Manufacturing KPIs You Should Be Tracking
- 77 Teknik
- Aug 12
- 11 min read
Updated: Aug 18
Unlocking Insights to Drive Performance, Efficiency, and Quality
In modern manufacturing, data isn’t optional it’s the foundation of smarter decision making, leaner operations, and higher customer satisfaction. But which metrics actually matter?
At 77 Teknik, we focus on tracking the most relevant manufacturing KPIs (Key Performance Indicators) to ensure operational excellence, consistent quality, and timely delivery. Here’s a breakdown of the top Manufacturing KPIs you should be monitoring.
1. Overall Equipment Effectiveness (OEE)
What it measures: Utilization of production equipment, considering availability, performance, and quality.
Why it matters: A high OEE means you’re making the most of your resources. It helps identify downtime, bottlenecks, and inefficiencies.
In modern manufacturing, efficiency is everything. But how can you truly measure how well your machines are performing? That’s where OEE (Overall Equipment Effectiveness) comes in.
OEE is a gold standard metric used to evaluate how effectively a manufacturing process is utilized. It helps you uncover losses and improve productivity on the shop floor.
What Does OEE Measure?
OEE combines three key factors:
Metric | Description |
Availability | How much of the scheduled time the machine is actually running |
Performance | How fast the machine runs compared to its maximum speed |
Quality | How many good parts were produced |
Formula:
OEE = Availability × Performance × Quality
Each factor is calculated as:
Availability (%) = (Run Time / Planned Production Time) × 100
Performance (%) = (Ideal Cycle Time × Total Pieces) / Run Time × 100
Quality (%) = (Good Pieces / Total Pieces) × 100
How to Interpret OEE?
OEE Score | Interpretation |
85% – 100% | World class performance |
60% – 85% | Acceptable but has optimization gaps |
< 60% | Inefficient, improvement needed |
Sample OEE Calculation
Let’s look at a real world example from a CNC machine during one 8-hour shift (480 minutes):
Parameter | Value |
Planned Production Time | 480 minutes |
Downtime | 60 minutes |
Total Parts Produced | 300 units |
Good Parts Produced | 270 units |
Ideal Cycle Time | 1 min / piece |
Availability
Availability= (480−60) / 480=420 / 480 =87.5%
Performance
Performance= (1×300) / 420= 300 / 420 =71.4%
Quality
Quality= 270 / 300 = 90%
OEE Result
OEE=87.5%×71.4%×90%=56.2% ( Inefficient, improvement needed )
Why Track OEE?
OEE is more than just a performance score it reveals the true causes of inefficiency:
Availability losses → unplanned stops, breakdowns
Performance losses → slow cycles, minor stoppages
Quality losses → scrap, rework, defects
Tracking OEE regularly helps manufacturers:
Reduce downtime
Increase output
Maintain high product quality
Improve delivery reliability
OEE = Continuous Improvement
Want to improve your OEE? Start by identifying the biggest loss area is it availability, performance, or quality? From there, apply lean methods like SMED, TPM, or root cause analysis to target the bottleneck.
OEE is an essential KPI for any manufacturing company that wants to boost efficiency and reduce waste. Whether you're running CNC machines, assembly lines, or packaging systems, tracking OEE puts you on the path to world class performance.
2. On-Time Delivery Rate (OTD)
What it measures: Percentage of orders delivered on or before the agreed deadline.
Why it matters: This KPI reflects supply chain reliability and customer satisfaction. It’s a critical metric for maintaining trust in B2B manufacturing.
In a competitive manufacturing and logistics environment, delivering on time isn't just a goal it’s an expectation. On-Time Delivery Rate (OTD) is a key performance indicator (KPI) that helps measure your ability to meet customer deadlines reliably.
Let’s explore what OTD is, how it’s calculated, and how to interpret the results for continuous improvement.
On-Time Delivery Rate (OTD) measures the percentage of customer orders delivered on or before the promised date.
It helps answer a critical question: “Are we keeping our delivery promises?”
Formula:
OTD Rate=( Number of On-Time Deliveries / Total Number of Deliveries )×100
How to Interpret OTD Results?
OTD Rate | Performance Level |
95% – 100% | Excellent – Highly reliable |
85% – 94% | Good – Minor gaps exist |
< 85% | Needs Improvement |
Sample OTD Calculation
Let’s say your company made 250 deliveries in a given month.
