New software product
HMR EPI
Extrusion Process Intelligence.
HMR EPI turns production data, process expertise and historical production cases into explainable recommendations for PVC sheet extrusion.
The platform combines PAS data, SCADA and quality information, expert rules, Lean Six Sigma DMAIC and industrial AI into a local decision-support and knowledge system.
6-12
Months typical ROI
Example range depending on line, data quality and project scope.
€1.2M
Annual improvement potential
Illustrative potential per line based on the executive overview.
-22%
Scrap reduction
Target direction: lower startup, process and quality losses.
+15%
Productivity improvement
Through more stable processes, better windows and faster reaction.
Hybrid intelligence
One system for four
process areas.
HMR EPI covers the value chain from formulation and mixing to extrusion and quality. Causes, parameters and effects are analyzed in context instead of isolation.
Formulation Intelligence
Analysis of PVC resin, additives, suppliers, batch behavior, material properties and formulation optimization.
Mixing & Blending Intelligence
Evaluation of addition sequence, hot and cold mixing, mixing energy, cooling, dryblend consistency and intermediate storage.
Extrusion Process Intelligence
Correlation of torque, pressure, temperature, vacuum, moisture, density, wall thickness, process stability and OEE.
Quality & Market Intelligence
Connection of inline QC, laboratory values, SPC, complaints, market feedback and long-term product performance.
Explainable recommendations
From raw signals to
technical decisions.
The platform does not generate recommendations from a black-box model alone. Findings are validated with historical cases, expert correlations, engineering rules and DMAIC knowledge.
01
Capture data
Production, quality, recipe, alarm, laboratory and operator data is imported from available systems.
02
Create context
Process values are linked to product, recipe, line, shift, operator, time window and quality result.
03
Detect patterns
Correlations, trends, drift, anomalies, best-practice windows and recurring loss drivers become visible.
04
Validate technically
Engineering rules and expert knowledge constrain recommendations to plausible and safe process windows.
05
Recommend actions
HMR EPI delivers concrete next steps for operators, process engineering, quality or management.
06
Retain knowledge
Successful actions, operator feedback and DMAIC results flow back into the knowledge base.
Architecture & security
Local, controlled
and production-oriented.
HMR EPI is designed for industrial environments where process know-how and production data are sensitive. The platform can run locally, isolated or with controlled one-way data flow.
BOOM SCADA or existing systems
Data acquisition, live monitoring, alarms, SPC and dashboards can run through BOOM SCADA or existing historian and SCADA systems.
Controlled data transfer
Production data can be transferred to HMR EPI through export, SSD/USB or a customer-controlled synchronization process.
Local AI system
Analysis, pattern recognition, correlation logic and optimization recommendations run without mandatory cloud dependency in customer-controlled infrastructure.
Business impact
Less loss.
More process knowledge.
Better quality
More stable product quality through SPC, trend analysis, quality prediction and root-cause evaluation.
Higher productivity
More output, less downtime and better utilization of existing production lines.
Lower costs
Less scrap, lower energy consumption and better material efficiency.
Faster time to market
Shorter startup times, fewer trials and faster stabilization of new processes.
Knowledge retention
Practical know-how from shifts, lines, projects and expert sessions becomes structured and reusable.
More sustainable production
Lower material waste, better energy efficiency and more stable processes over time.
Industrial AI from real practice
Turn process data into
decision knowledge.
HMR EPI is built for producers who want to not only monitor PVC extrusion, but systematically understand, optimize and preserve it as reusable know-how.