Particle foam moulding can often be unstable and requires manual adjustments to machine settings to control scrap and improve part dimensions. However, these fixes are usually short-lived, the quality issues return and the cycle repeats.

Teams spend too much time chasing root causes without lasting results. The outcome: increased scrap rates, rising costs, and pressure on production schedules.

Wasted material, rework, extra transport, and repeated quality checks all add up, draining resources that could be used for improvement and innovation.

The Analytics application visualises every cycle, tracking key parameters like filling pressure, steaming and cooling conditions, foam pressure as well as utility stability (cooling water, compressed air, steam pressure, and temperature).

By linking these conditions directly to quality outcomes, production teams can see what truly drives the performance.

This data-driven approach replaces guesswork. Engineers can identify root causes faster, understand process instabilities, and apply precise corrections.

With real-time data and remote access, problem-solving becomes quicker and collaboration more effective.

A customer struggled with high scrap rates caused by dimensional instability. Using DDE Technology (Gateway, Connect and Analytics), they combined process and quality data to compare good and bad production runs. This revealed problems with compression ratio, steaming temperature and pressure, and cooling temperature.

Through remote access in the Analytics app, support engineers guided the operator on specific adjustments. This fixed warping, stabilised dimensions, and cut scrap to zero.DDE provided engineers with the data to decide and operators with clear actions.

The outcome: no waste, lower costs, and improved efficiency.

Producing particle foam parts demands a lot of energy - mainly steam from natural gas. Each cycle heats heavy aluminium moulds from 60–70°C to 135–140°C, then cools them down again.

Since the mould is much heavier than the material, most of the steam goes into heating the mould, not the part. Steam often makes up 70–80% of utility costs, making it a key target for savings.

However, reducing steam too much can result in poor fusion, which can weaken part strength and safety - both key performance attributes. Adding too much steam requires longer cooling, so your energy cycle is not in balance and expensive.

Gateway automatically collects data from moulding machines and quality instruments. Connect organises data into an aggregated database designed specifically for an EPP domain. Analytics visualises process parameters and calculates energy consumption per cycle.

This visibility helps engineers to define the optimal process window, where steam use and cooling times can be reduced without compromising product quality.

Over time, this window becomes more precise, allowing incremental efficiency improvements.

When tooling or equipment is upgraded, DDE helps to validate the return on investment by comparing data across different setups using actual production results.

In the laboratory environment, equipped with DDE Technology, the development team used Analytics to run controlled experiments to benchmark process performance across different conditions and different tooling technologies using the same sample cavity.

They tracked utility consumption, carbon footprint, and cycle times, and analysed machine performance at each process step.

This helped them to understand how each change in the process affected output and quality. Based on this, they developed an expert level moulding technique, which allowed them to uncover significant energy savings opportunities without compromising process stability.

As the team put it: "DDE Technology provided us with precise data and analytics capabilities, which was critical to validate sustainable moulding".

Many manufacturers still rely on paper-based data collection. Operators record machine settings, quality checks, and measurements by hand on printed control sheets. Quality data is often retyped into Excel or saved as static PDF reports.

This manual approach makes it hard to track changes, link different data sources, or quickly access historical information. Teams waste time collecting and correcting data instead of using it. As a result, mistakes are repeated, responses are delayed, and opportunities to improve equipment use and reduce costs are missed.

DDE Technology collects data automatically from a wide range of machines and quality systems, regardless of brand, type, or age. It reduces manual work, errors, and duplicated effort by organising information into a structured database with proper security and backups.

The Monitor application helps operators to easily log failure modes and link them directly to machine data. By combining the operator's input with real-time production data, teams get immediate visibility into the root causes of scrap and downtime, allowing faster and better decisions.

Monitor also allows operators to record the wet weight of the part on the spot.

Implementing Monitor saved the customer a significant amount of manual work on collecting data inputs for daily reports. Skilled staff can now focus on process improvement instead of data collection, entry, and re-entry.

In practical terms, customers benefitted from an increase in Overall Equipment Effectiveness (OEE), which translated to less downtimes and additional production cycles per machine. Apart from the annual financial gains per machine operators face less frustration and can react quicker to problems.

To ensure part quality, many manufacturers rely on conservative process settings, such as extended steaming or maintaining equipment readiness.

While this helps ensure proper fusion and surface finish, it also increases energy consumption, prolongs cooling cycles, and leads to heavier parts.

These inefficiencies can go unnoticed in daily operations and gradually raise overall production time and resource use.

In highly automated, robot-driven production lines, all machines are connected to a central database managed by the customer. DDE Technology assures secure reading of real-time data from the machines, organises it, and sends it to the Connect database. This setup gives fast, reliable access to production data (no delays from file transfers) and allows easy comparison of key parameters over time.

Analytics links process data directly to quality measurements, which gives engineers and operators clear visibility into how process settings affect part quality. They can define stable process windows, identify when the process drifts from optimal conditions, and take timely action.

Access to data also allows other applications to manage energy efficiency at factory level. The system supports consistent decision-making based on actual performance, not assumptions.

With everything wired via OPC UA and a well-configured setup, this solution provided fast, reliable access to production data (no delays from file transfers). It allowed an easy comparison between key parameters over time and made it easier to improve the process step by step while maintaining reliability and quality.

Experienced engineers understand the initial process setup and have access to reference values from actual production. DDE Technology aggregates and monitors data, measures results, and enables direct comparison of settings. Now process engineers use DDE applications to benchmark process performance, compare quality outputs, and make data-driven decisions on how to re-calibrate their benchmark processes.

In this case, the analysis of detailed data revealed a potential to improve process performance by balancing the thermo-cycle and shortening cycle times - without compromising the quality.