Relationship Analysis: OEE vs. Production Cost per Unit

In the world of manufacturing, machine efficiency not only affects the quantity of goods produced; it directly reflects the factory’s production cost per unit. One of the key metrics used globally to evaluate production line efficiency is OEE (Overall Equipment Effectiveness), which measures how effectively machine potential is utilized.

What is OEE (Overall Equipment Effectiveness)

In modern manufacturing, factories do not compete just on “volume” but on producing quickly, with high quality, and by using resources as efficiently as possible. OEE is a metric that allows factories to see a clear overview of production performance. Instead of looking only at the final count, it analyzes where efficiency is lost, such as machine downtime, slow production cycles, or defects.
Measuring OEE is an essential tool that allows organizations to identify Hidden Production Losses in the line and use that data for systematic process improvement

Cost per Unit is the average cost used to produce one unit of a product, calculated by dividing the total production costs by the actual number of units produced. If a factory can produce goods at a lower unit cost, the business can set more competitive prices or maintain higher profit margins.

The 3 Core Components of OEE

OEE is designed to reflect major losses in the production process through three key components: Availability, Performance, and Quality. Each component helps a factory analyze problems from different dimensions of the production process.

Availability (Machine Readiness)

Availability measures how much of the time the machine is actually running compared to the time it was scheduled to operate. If a machine stops, whether due to:
Machine setup or changeover
Maintenance
Machine breakdown or malfunction
Waiting for raw materials or production orders
These time losses immediately decrease the Availability value. For example, if a machine is scheduled to work for 8 hours but stops for a total of 1 hour, the actual production time is only 7 hours, which reduces Availability.

Performance (Production Speed Efficiency)

Performance measures whether the machine is producing as fast as its defined standard. Even if a machine is running continuously, if its production speed is below standard, it is still considered a loss. Causes for decreased Performance include:

Running slower than the Standard Cycle Time
Minor stops (Micro Stop)
Non-continuous production line flow
Improper raw material handling

This type of loss is often overlooked because the machine is still “running,” but in reality, the potential production capacity is significantly reduced.

Quality (Product Quality)

Quality measures the ratio of products that meet quality standards compared to the total number produced. If production results in:

Defects
Rework
Scrapped items

The quantity of sellable products decreases immediately, directly affecting the Quality value. For example, if 1,000 units are produced but 50 are defective, the Quality rate is 95%. The more defects there are, the more OEE decreases.

Why OEE has Become a Crucial KPI for Factories Worldwide

OEE has become a standard KPI for industrial factories globally because it can comprehensively reflect the efficiency of the production process in a single number. The key advantages of OEE are:

It helps factories see production process losses systematically.
It allows for the clear identification of the root causes of problems.
It helps in setting goals for the production process improvement.
It links production efficiency with production costs and business profit.

Furthermore, OEE is a vital tool in Lean Manufacturing and Total Productive Maintenance (TPM), which emphasizes continuous loss reduction and increased production efficiency. When an organization can consistently measure and track OEE, the factory can discover “Hidden Losses” in the process and use that data for sustainable production efficiency improvement.

What is Cost per Unit?

In the manufacturing industry, competition depends not only on the ability to produce goods but also on the ability to control the Cost per Unit. If a factory can produce goods at a lower cost, the business can set more competitive prices or maintain higher profit margins, even in highly competitive market conditions.

Cost per Unit is a critical metric that helps executives and production teams understand the actual cost of producing each individual item and which components of the production process contribute to those costs. Analyzing the cost per unit also allows factories to identify areas for improvement, such as:

Definition of Cost per Unit

Cost per Unit refers to the average cost incurred to produce one unit of a product. It is calculated by dividing the total cost of the entire production process by the actual number of units produced.

This figure helps factories answer key questions such as:

What is the actual cost to produce one item?
Which part of the production process contributes most to the cost?
How much can the cost per unit be reduced if production efficiency is increased?

When a factory can consistently track its Cost per Unit, it can control costs and plan production process improvements more accurately.

Examples of Production Cost Structure

Production costs in a factory typically consist of several components, which can be categorized into the following main groups:

1. Raw Material

Raw materials are the primary cost of the production process, particularly in industries that consume large quantities of materials, such as food and beverage, plastics, or electronics. Raw material costs include:

Price of primary raw materials
Transportation costs for materials
Storage and warehouse management costs

If the production process generates waste (Scrap) or uses materials beyond standard requirements, this cost portion increases immediately.