On-time Deliveries: 230
Late Deliveries: 20
OTD Rate=(230 /250)×100=92% ( Good – Minor gaps exist )
Why Track OTD?
Customer satisfaction: On-time shipments build trust.
Operational efficiency: Late deliveries often indicate bottlenecks or planning issues.
Cost control: Delays can result in penalties, rush shipping, or lost clients.
To Improve OTD
Improve production planning and lead time accuracy
Monitor supplier reliability
Use real time tracking for logistics
Perform root cause analysis for late deliveries
Align with customers on realistic delivery promises
A high On-Time Delivery Rate is a sign of operational maturity and customer centric service. By consistently measuring and improving OTD, you can enhance both your reputation and your bottom line.
OTD is not just a logistics metric it’s a commitment to your customers.
3. Capacity Utilization
What it measures:
How much of your total available manufacturing capacity is being used.
Why it matters:
It shows whether you’re underutilizing your resources or approaching production limits.
In manufacturing, it's not just about what you produce it's about what you could be producing. Capacity Utilization is a vital metric that measures how effectively you're using your available production capacity.
A low capacity utilization rate may indicate wasted resources, while a very high rate could signal overburdened equipment or risk of downtime.
Formula:
Capacity Utilization (%)=( Actual Output / Maximum Possible Output )×10044
How to Interpret Capacity Utilization?
Utilization Rate | Interpretation |
85% – 100% | Optimal – High efficiency |
70% – 84% | Acceptable – Some unused capacity |
< 70% | Underutilized – Potential waste |
Note: 100% is not always ideal. Constant maximum utilization may lead to wear and breakdowns. Aim for a healthy buffer.
Sample Capacity Utilization Calculation
Let’s say your machining center can produce 2,000 parts per month at full capacity.
Actual Output: 1,600 parts
Maximum Output: 2,000 parts
Capacity Utilization=(1600 / 2000)×100=80 % ( Acceptable – Some unused capacity )
Why Capacity Utilization ?
Helps with production planning
Identifies bottlenecks or idle resources
Supports investment decisions (new machines, more staff)
Affects unit cost the more efficiently you produce, the lower your per unit overhead
To Improve Capacity Utilization
Balance workloads across shifts
Reduce setup/changeover times (apply SMED)
Improve machine uptime through preventive maintenance
Streamline scheduling with real time data
Expand capacity only when utilization is consistently high
Capacity Utilization is one of the most practical indicators of operational health. It helps decision makers align production goals with real world constraints and opportunities.
Track it. Analyze it. Optimize it.
4. First Pass Yield (FPY)
What it measures: Percentage of products manufactured correctly without any rework.
Why it matters:A high FPY means less waste and higher efficiency crucial for quality control and lean manufacturing.
In high precision manufacturing, quality isn’t optional, it’s essential. One of the most effective ways to monitor process quality is through First Pass Yield (FPY). This metric shows how many units make it through production without needing rework, repair, or rejection. It's also known as:
Throughput Yield
First Time Yield
Formula
FPY (%)=( Good Units / Total Units Processed )×100
How to Interpret FPY Results
FPY Rate | Meaning |
98% – 100% | Excellent – World class process control |
90% – 97% | Good – Some minor quality loss |
< 90% | Needs attention – Significant waste |
Note: FPY can also be calculated per station or step in complex assemblies.
Sample FPY Calculation
Let’s assume a CNC line processes 500 parts in a day:
Good parts on first pass: 455
Reworked parts: 30
Scrapped parts: 15
FPY=( 455 / 500 )× 100= 91 % ( Good – Some minor quality loss )
Why FPY ?
Reduces rework and scrap costs
Indicates process stability
Improves delivery timelines
Enhances customer satisfaction
Supports ISO and Six Sigma initiatives
To Improve FPY
Conduct root cause analysis on defects
Train operators and standardize work instructions
Calibrate tools and maintain machines regularly
Use in process inspections to catch defects early
Apply poka-yoke (error-proofing) techniques
First Pass Yield is a powerful metric not just for quality control, but for operational efficiency. A higher FPY means smoother production, lower costs, and happier customers.
What passes the first time, saves time every time.
5. Scrap Rate
What it measures: Amount of material or product discarded due to defects or errors.
