the same page.
Week 2–4: Collect Data
Once a target is selected, you need to calculate its baseline OEE score. To do this, you must track the appropriate data for the machine or process: planned production time, downtime, total production, good production, rejected production, changeover time, ideal cycle times.
From this data you can calculate the machine’s Availability, Performance, Quality, and OEE score.
The goal for this period is to identify where losses are occurring before trying to fix them.
Day 30–60: Attacking the Biggest Losses
You have the data. Now it’s time to analyze it. Identify the largest downtime causes, the most frequent stops, highest-value improvement opportunities, and recurring quality problems.
From those, you can select the highest value improvement opportunities. Determine a specific action to take, assign a person or a team to it, and give them a deadline and an expected result.
Look for quick wins: improving preventive maintenance, eliminating recurring jams, standardizing changeover steps or startup procedures, or addressing an obvious source of scrap. Little wins over time compound into big improvements.
Day 61–90: Measure, Standardize, and Expand
You’ve collected the data and taken corrective action. Now it’s time to measure and compare against your baseline.
Ask: Did OEE improve? Was equipment downtime reduced? Did quality improve? Was the problem fixed, and did improvement hold?
If an improvement worked, standardize it. Document the new process. Train operators and update maintenance procedures. This becomes the new standard for operations.
Once you reach Day 90, you can target the next biggest loss from your initial baseline evaluation or proceed to another machine or line.
Turning OEE Data Into Actionable Improvement
Once you’ve measured a baseline OEE score and collected several weeks of production data, it’s time to turn it into actual improvement. The best place to start is by prioritizing the biggest losses.
Rank your losses by the amount of production time they consume, how frequently they occur, or their impact on output and quality. Instead of trying to fix everything at once, focus on one or two high-priority losses that offer the greatest opportunity for improvement.
Smaller manufacturers don’t necessarily need sophisticated software on day one to measure and track OEE performance. The priority should be capturing consistent, reliable data that can show where losses are occurring. However, creating a manufacturing KPI dashboard or using dedicated OEE software can bring data such as Availability, Performance, Quality, and OEE scores, downtime, production output, and scrap into a single view. This can make it easier to identify problems and determine what actions to take, but specialized software isn’t strictly necessary to begin improving OEE.
For example, if availability is one of your lowest scores, you might focus on strengthening preventive maintenance, improving spare-parts planning, and investigating the root cause of failures to reduce equipment downtime. Standardizing procedures and prepping tools in advance can reduce the amount of changeover time.
If performance is a problem area, consider investigating why a machine is experiencing frequent minor stops, jams, sensor problems, or material handling issues. Quality losses may require analyzing recurring defects or standardizing startup parameters.
The data alone won’t improve OEE, but it does give manufacturers the ability to identify problems and prioritize corrective actions. Taking the right actions is what produces measurable results.
Start Improving Today With Manex’s OEE Consulting Services
OEE improvement doesn’t end after 90 days. It’s about creating a repeatable framework for generating continuous improvement and eliminating losses over time. By establishing a reliable baseline, identifying the biggest sources of downtime, performance loss, and quality problems, manufacturers can turn lost production capacity into measurable gains by addressing the most important losses one at a time.
A 90-day improvement playbook provides an accessible starting point, but the real results only come when a manufacturer makes a long-term commitment to continuous improvement.
That’s where Manex can help. Our OEE consulting services can help you calculate your initial OEE scores, train your company on OEE principles, and help implement practical techniques you can use to start improving your equipment effectiveness.
Ready to identify where your organization’s equipment is holding you back? Contact Manex today to discuss your OEE improvement opportunities.
