Manufacturing Process Automation with Cloud MES

What is Manufacturing Process Automation?

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.

Objectives: Higher Automation Levels & Stable Processes

Manufacturing Process Automation targets three main levers:

Increase the Level of Automation

Fewer manual bookings, less Excel, no paper-based coordination. Order distribution, status changes, inspections, and feedback run automatically based on defined rules.

Workflow Automation

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.

Improve Quality & OEE

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.

Core Building Blocks of Manufacturing Process Automation

Typical components include:

Machine & Sensor Connectivity

Data from PLCs, CNC machines, robots, test benches, and sensors (via OPC UA, fieldbus, IoT gateways).
Only what is digitally captured can be automated.

Workflow Engine & Rule Framework

“If X happens, do Y.”
Order starts, threshold violations, disruptions, or inspection results automatically trigger actions such as stops, blocks, escalations, or rebooking.

Digital Worker Guidance

Workflows actively involve operators through Digital Work Instructions, checklists, OK/NOK decisions, photos, and digital signatures—directly linked to orders and parts.

Data Platform & Analytics

All events are stored with timestamps, machines, orders, materials, and operators. This enables transparent identification of bottlenecks, waste, and optimization potential.

The Role of Cloud MES in Manufacturing Process Automation

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.

Typical Use Cases for Manufacturing Process Automation

Practical scenarios where Cloud MES significantly increases automation levels:

Automated Order Release & Distribution

Orders are automatically assigned to machines or lines based on due dates, setup families, and availability.

Automated Setup & Program Changes

MES triggers the correct program or recipe, checks material and tool availability, and blocks start if conditions are not met.

Automated Quality Workflows

Inspection plans are loaded automatically. Deviations trigger blocking, rework routing, or additional inspections—without relying on manual intervention.

Rework & Scrap Handling

NOK decisions automatically create rework orders or scrap bookings, including ERP feedback and full traceability.

Event-Based Maintenance

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.

Step-by-Step Implementation Instead of Big Bang

For mid-sized manufacturers, a pragmatic approach works best:

1. Select one line or process with high manual effort and frequent issues

2. Automate 3–5 clearly defined rule-based workflows (e.g. order release, NOK parts, disruption handling)

3. Measure impact: errors, downtime, lead time, OEE

4. 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.