SYSTEM ACTIVE · ONLINE

Digital twin
of your factory:
from monitoring to forecast

Procesia Industrial Cloud is a cloud platform that creates a digital twin of your shop floor. It captures every event, detects anomalies, and predicts downtime risks before they occur. Connects to your existing MES (SIMATIC IT / Opcenter) without changes on the factory side.

MSSQL FastAPI PostgreSQL TimescaleDB Grafana 13 Docker

Everything you need for a transparent factory

Connect to your existing MES with no changes, web dashboards, downtime log with acknowledgement, Grafana analytics, and ML-based downtime forecasting once labeled history is collected.

01
📊

Equipment monitoring

Shop floor diagram with real-time status indicators. Click any element to see details and events.

02

Downtime log

CRUD log with acknowledgement. Operator selects shift, reason, comment. XLSX export by period.

03
📈

Grafana analytics

Ready-made dashboards: downtime dynamics by period, top reasons, OEE and line activity, event stream.

04
🏭

Multi-plant architecture

Each plant has its own agent and access token. Data isolation — owners see only their own plants and shops.

05
📱

QR codes for tablets

QR code on a shop floor tablet → instant access, no login required. Mobile-friendly.

06
🔄

Auto-update for agents

Centralized version management. Agents auto-update; per-plant version pinning.

Live preview of the running system

These previews load directly from the production server — what you see here is exactly what your operator sees.

shric.ru/demo
LIVE
◈ Main dashboard — demo

Shop diagram · Status indicators · Event stream · Activity · Sparkline

shric.ru/grafana/public-dashboards/
LIVE
◈ Grafana — analytics

OEE · Top rules · Event dynamics · Filters by plant and shop

Delivered automation and optimization projects

MES integration, reconfiguration of existing production setups, integrations with weighing and laboratory systems. Below are examples of completed projects.

01
🏭

Connecting a new plant to MES

Integrated SIMATIC IT with cloud monitoring, configured agent, migrated equipment and operator registries. 4 weeks from start to first production dashboard.

SIMATIC IT · MSSQL → CLOUD
02

Plant configuration optimization

Audit of existing recipes, reconfiguration of production routes and nodes, reduced batch transition times. Before/after measurement on real data via the built dashboard.

OPTIMIZATION · BUSINESS PROCESS
03
🔄

MES reconfiguration for production scaling

Added a new line to a live MES, configured registries, integrated new sensors and operators. Zero downtime for the running shop, phased migration.

SCALING · ZERO-DOWNTIME

From sensor to dashboard in seconds

A Windows agent at the factory pulls data from MSSQL and pushes it to the cloud over an encrypted channel. No changes to your MES, no VPN, no inbound open ports.

🏭
FACTORY
MSSQL / MES
SQL Server Express
SIMATIC IT / Opcenter
data
AGENT
Windows EXE
Datetime polling
HTTPS · JWT · API-key
https
CLOUD
FastAPI + Postgres
TimescaleDB hyper
Docker Compose
📊
DASHBOARDS
Web UI + Grafana
QR access · public
dashboards · filters
labels
🤖
AI SERVICE
ml-worker
scikit-learn
Downtime forecast
predict
📋
OPERATOR
Shop floor tablet
QR · acknowledgement
downtime history

7 steps from audit to forecast

A typical implementation cycle is about 4–6 weeks to launch the base system. AI forecasting is added as a separate stage as labeled history is collected.

1

Audit

MES analysis, SQL Server version, network availability, list of tables to poll.

2

Agent

Install the Windows agent, configure table polling, NSSM service, auto-update.

3

Cloud

Deploy API + DB + Grafana on a VPS or your cloud. Docker Compose, SSL.

4

Dashboards

Configure shop floor diagram, QR tokens for tablets, registries of operators and reasons.

5

Pilot

Testing with real data, training operators to acknowledge downtime.

6

Scaling

Connect additional plants and shops, data isolation, role-based access.

7

AI analytics

Launch the predictive model once enough labeled downtime history is collected.

LAUNCH THRESHOLD 50–100 labeled downtime events  2–3 months of shop operation  predictive model launch

MES ↔ 1C — production and accounting work as one

In addition to cloud monitoring, our team builds MES ↔ 1C integrations and customizations within AutomationX projects, tailored to each production site.

📋
Challenge
  • Manual data transfer between MES and 1C
  • Input errors, delays in accounting
  • Production and finance out of sync
  • Decisions made too late
Solution
  • Direct MES ↔ 1C exchange, no operator needed
  • Automatic transfer of output and consumption
  • Reconciliation of item registries
  • Exchange log and error monitoring
🔧
Technology
  • SIMATIC IT (axpdb) as data source
  • 1C UPP / ERP as receiver
  • XML / web service exchange bus
  • Scheduled jobs and monitoring
🎯
Result
  • Human error eliminated
  • Faster response time
  • Decision-making speed increased
  • Production and accounting work as one
Customizations in AutomationX projects
  • SCADA/MES tuning for site-specific needs
  • New operator screens, reports, and logs
  • Customization of alarm logic
  • Integrations with weighing systems, ERP, lab
Maintenance and support
  • Incident resolution and bottleneck removal
  • Regular performance audits
  • Component updates and migrations
  • Operator and engineer training

Ready to discuss implementation at your factory

The first 30 days of the pilot are free. Reach out any way that works for you — we’ll discuss your MES infrastructure and put together an implementation plan.