Why it matters: Helps identify recurring issues, reduce waste, and improve cost efficiency.
In every production environment, waste is the enemy of efficiency. One of the clearest indicators of waste is your Scrap Rate a critical quality and cost KPI that tells you how many units or materials are being discarded instead of shipped.
Monitoring scrap helps manufacturers identify process issues, reduce material loss, and improve profitability.
These items cannot be reworked or recovered , they are written off as waste.
Formula
Scrap Rate (%)=( Scrapped Units / Total Units Produced )×100
How to Interpret Scrap Rate
Scrap Rate | Interpretation |
< 1% | Excellent, Very low material loss |
1% – 3% | Acceptable, Monitor closely |
> 3% | High waste, Needs corrective action |
Note: Benchmarks vary by industry. High precision sectors (like aerospace or medical) often target scrap rates well below 1%.
Sample Scrap Rate Calculation
Suppose your production line outputs 1,000 parts in a shift.
Scrapped Units: 35
Total Produced Units: 1,000
Scrap Rate=( 35/1000 )×100=3.5% (High waste, Needs corrective action )
Why Scrap Rate ?
Directly impacts material cost and profit margin
Affects machine efficiency and operator productivity
Drives lean manufacturing efforts and Six Sigma projects
Reflects the consistency and capability of production processes
To Reduce Scrap Rate
Analyze root causes of defects (e.g., machine calibration, human error)
Train staff on standard work and quality checks
Improve raw material handling and storage
Introduce poka-yoke (error-proofing) at critical steps
Monitor and maintain tooling and equipment proactively
Automate inspections with vision systems
Scrap Rate may seem like a small number, but it reveals big problems. Tracking it closely helps manufacturers cut costs, boost sustainability, and build more reliable processes.
Every scrap is a cost , but also an opportunity to improve.
6. Cycle Time
What it measures: Time taken to produce one unit, from start to finish.
Why it matters: It impacts lead time, throughput, and customer satisfaction. Reducing cycle time is often key to scaling operations.
In any production line, time is money and one of the most important time based metrics is Cycle Time. It defines how long it takes to produce one unit from start to finish and serves as a foundation for productivity, lead time planning, and capacity analysis.
It includes:
Processing time
Handling/movement between steps
Waiting or queuing time (optional, depending on definition)
Let’s explore what cycle time is, how to calculate it, and how to use it to improve operations.
Formula
There are two common ways to calculate average cycle time:
1. Time based calculation:
Cycle Time= Total Production Time / Number of Units Produced
2. Observation based (Stopwatch method):
Measured by timing the duration it takes to complete a unit directly at the workstation.
How to Interpret Cycle Time
Cycle Time Performance | Meaning |
Decreasing | Improved efficiency / less waste |
Increasing | Potential bottlenecks / process delays |
Stable & predictable | Process is under control |
Ideal cycle time depends on product type, complexity, and industry standards
Sample Cycle Time Calculation
Let’s say your CNC machine runs for 6 hours (360 minutes) and produces 120 components.
Cycle Time= 360 minutes / 120 units= 3 minutes/unit
Why Cycle Time ?
Helps balance line efficiency and takt time
Affects lead time and order delivery
Reveals bottlenecks and waiting time
Supports capacity planning and cost per unit analysis
How to Optimize Cycle Time
Use SMED to reduce setup time
Eliminate non value adding tasks (motion, waiting)
Automate repetitive steps
Balance workloads across workstations
Use time studies and value stream mapping
Apply Lean tools (5S, Kaizen) to remove delays
Cycle Time is a core metric that connects speed, cost, and capacity. Whether you’re optimizing a CNC cell or a packaging line, understanding your cycle time is the first step toward a faster, more predictable operation.
What gets measured gets improved and what’s timed gets faster.
7. Production Downtime
What it measures: Duration and frequency of unplanned production stoppages.
Why it matters: Downtime directly affects profitability. Monitoring this KPI helps with predictive maintenance and scheduling efficiency.
In manufacturing, downtime is the silent killer of productivity. Every minute a machine isn’t running, money is lost, not just in output, but in labor, delivery delays, and customer trust.
Tracking and reducing Production Downtime is a key priority for any factory focused on efficiency and continuous improvement.
