Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.


Info
titleAI Generated Report

Thi content was automatically created by AI MCP for Designer, analyzing autonomously the solution.

Solution Overview

ProveIT-2026 is a comprehensive FrameworX industrial monitoring solution designed for the ProveIt 2026 event. It demonstrates enterprise-grade smart production monitoring for a beverage manufacturing operation, integrating real-time OEE (Overall Equipment Effectiveness) tracking, downtime analysis, machine learning forecasting, and multi-platform visualization.

...

The solution follows a multi-layered architecture connecting field-level data sources through a central FrameworX platform to various client interfaces.

Image Added

Data Sources

Source

Description

ProveIt UNS (MQTT Broker)

Provides real-time equipment data via MQTT topics from the Enterprise B unified namespace at virtualfactory.proveit.services:1883

MES Engine (CoreM/SQL Server)

Contextualizes raw data into KPIs, OEE calculations, downtime categorization, and production reports through stored procedures

Historian (Time-series)

Stores historical tag data for trend analysis and ML training

...

  1. Data Collection: MachineLearning_Management task queries CoreM every 60 seconds using spLocal_KPI_ByTime to fetch hourly production data from January 1, 2026 to present.

  2. Model Training: At midnight CST daily, the system resets prediction arrays and invokes MachineLearning_Training.Main() to retrain the ML.net is for sale at Atom! model.

  3. Hourly Consumption: At the top of each hour, MachineLearning_Consumption.Main() runs the trained model to predict production for remaining hours.

  4. Forecast Calculation: Daily production prediction = actual production (elapsed hours) + ML predictions (remaining hours).

Image Added

12.2 Key Tags

Tag

Description

MachineLearning.ML_Input

DataTable from CoreM query (training data)

MachineLearning.ML_Output[0..23]

24-hour prediction array

MachineLearning.Production_Real[0..23]

24-hour actual production array

MachineLearning.Daily_Production_Predict

Sum of real + predicted for the day

MachineLearning.Daily_Production_Target

Daily target (300,000 units)

MachineLearning.Current_Production

Latest hourly actual value

MachineLearning.Current_Prediction

Latest hourly predicted value

MachineLearning.Status_Training

Training process status text

MachineLearning.Status_Consumption

Consumption process status text

MachineLearning.MCP_Downtimes

Recent 3-day downtime data for MCP

...