2. Labor

Labor costs refer to expenses related to employees in the production process, such as:

Salaries or wages
Overtime pay
Employee training costs
Benefits and other related expenses

While labor is a vital resource for a factory, the labor cost per unit will increase unnecessarily if the production process is inefficient—for instance, if workers must wait for machines or if work steps are improper.

3. Machine Cost

Machinery is considered a major asset for the factory and involves several types of costs, such as:

Depreciation
Maintenance
Spare parts
Preventive Maintenance

If machines break down frequently or have low efficiency, the incurred machine costs will be averaged over fewer products, resulting in a higher cost per unit.

4.Overhead

Overhead refers to expenses that cannot be directly attributed to each individual product but are still necessary for the production process, such as:

Factory rent
Building depreciation
Management costs
IT and support systems

These costs are often Fixed Costs, which do not change based on production volume in the short term.

5. Energy Cost

Energy costs are another significant factor impacting production costs, such as:

Electricity for machinery
Steam or gas is used in the process
Energy for cooling systems or factory air conditioning

If machines operate inefficiently or undergo frequent start-stops, the energy cost per unit will increase significantly.

The Relationship Between OEE and Production Cost per Unit

Although OEE is primarily used as a measure of production efficiency, it has a direct impact on the production cost per unit. When OEE decreases, production process losses increase, such as machine downtime, slower-than-standard production, and the occurrence of defects. Consequently, the factory produces fewer goods using the same amount of resources.

1. High OEE → Increased Output with the Same Resources

When OEE increases, it signifies that:

Machine downtime is reduced.
Production speed meets established standards.
Produced goods are of high quality.

These improvements allow a factory to increase output without adding more resources. In other words, more products are manufactured while using the same amount of machinery, labor, and time.

2. Averaging Down Fixed Costs

Many factory costs—such as machinery, buildings, basic labor, and overhead—are typically fixed costs that do not change based on short-term production volume. When a factory increases its production volume, these fixed costs are averaged down per unit.

For example:

If fixed costs are 100,000 baht per day.
Producing 10,000 units results in a cost of 10 baht per unit.
Increasing production to 12,000 units reduces the cost to 8.33 baht per unit.

By simply increasing production efficiency, unit costs can be reduced immediately.

3. Reduction in Cost per Unit

As OEE improves, factories gain several simultaneous benefits:

Reduced machine downtime.
Decreased production waste.
Increased line production capacity.

The final result is a decrease in the production cost per unit, which directly impacts product competitiveness, corporate profit margins, and the overall value of machinery investment.

4. The Fundamental Equation of This Relationship

The relationship between OEE and unit cost can be explained by a simple concept:

Production Output ↑ → Cost per Unit ↓

When a factory increases production efficiency and reduces process losses, the number of goods produced increases while total costs do not rise proportionally. This results in a lower average cost per piece. This is why organizations worldwide prioritize OEE improvement; even minor efficiency gains can lead to massive long-term production cost savings.

How Low OEE Increases Costs ?

While many factories view OEE as just a KPI reflecting machine performance, a lower OEE directly and significantly impacts the Cost per Unit. This is primarily because most factory expenses are Fixed Costs—such as labor, machinery, buildings, or overhead—which persist even when machines are not producing at full capacity. As production efficiency drops, the actual number of goods produced decreases, forcing total costs to be averaged over fewer items, thus automatically increasing the unit cost.

The factors that lower OEE generally stem from Production Loss, which can be categorized as follows:

1. Downtime Loss: Stopped Machines = No Production, but Costs Persist

Downtime Loss is the waste resulting from unplanned machine stoppages, such as:

Machine breakdowns
Waiting for technicians/repairs
Waiting for raw materials
Stoppages for machine setup or adjustment

During downtime, the factory cannot produce goods, yet expenses continue, including online labor wages, machine depreciation, basic factory electricity, and overhead. For example, if a machine stops for one hour a day on a line that should produce 100 pieces per hour, the factory loses 100 units of daily capacity, unnecessarily driving up the Cost per Unit.

2. Speed Loss: Slow Machines = Low Productivity

Speed Loss occurs when a machine operates slower than its designed speed or Ideal Cycle Time. Common causes include:

Deteriorated machinery
Improper parameter settings
Operators are reducing speed to prevent defects
Upstream or downstream process issues

Even if the machine is running, operating below standard means the factory fails to meet its potential production capacity. For instance, if a machine should produce 120 pieces per hour but only produces 90, the factory loses 25% of its capacity. Since labor, machine, and energy costs remain the same during that period, the cost per piece increases immediately.

