ITP, InTech Partner

In industrial environments, safety challenges often arise in moments.
A person entering a restricted area, moving too close to hazardous equipment, or accessing a high-risk zone can create a serious safety concern before it is noticed through traditional monitoring methods.

For this project, we implemented a real-time video monitoring solution to improve visibility of personnel movement across hazardous industrial zones.
The objective was simple: help safety teams understand what is happening inside critical areas, identify risks faster, and have better information available for incident review.

The solution enabled:
✅ Real-time monitoring of personnel entering restricted zones
✅ Flexible configuration of hazardous areas based on site requirements
✅ Individual person tracking within monitored spaces
✅ Complete movement path analysis inside defined zones
✅ Recorded video review for incident investigation and safety audits

Project Outcomes:
📍 Detection accuracy: 95%+
📍 Zone management: Real-time adjustment of monitored areas
📍 Tracking capability: Individual movement monitoring
📍 Analysis: Complete movement history for review and investigation

By improving visibility across hazardous areas, the system helps safety teams better understand workplace activity and support faster decision-making when risks occur.

Have a challenging area where continuous monitoring is difficult?
Share your existing camera setup with us, and we can evaluate the possibilities.

In our Computer Vision project, the team implemented a solution to automate PPE compliance monitoring in an industrial environment.

The objective was practical: reduce dependence on manual observation and provide continuous visibility into whether required protective equipment is being used.

The workflow is straightforward:

Person detected → PPE checked → violation registered → alert sent → incident available for later review

The system recognizes 4 categories of PPE:

➡️ Helmet
➡️ Safety glasses
➡️ Respiratory protection
➡️ Firesuits

When a violation is identified, the event can be sent to the appropriate systems for further action. Historical video and analytics can also be used to review each individual case.

Detection accuracy: 95%+

For HSE teams, the value is not simply detecting a person on camera. It is automatically checking whether the required protective equipment is actually present and creating a record when it is not.

If PPE compliance is still monitored mainly through manual checks, we can assess one camera view from a work zone and evaluate whether this approach is suitable for the environment.

In one of our Computer Vision projects, our team implemented a solution to automate slag pot processing control in an industrial environment.
The goal was to improve process visibility, reduce manual monitoring efforts, and provide better tracking of slag pot conditions during each locomotive pass.

The workflow is straightforward:
Slag pot detected → Pot condition classified → Spraying process monitored → Violation recorded

The system automatically detects and tracks slag pots, identifies their condition (empty / with slag), monitors spraying activities, and captures process deviations for further review.

When a violation is detected, the system records the event with relevant information to help teams analyze and improve the process.

Key capabilities include:
• Slag pot detection and tracking
• Pot state classification
• Spraying zone and process monitoring
• Automated violation detection

Detection accuracy: 98% ✔️
For the operations team, the solution provides better visibility into slag pot processing and helps review important process conditions during each locomotive pass.

If you are looking to improve monitoring and control within your industrial processes, InTech Partner | ITP team can help explore how Computer Vision can support your operations.

A successful S/4HANA migration in pharma isn’t just about moving to a new system.

In a regulated environment, the decisions made before and during the migration can matter just as much as the technology itself.

From our experience working on pharmaceutical transformation projects, five lessons consistently stand out:

→ Design around regulated processes, not just SAP modules
→ Define validation scope early
→ Give data migration clear ownership
→ Test exceptions, not only the happy path
→ Treat user adoption as part of maintaining control

Compliance shouldn’t be something you try to prove at the end. It should influence how the migration is designed from the start.

Swipe through the carousel for the five practical lessons ➡️

Tell us the compliance risk you’re most concerned about. Our pharma team would be happy to discuss it.

GxP ITP

Your best engineers shouldn’t spend hours rebuilding routing cards.
Yet that’s still part of the daily workload for many manufacturing teams — reviewing drawings, checking old projects, repeating calculations, and turning the same engineering knowledge into new documentation.

AI can take some of that repetitive work off the team’s plate.
Technical drawings and manufacturing parameters can be used to create structured draft process plans and routing cards, with engineers reviewing and approving the results.

💬 Comment “AI Workflow” if you’d like to see how this workflow can work in practice.

Your SAP project success depends on the questions you ask first.

From KPIs and production to procurement, logistics, data, and automation — the right discovery approach creates the foundation for transformation.

💬 Comment “Checklist” to get the complete checklist.

How much delivery cost is already locked in before the first truck leaves?
Route-planning inefficiency often starts long before dispatch.
Manual sequencing.

Incomplete addresses.
Missed time windows.
Unused vehicle capacity.
Slow replanning when something changes.

None of these problems looks dramatic on its own. But repeated across every planning cycle, they can quietly add kilometres, planner hours and avoidable cost.

The first step is not necessarily replacing your planning process.
It is understanding where the leakage is happening today.

Swipe ➡️ for five areas worth checking with your dispatch team.
Use our route-planning baseline checklist to review your current process and identify where optimisation could create value.

The same deliveries. Fewer kilometres.

Up to 10% lower delivery mileage, with a full order set planned in under five minutes.

The opportunity isn’t always about adding more vehicles or changing the fleet. Sometimes, it starts with building better routes.

Our logistics optimisation approach works with the data companies already have. Orders, vehicles and operational constraints can come directly from existing ERP exports.

From there, the process validates the data, geocodes delivery addresses and generates optimised, editable routes.

And importantly, the planner stays in control.
AI handles the heavy calculation. The logistics team keeps the operational knowledge and final decision-making.

In one of our business cases, this approach delivered 5–10% lower mileage on historical orders while reducing route planning from hours to minutes.

Want to see where the hidden cost may be in your current route planning process?
Test your historical orders and measure the opportunity against your own baseline.

🌐 Read the full article:
https://lnkd.in/dj2FXM6k