1. MES Basics

Definition, core functions, and applications of Manufacturing Execution Systems.

2. MES Software

Transparency and efficiency in manufacturing through modern MES software solutions.

3. Cloud MES

The pinnacle: How cloud-native MES sustainably transforms your production.

Global Scalability

Effortlessly adapt your manufacturing to new markets.

Fast Results

Implement in weeks, not months.

Intelligent Processes

Leverage AI for precise analysis and optimization.

• From CAPEX to OPEX: Pay only for what you use, reducing initial costs.
• No IT Infrastructure Costs: Eliminate expenses for servers, databases, and network components.
• Up to 90% CAPEX Savings: Proven cost efficiency compared to on-premises MES in reference cases.
• Predictable Costs: Transparent SaaS pricing with fixed subscription fees.
• Automatic Updates: No costs for major system upgrades.

• Days, Not Months: Deploy in days with improvements in four weeks, compared to 12-18 months for traditional MES.
• Instant Access: Available immediately upon contract signing.
• Phased Rollout: Start with pilot projects and scale to enterprise-wide use.
• Streamlined Onboarding: Structured processes for quick wins.
• Fast ROI: Amortization in under 3 months, versus 18-36 months for on-premises MES.

• Effortless Expansion: Integrate new production lines, sites, or functions with ease.
• Global Deployment: Implement seamlessly across international locations.
• Elastic Resources: Automatically adjust to fluctuating demands.
• Modular Design: Customize functionalities to your needs.
• Pay-as-you-grow: Costs scale with your business needs.

• Robust Security Architecture: Comprehensive protection aligned with industry standards.
• Continuous Updates: Automatic security patches and updates.
• Certified Data Centers: Compliance with international security standards.
• Comprehensive Encryption: Secure sensitive manufacturing data.
• Redundant Systems: Ensure high availability with multiple safeguards.

• Standardized APIs: Easily connect to ERP, PLM, and other enterprise systems.
• Flexible Machine Integration: Connect diverse machines and equipment.
• Edge Computing: Process data intelligently at the source.
• IoT Integration: Seamlessly incorporate sensors and smart devices.
• Open Standards: Ensure future-proof communication with established protocols.

• Live Dashboards: View all production KPIs at a glance.
• Issue Management: Immediate alerts for problems.
• OEE Tracking: Continuous monitoring of Overall Equipment Effectiveness.
• Mobile Access: Access production data from anywhere.
• Custom Visualizations: Tailored dashboards for different user groups.

• Integrated Quality Checks: Embedded inspections within production.
• Statistical Process Control (SPC): Early detection of quality deviations.
• Root Cause Analysis: Systematic identification of quality issues.
• Traceability: Complete documentation of quality data.
• Automatic Alerts: Instant notifications for threshold breaches.

• Capacity Planning: Optimize resource utilization.
• Sequence Optimization: Minimize setup times and maximize throughput.
• Real-Time Adjustments: Dynamic rescheduling for disruptions or priority changes.
• What-If Scenarios: Simulate planning alternatives.
• AI-Driven Optimization: Leverage learning algorithms for continuous improvement.

• Material Tracking: Transparency over material flow and inventory.
• Tool Management: Optimize tool provisioning and maintenance.
• Workforce Planning: Efficiently assign staff based on skills.
• Energy Monitoring: Track and optimize energy consumption.
• Maintenance Management: Predictive maintenance to minimize downtime.

• Advanced Analytics: In-depth analysis of production data.
• Predictive Analytics: Forecast quality issues and machine failures.
• Custom Reports: Tailored reports for various stakeholders.
• Trend Analysis: Identify and evaluate long-term trends.
• Benchmarking: Compare performance across lines, shifts, or sites.

• End-to-End Digitization: Seamless integration of all production processes.
• Horizontal and Vertical Integration: Connect systems from machines to management.
• Data-Driven Decisions: Make informed choices with real-time data.
• IoT Integration: Easily incorporate sensors and smart devices.
• Transparent Supply Chains: Enhance coordination with suppliers and customers.

• Human-Centric Production: Empower workers rather than replace them.
• Sustainable Manufacturing: Optimize resource use and minimize waste.
• Custom Mass Production: Flexibility for tailored products.
• Resilience: Adapt to changing market conditions.
• Collaborative Ecosystems: Enhance cooperation in value networks.

• OEE Improvement: 10-25% increase in Overall Equipment Effectiveness.
• Scrap Reduction: 30-60% less waste.
• Labor Productivity: 10-15% productivity boost.
• Inventory Reduction: 15-30% lower stock levels.
• Energy Savings: 5-15% reduction in energy consumption.
• Setup Time Reduction: 20-45% faster changeovers.
• Lead Time Reduction: 20-40% shorter lead times.
• On-Time Delivery: 15-30% improvement in delivery reliability.

• Conduct a detailed requirements analysis.
• Define clear objectives and measurable success criteria.
• Assemble a cross-functional project team.
• Develop a change management strategy.

• Start with a single production line or area.
• Focus on key performance indicators.
• Highlight and communicate early successes.
• Gather and implement user feedback.

• Roll out the successful pilot to other areas.
• Activate additional functionalities incrementally.
• Ensure ongoing user training.
• Regularly review results.

• Optimize processes with data-driven insights.
• Conduct regular reviews and adjustments.
• Foster a culture of continuous improvement.
• Leverage your MES partner’s expertise.

• Challenge: Concerns about the security of sensitive manufacturing data in the cloud.
• Solution: Conduct a thorough analysis of the provider’s security architecture, encryption technologies, and compliance certifications.

• Challenge: Integrating legacy machines without modern communication interfaces.
• Solution: Use edge gateways and IoT sensors for retrofitting, and DI solutions (Digital Input) for basic status capture.

• Challenge: Resistance to change and new technologies among employees.
• Solution: Engage employees early, provide comprehensive training, and demonstrate tangible benefits for daily work.

• Challenge: Fear of production downtime due to internet disruptions.
• Solution: Implement redundant internet connections, edge computing for critical functions, and offline capabilities.

• Challenge: Seamless integration with ERP, PLM, and other enterprise systems.
• Solution: Use standardized APIs, middleware solutions, and phased integration approaches.

• Predict machine failures before they occur.
• Optimize maintenance schedules.
• Reduce unplanned downtime.

• Automatically identify process deviations.
• Early detection of quality issues.
• Self-learning systems for continuous improvement.

• AI-driven optimization of production sequences.
• Dynamic adjustments for disruptions.
• Self-learning algorithms for continuous improvement.

• Automated optical inspection.
• Detection of defects and quality issues.
• Support for workers in complex assembly processes.