3. Quality Loss: Defects = Rework Required

Quality Loss is the waste generated by products that do not meet quality standards, such as:

Damaged goods
Items requiring rework
Scrapped items

Defects significantly impact costs because producing a single item consumes various resources, including raw materials, labor, machine time, and energy. If a product cannot be sold, the factory must produce a replacement. For example, a 5% defect rate means that for every 100 pieces produced, an additional 5 must be made to compensate for the waste, turning the resources used on the original 5 into wasted costs.

4. Startup Loss: Initial Running Period = Long Time Before Stable

Startup Loss occurs at the beginning of a production run after a machine is turned on or after a changeover. During this phase, machines often do not operate at full efficiency due to:

Multiple required parameter adjustments
Initial production run defects
The need for operators to test-run machines before actual production

If the startup period lasts a long time (e.g., 30–60 minutes) before the line reaches Stable Production, the factory loses significant capacity. Many organizations overlook this because they fail to strictly measure Run-to-Stable Time, allowing these daily small losses to accumulate into massive long-term production costs.

Hidden Losses that Lower OEE Without the Factory Realizing It

Beyond obvious losses like machine breakdowns or production defects, there are Hidden Losses occurring on the production line that many factories may not immediately notice. While these losses typically occur in small increments, they can significantly reduce overall production efficiency when accumulated throughout the day.

1. Micro Stop

Micro stops are brief machine interruptions lasting only a few seconds or dozens of seconds. Examples include:

Workpieces are getting jammed in the machine.
Sensor detection errors.
Operators need to adjust the position of a workpiece.

Although each individual stop is very short, if they occur hundreds of times per day, they significantly reduce production capacity.

2. Waste of Motion

Waste of motion refers to unnecessary employee movements that do not add value, such as:

Walking far to retrieve tools.
Bending down to search for parts in a box.
Turning back and forth between workstations.

Even if each movement takes only a few seconds, repeated occurrences throughout the day increase the work cycle time and decrease line productivity.

3. Changeover Delay

Changeover delay is the excessive time spent switching production models. Examples include:

Lengthy machine adjustments.
Lack of preparedness in equipment.
Unclear communication between teams.

If changeovers take too long, the factory loses a massive amount of production time daily.

4. Waiting Time

Waiting time occurs when employees or machines must wait for certain conditions to be met, such as:

Waiting for raw materials.
Waiting for an upstream machine.
Waiting for quality inspections.

These delays prevent the production line from working continuously, leading to a decrease in overall production capacity.

5. Poor Line Balance

Imbalanced line synchronization is another major cause of hidden loss. If some stations work faster while others are slower, it causes:

Bottlenecks.
Waiting within the production line.
Accumulation of work-in-progress (WIP) between processes.

The result is that the production line cannot operate at full efficiency.

6. How Hidden Loss Affects Cost per Unit

While hidden losses may seem like small issues, their continuous occurrence leads to:

Decreased Production Output: When output decreases while total factory costs remain the same.
Higher Cost per Unit: As a direct result of lower output, the cost per unit increases.

This is a key reason many factories are now prioritizing detailed OEE and production loss analysis to identify hidden losses and sustainably improve production processes

Methods to Increase OEE for Reducing Unit Production Costs

Once an organization understands that OEE (Overall Equipment Effectiveness) is directly related to the Cost per Unit, the next step is finding ways to increase machine and process efficiency. The primary principle is to reduce Production Loss in the manufacturing system—whether it be machine stoppages, slower-than-standard production, or process waste. Reducing these losses increases production capacity, allowing fixed costs to be averaged over more products, which significantly lowers the Cost per Unit.

There are four main areas for increasing OEE:

1. Reducing Downtime

A major cause of decreased Availability in OEE is machine downtime, which results in immediate capacity loss. Downtime can be reduced through systematic maintenance management:

Preventive Maintenance

PM involves planned, periodic inspections and care for machinery:

Checking parts prone to wear and tear.
Replacing spare parts according to a schedule.
Inspecting electrical systems and sensors. Regular PM reduces the risk of sudden machine breakdowns, which are among the costliest causes of downtime.

2. Improving Cycle Time

Excessive Cycle Time reduces factory productivity and lowers the Performance score in OEE. Improving this is a key way to increase capacity without extra machinery investment:

Line Balancing

This involves balancing work across stations so every step in the line takes roughly the same amount of time. If one station takes longer than others, it creates a bottleneck, causing other stations to wait. Analyzing line balance allows a factory to:

Adjust work allocation at each station.
Add or adjust staff positions.
Improve work procedures for continuous, efficient flow.

