Скачать или смотреть Smart Employee Assignment in HxGN EAM — Real-Time Scoring & Automatic Recommendation

In this video, I show how to build a fast and intelligent Employee Recommendation System inside HxGN EAM, using a multi-dimensional technical scoring model.

We evaluate each employee across seven scoring categories, designed specifically for reactive maintenance planning:

• Backlog – How many activities from yesterday are still open
• Booked Yesterday – Logged hours and proof of active involvement
• EVT Status – Whether the current job is free, open, waiting for materials, or actively in progress
• Today Location – How close the person already is to the equipment, line, or plant
• Tomorrow Load – Whether the person is heavily scheduled for the next day
• Object Match – Open work on the same asset, line, or area
• Activity Today – Whether the employee has already started tasks today

Each category is visualized using a LED-style scoring row, moving from red to green, making it instantly clear who is the best candidate for the new task.

In this video you’ll also see how to:

✔ Visualize the score inside an ExtJS popup
✔ Automatically identify the optimal employee
✔ Insert the selected employee directly into udfchar09 (Assigned To)
✔ Enhance planning efficiency with data-driven recommendations

This approach is ideal for:

• Maintenance and asset management teams
• Dispatchers and planners
• Production sites with many parallel activities
• Organizations looking to reduce walking time and improve reactivity
• Anyone wanting more transparency and smarter decision-making in EAM

If you enjoy this type of content around HxGN EAM, automation, AI in maintenance, or practical technical solutions, feel free to like, subscribe, or leave a comment.
I regularly publish new videos about EAM optimization, AI tools, and workflow automation.

📌 Share this video with colleagues who work with HxGN EAM or maintenance scheduling.