Types of Downtime
Downtime Type | Description | Example |
Planned | Scheduled maintenance or changeovers | Tooling setup, cleaning, training |
Unplanned | Unexpected stoppages | Machine breakdown, operator error |
Idle Time | Waiting for material, info, or labor | Missing part, delayed approval |
Formula
Downtime Rate (%)=( Downtime Duration / Total Available Production Time )×100
How to Interpret Downtime Rates
Downtime % | Interpretation |
< 5% | Excellent – High equipment availability |
5% – 10% | Acceptable – Monitor for improvement |
> 10% | High – Investigate and act immediately |
OEE calculations typically use Availability = (Run Time / Planned Time), which includes the impact of downtime.
Downtime Example
Let’s say your production shift is 8 hours (480 minutes), and your equipment was down for 72 minutes.
Downtime Rate=(72/480)×100=15% ( High – Investigate and act immediately )
Why Downtime Hurts ?
Loss of output and revenue
Labor cost without production
Risk of delayed customer shipments
Increased stress on equipment and operators
Lower overall equipment effectiveness (OEE)
To Reduce Downtime
Apply Preventive Maintenance (PM) schedules
Use Root Cause Analysis (RCA) on repeated failures
Track and categorize downtime with software
Improve changeover times (apply SMED)
Train operators on minor troubleshooting
Maintain spare part inventory for fast repairs
Monitor machines with IoT or MES systems
Downtime is one of the biggest hidden costs in manufacturing and one of the most preventable. By measuring it clearly and acting on the causes, factories can unlock enormous productivity gains.
Downtime isn’t just time lost, it’s profit lost.
8. Order Fulfillment Rate (OFR)
What it measures: The percentage of customer orders delivered completely and accurately.
Why it matters: It's a strong indicator of operational consistency and customer trust.
In today’s competitive market, delivering on time and in full is more than a goal, it's a promise to the customer. That’s where Order Fulfillment Rate (OFR) comes in.
This key logistics and customer service KPI tracks how well a company delivers exactly what was ordered, when it was promised.
It reflects a company’s ability to meet demand reliably and maintain customer satisfaction.
Formula
Order Fulfillment Rate (%)=( Fulfilled Orders/Total Orders )×100
Fulfilled Orders: Orders delivered on time, in full, and with no errors
Total Orders: All customer orders placed in the same period
How to Interpret Order Fulfillment Rate
OFR % | Interpretation |
98% – 100% | World class fulfillment |
95% – 97.9% | Good, but may need fine tuning |
< 95% | Risk of customer dissatisfaction |
Order Fulfillment Rate Example
n one month, your company received 1,000 customer orders.Out of those, 940 were delivered correctly and on time.
OFR=( 940 / 1000 )×100=94% ( Good, but may need fine tuning )
Why Order Fulfillment Rate ?
Directly impacts customer satisfaction and retention
Reflects supply chain coordination (inventory, planning, shipping)
Affects brand reputation and repeat business
Helps monitor order accuracy and warehouse efficiency
To Improve OFR
Improve inventory accuracy with real time tracking
Use demand forecasting to prevent stockouts
Streamline order picking and packing processes
Automate order verification systems
Integrate ERP/WMS for end to end visibility
Track OFR by region, product, or customer type to identify gaps
Order Fulfillment Rate is more than just a number, it's your customer experience, measured.If your products don’t arrive complete and on time, your competitors’ will.
Every fulfilled order builds trust. Every missed one chips away at it.
How 77 Teknik Tracks Manufacturing KPIs for Excellence
KPI | 77 Teknik Approach |
OEE | Monitored daily with root cause tracking |
On-Time Delivery | Real time logistics dashboards |
Scrap Rate | Tracked by part number, machine, and shift |
Capacity Utilization | Forecasting tools for proactive planning |
Cycle Time | Analyzed per product family and revision |
First Pass Yield | Quality checkpoints at every critical process |
Downtime | Automated alerts and incident logging |
Why KPIs Matter More Than Ever
In today’s fast moving industrial landscape, monitoring the right KPIs helps manufacturers:
Reduce costs
Improve product quality
Minimize lead times
Respond faster to demand shifts
Enhance customer satisfaction
At 77 Teknik, we use data to drive every improvement initiative. Because in manufacturing, what gets measured, gets improved.
Need help implementing KPI driven manufacturing processes?
Contact 77 Teknik to learn how we turn real time metrics into long term success for global clients.
