As digitalization transforms manufacturing, machining factories are placing unprecedented importance on data. Many have already collected, aggregated, and visualized tool-related data through comprehensive reports to support decision-making.

However, when it comes to improving efficiency, optimizing processes, or controlling costs, data reports alone often aren’t enough. Many factories are now at a turning point — from data display to data enablement. 🚀

🔄 01 – The Shift: From Report-Oriented to Asset-Oriented Thinking

Tool procurement, inventory, tool life, and consumption data...
Most factories already have them.
Yet we often hear:

“We’ve got the data, but the analysis doesn’t help us optimize.”
“We record every trial cut, but still have to redo it next time.”
“Reports look great — but don’t lead to action.”

It’s not about having more data — it’s about using it better.
The leap from report to asset is not just about formatting, but about building:

• 🧱 Structured knowledge

• 🔁 Reusability

• 🌐 Transferability

  
  

📉02 – Reports vs. Assets: What’s the Difference?

Reports show how things are; assets help improve how things will be.

💡03 – Four High-Value Data Assets for Tool Management

🧮 1) Workpiece-Driven Parameter Models

From functional tool selection to intelligent matching.
Use workpiece material, geometry, and machining type to recommend optimal tools and parameters — and reduce trial cuts with a reusable “Workpiece–Process–Parameter” model.

📚 2) Reusable Process Libraries

Don’t waste trial cuts — capture and reuse them.
Turn cutting records, strategy choices, and optimization experiences into a sharable process knowledge base.

📈 3) Tool Cost-Effectiveness Models

Beyond purchase price — model value per output.
Evaluate tools by actual lifespan, cycle time, and part quality to optimize selection and total cost.

⏱ 4) Smart Tool Life Strategies

From experience-based replacement to predictive changeovers.
Use wear data and lifetime trends to forecast failures, reduce unplanned downtime, and enhance production stability.

🌟 04 – Why Data Assets Matter

Because they’re:

✅ Reusable — reduce trial & error
✅ Transferable — empower new teams faster
✅ Foundational — essential for intelligent decisions

Most importantly: Data assets are a digital expression of your factory’s know-how.
Every model or structured record contributes to your long-term capability. 💪

🔧 05 – Knowhy’s Approach: Let Data Drive Value

At Knowhy, we go beyond dashboards.
Our tool management projects help customers:

• 📐 Structure raw data

• 🧠 Build knowledge-based models

• 📊 Transfer expertise across teams

We want every piece of tool data to be:

✅ The basis for continuous improvement
✅ A vessel for experience and know-how
✅ A true marker of digital maturity

✅ Conclusion

📊 Reports are helpful.
🧠 Assets are powerful.
🔧 Tool management digitalization isn’t just about visibility — it’s about actionability.

In today’s complex and competitive environment:

Only when data becomes an asset, does it unlock real value. 💼📈