Bottleneck Removal

A bottleneck is the slowest point that determines the capacity of the entire line. Resolving it can rapidly increase capacity by:
Upgrading bottleneck machinery.
Eliminating unnecessary work steps.
Adding assistive tools or equipment. Fixing bottlenecks increases speed and output without raising fixed costs.

3. Reducing Quality Loss

Defects and scrap lower the OEE Quality rate and increase unit costs because every defect wastes raw materials, machine time, labor, and energy.

Quality Control

An effective QC system reduces defects through:

In-process Inspection: Checking quality during the process.
Automated Inspection: Utilizing automated systems for checks.
Root Cause Analysis: Analyzing the source of quality issues.

Process Standardization

Clear standards, such as Standard Operating Procedures (SOP), Standard Work Instructions, and proper machine parameters, ensure everyone works to the same standard. This reduces errors caused by inconsistent methods and stabilizes the production process.

4. Reducing Startup Loss

Startup Loss occurs at the beginning of production or after a changeover when machines are not yet at full efficiency. This often involves multiple parameter adjustments, initial defects, or trial runs. If this period is long, significant capacity is lost unnoticed.

Standard Work

Defining standard work for startup—such as specific machine settings, pre-production checks, and parameter adjustment methods—helps teams reach full speed faster and reduces early errors.

Run-to-Stable Time Analysis

This measures the time from machine start until the process reaches a stable state. Reducing this time (e.g., from 45 minutes to 20 minutes) can greatly increase long-term capacity.

Utilizing Data and Digital Tools to Increase OEE

Modern factories use Smart Factory digital tools to increase analysis accuracy

1. Real-time Production Monitoring

Systems connect to machines via IoT or PLC to automatically collect data such as machine status, cycle time, output, and stoppage time. This allows managers to see the production situation immediately.

2. Loss Analysis

Continuous data collection allows for accurate analysis of Production Loss (Downtime, Speed, Quality, and Micro Stops). Pareto Analysis helps factories identify the primary causes of loss and prioritize improvements effectively.

3. Data-driven Improvement

Data-driven improvement removes guesswork from decision-making. Organizations can:

Measure actual improvement results.
Compare Before–After data.
Clearly track the outcomes of Kaizen projects.

Production Solutions to Increase OEE and Reduce Costs

Modern factories prioritize integrating technology into production management, and Solwer offers several solutions that tangibly increase production efficiency and reduce costs.

1. Loss Tracker

The Loss Tracker is a system that automatically records and analyzes production process losses. The system can:

Record machine stoppage data.
Categorize types of Production Loss.
Analyze the root causes of loss. This enables factories to identify actual problems rapidly.

2. Production Monitoring

The Production Monitoring system tracks the status of production lines in real-time. Executives can view critical information, such as:

Output for each line.
Machine efficiency.
Current production status. This allows for immediate problem-solving when abnormalities occur.

3. Digital Factory Dashboard

The Digital Factory Dashboard is a centralized display for production data that gives executives a clear overview of the entire factory. Displayed data includes:

OEE for each machine.
Production output.
Downtime analysis.
Performance trends.

Key benefits of these systems include:

Viewing Production Loss in real-time.
Performing rapid Pareto Loss analysis.
Identifying production process bottlenecks.
Improving productivity faster.

When an organization can clearly visualize production data, decision-making for process improvement becomes more accurate. This helps factories increase OEE and sustainably reduce the cost per unit.

The clear relationship between OEE (Overall Equipment Effectiveness) and Cost per Unit demonstrates that machine and process efficiency directly affects cost control. Increasing OEE—whether by reducing downtime, increasing production speed, or reducing waste—increases total production volume. This allows fixed costs to be averaged over more pieces, significantly lowering the cost per unit.

Conversely, low OEE means the factory faces high production losses, such as frequent stoppages, slow production, or waste. These issues decrease output while costs remain constant, unnecessarily driving up the cost per unit.

To maintain long-term competitiveness, factories must prioritize continuously measuring, analyzing, and improving OEE. Combining this focus with digital technology allows organizations to reduce Production Loss, increase productivity, and sustainably control unit costs.

For a deeper understanding of how OEE impacts efficiency and costs, including methods to find and reduce hidden production losses, consult Solwer’s E-book, which compiles concepts, tools, and digital technology strategies for systematic production enhancement.

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Relationship Analysis: OEE vs. Unit Production Cost