Manufacturing Process Automation refers to the systematic automation of production processes beyond individual machines. It is not limited to PLCs or robots, but focuses on the end-to-end process flow across the shopfloor.
Key questions Manufacturing Process Automation addresses:
Which orders run on which line, and when?
Which work plans, programs, and inspections are loaded automatically?
Which decisions (OK/NOK, rework, blocking) are triggered directly by data?
Core idea:
Recurring, rule-based tasks are no longer handled manually. Instead, a central system automatically triggers, controls, and documents processes—ideally in real time and across plants.
Manufacturing Process Automation targets three main levers:
Fewer manual bookings, less Excel, no paper-based coordination. Order distribution, status changes, inspections, and feedback run automatically based on defined rules.
Production processes are modeled as workflows:
Order release → machine setup → operator execution → quality checks → automatic feedback to ERP/MES.
No media breaks. No duplicate data entry.
Fewer operating errors, fewer missed inspections, fewer downtime events due to missing information. Decisions are based on real-time KPIs such as OEE, FPY, scrap rate, and lead time.
Typical components include:
Data from PLCs, CNC machines, robots, test benches, and sensors (via OPC UA, fieldbus, IoT gateways).
Only what is digitally captured can be automated.
“If X happens, do Y.”
Order starts, threshold violations, disruptions, or inspection results automatically trigger actions such as stops, blocks, escalations, or rebooking.
Workflows actively involve operators through Digital Work Instructions, checklists, OK/NOK decisions, photos, and digital signatures—directly linked to orders and parts.
All events are stored with timestamps, machines, orders, materials, and operators. This enables transparent identification of bottlenecks, waste, and optimization potential.
A Cloud MES is the natural backbone of Manufacturing Process Automation:
It manages orders, BOMs, variants, and routing plans
It provides live data from machines, sensors, and inspection systems
It defines workflows, rules, and roles for operators, supervisors, quality, and maintenance
Cloud MES platforms like SYMESTIC connect these layers:
Automated order control: release, prioritization, and assignment to machines and lines
Event- and KPI-driven workflows: disruptions, OEE losses, or quality deviations trigger defined actions
Integration with ERP, maintenance, and quality systems to avoid duplicate bookings and inconsistent statuses
This turns Manufacturing Process Automation into a platform capability, not a local isolated solution—scalable, maintainable, and transparent across plants.
Practical scenarios where Cloud MES significantly increases automation levels:
Orders are automatically assigned to machines or lines based on due dates, setup families, and availability.
MES triggers the correct program or recipe, checks material and tool availability, and blocks start if conditions are not met.
Inspection plans are loaded automatically. Deviations trigger blocking, rework routing, or additional inspections—without relying on manual intervention.
NOK decisions automatically create rework orders or scrap bookings, including ERP feedback and full traceability.
Counters, runtimes, process signals, or error patterns automatically trigger maintenance orders and escalations.
These are Manufacturing Process Automation in practice:
rules instead of intuition, events instead of paper, workflows instead of ad-hoc communication.
For mid-sized manufacturers, a pragmatic approach works best:
Select one line or process with high manual effort and frequent issues
Automate 3–5 clearly defined rule-based workflows (e.g. order release, NOK parts, disruption handling)
Measure impact: errors, downtime, lead time, OEE
Roll out proven templates to additional lines or sites
This turns Manufacturing Process Automation with Cloud MES into a continuous improvement lever, not a one-time IT project.