Throughput Time | Optiwise
Learn throughput time in manufacturing, its formula, examples, causes of delay, improvement strategies, and how ERP helps SMEs track production flow.
Throughput Time: Meaning, Formula, and How Manufacturing SMEs Can Reduce It
Throughput time tells a manufacturer how long it takes for work to move through the production system.
It is not only machine time. A job may spend one hour on a machine but wait two days for material, inspection, tool availability, or the next operation. Those waiting periods are part of the real production lead time the customer experiences.
For manufacturing SMEs, throughput time matters because long production flow creates delayed dispatch, higher WIP, blocked cash, poor customer communication, and pressure on supervisors. Reducing throughput time improves delivery and frees capacity without always buying new machines.
This guide explains throughput time, formula, examples, causes of delay, improvement strategies, and how AICAN Optiwise helps SMEs track production flow.
What Is Throughput Time?
Throughput time is the total time taken for a product, job, or order to move through the manufacturing process from start to completion.
It may include:
- queue time
- setup time
- processing time
- inspection time
- movement time
- waiting time
- rework time
The key point is that throughput time includes both active and inactive time.
Throughput Time Formula
A practical formula is:
Throughput time = processing time + inspection time + movement time + waiting time + setup time
Some businesses may include or separate queue time depending on their process. The purpose is to understand total flow time, not only machine time.
Why Throughput Time Matters
Throughput time affects:
- customer delivery
- production planning
- WIP levels
- capacity utilization
- cash flow
- dispatch reliability
- bottleneck visibility
- customer satisfaction
A business with shorter throughput time can respond faster to customer demand.
Example in Manufacturing
A job takes 3 hours of actual processing time. But before completion, it waits 8 hours for material, 4 hours for inspection, 12 hours before the next operation, and 2 hours for movement and setup.
Total throughput time is much higher than processing time.
This shows why improving only machine speed may not solve delivery delays.
Throughput Time vs Cycle Time
Cycle time usually refers to the time taken to complete one unit or cycle of a process.
Throughput time is broader. It covers the total time a job spends moving through the full production flow.
Cycle time helps understand operation speed. Throughput time helps understand overall flow.
What Increases Throughput Time?
Material Shortage
Jobs wait because raw material or components are unavailable.
Poor Scheduling
Work waits between operations due to unclear priority.
Bottleneck Machines
One overloaded process delays the whole flow.
Inspection Delay
Output waits for quality approval.
Rework
Defective output returns to earlier stages.
Excess WIP
Too many jobs in process increase waiting time.
Manual Follow-Up
Supervisors spend time locating job status.
How to Reduce Throughput Time
Map the Process
List each step from order release to completion.
Measure Waiting Time
Do not measure only processing time. Waiting often hides the biggest loss.
Remove Bottlenecks
Identify the process where work piles up.
Improve Material Readiness
Do not release jobs without required material.
Reduce Rework
Quality improvement reduces repeat processing.
Improve Scheduling
Prioritize based on delivery date, material readiness, and bottleneck capacity.
Track WIP
Know where each job is stuck.
How ERP Helps Track Throughput Time
ERP helps by connecting work orders, material issue, operation status, quality, and dispatch.
A connected ERP can show:
- work order release date
- operation start and completion
- WIP status
- pending inspection
- material shortage
- rework quantity
- bottleneck stages
- planned vs actual production
- dispatch readiness
Optiwise by AICAN helps SMEs improve throughput visibility by connecting production, inventory, quality, and reporting.
KPIs to Track
Track:
- average throughput time
- order lead time
- queue time by operation
- WIP ageing
- bottleneck waiting time
- rework time
- planned vs actual completion
- dispatch delay due to production
Founder’s Note
At AICAN, we often see factories where machines are busy but orders are still late. The problem is not always machine speed. It is the waiting between steps.
AICAN Optiwise helps manufacturers make that waiting visible so production flow can improve with practical decisions.
FAQs
What is throughput time?
Throughput time is the total time a job takes to move through the manufacturing process from start to completion.
What is included in throughput time?
It may include processing, setup, inspection, movement, waiting, queue, and rework time.
How is throughput time different from cycle time?
Cycle time usually measures operation speed. Throughput time measures the full flow time across the process.
How can SMEs reduce throughput time?
They can reduce waiting, improve scheduling, remove bottlenecks, improve material readiness, and reduce rework.
How does Optiwise help with throughput time?
Optiwise by AICAN connects work orders, WIP, inventory, quality, and reports so SMEs can see where production is delayed.
Related Posts
Kanban System | Optiwise
Learn how a Kanban system works in manufacturing, where it helps, where it fails, and how Optiwise connects Kanban signals with inventory, purchase, and production planning.
Erp In Operations Management | Optiwise
Learn how ERP improves operations management by connecting planning, inventory, purchase, production, quality, dispatch, finance, and reporting.
ERP for FMCG Companies in India
A practical guide to ERP for FMCG companies in India, covering distributor orders, batch tracking, expiry, inventory, production, schemes, costing, and reporting.
What's the Difference Between Odoo, Acumatica, and Dynamics 365 for Small Businesses?
Compare Odoo, Acumatica, and Microsoft Dynamics 365 for small businesses across flexibility, cost, implementation, manufacturing fit, ecosystem, and support considerations.

