Optimization Potentials of Manufacturing Plants

In industrial manufacturing, numerous classic optimization potentials can be identified that companies can specifically leverage to increase their efficiency, quality, and profitability. The most important areas of focus are process optimization, resource management, maintenance, technology integration, as well as quality and safety improvement.

A central field of optimization is process optimization. The main objective here is to improve the capacity utilization of all resources and to avoid bottlenecks or overloads. By reducing idle times and precisely planning machine assignments, throughput times can be significantly shortened. Another lever is the minimization of setup times. In addition, standardizing processes ensures higher reproducibility and lower error rates.

There are also significant optimization opportunities in resource and cost management. Reducing material waste and offcuts contributes to increased efficiency, as does lowering energy consumption through optimal machine parameter settings. By deliberately selecting cost-effective machines and optimizing inventory management, manufacturing costs and capital commitment can be further reduced.

Maintenance is another key factor for the performance of manufacturing plants. Preventive maintenance and regular inspections extend the service life of equipment and prevent unplanned downtime. Modern approaches such as predictive maintenance, in which sensor data and artificial intelligence are used to predict failures, can drastically reduce unplanned downtime. Involving employees as part of Total Productive Maintenance (TPM) also helps maximize machine availability.

Last but not least, quality and safety aspects are important fields of optimization. Early detection of defects through real-time data analysis helps identify and correct quality deviations during production. The use of augmented reality (AR) in the form of industrial smart glasses supports employees with digital instructions, reduces operating errors, and increases occupational safety.

Technological innovations offer a wide range of optimization opportunities. The use of Manufacturing Execution Systems (MES) enables efficient production control based on real-time data. Automated guided vehicles reduce internal logistics costs. Digital machine terminals (which can also be retrofitted) create paperless workplaces and make daily work on the shop floor easier for operators through maximum transparency and centralized information.

By consistently leveraging these optimization potentials, companies can sustainably strengthen their competitiveness and achieve a significant increase in efficiency and profitability. It is crucial to always consider these potentials holistically. Individual measures often have effects across departmental boundaries and can influence each other—for example, pure cost optimization can have negative effects on throughput times or product quality. Only through comprehensive, systematic analysis and coordination of optimization approaches can sustainable improvements be achieved and goal conflicts avoided.

MES as a Central Tool for Holistic Optimization Strategies

A Manufacturing Execution System (MES) forms the core of an integrated optimization strategy for manufacturing plants. The tetys-MES connects the operational control of production with higher-level planning systems (ERP) and the machine level (SCADA). This bridging function makes it possible to systematically and data-driven implement all the previously mentioned optimization potentials—from process control to quality assurance.

The tetysMES continuously records machine data such as performance indicators (OEE), causes of downtime, or consumption figures. This real-time transparency allows bottlenecks to be identified immediately and corrective actions to be taken. For example, machine parameters can be adjusted to fluctuations in material quality to reduce scrap.

An MES seamlessly integrates key processes:

• Order management: Automated machine assignment shortens throughput times through optimized sequence planning
• Resource management: Energy and material consumption are documented per order to identify cost drivers
• Predictive maintenance: The analysis of process and experience data predicts maintenance needs before failures occur
• Quality control: Statistical process monitoring provides early warnings of deviations

Our products offer modular, expandable functions by design, which can be introduced step by step. For example, machine data acquisition can be implemented first before digitalizing in-process quality control. This approach minimizes risks and ensures rapid ROI through individual optimizations.

We are happy to advise you individually regarding your digital optimization strategy for your manufacturing plants—contact us to arrange a detailed appointment.