Problems we solve at each level
What holds operations back
- Hidden capacity wasteWithout run hour tracking, facilities lack visibility into which machines are productive versus idle, leading to over-investment in equipment while existing assets sit underutilized.
- Estimate-based schedulingProduction planning relies on assumptions rather than verified runtime data, causing missed delivery commitments, excess overtime, and poor quoting accuracy.
- Unquantified downtimeThe financial impact of downtime remains invisible, making maintenance planning reactive rather than strategic and capital equipment decisions unsupported by utilization data.
How we solve it
- Machine-level run hour trackingReal-time visibility into which machines are producing, idle, or down across all injection molding equipment. Accurate capacity utilization reporting enables data-driven scheduling and capital allocation decisions.
- Utilization dashboards by shift & lineHistorical and real-time metrics identify underutilized capacity, support accurate production forecasting, and enable better workforce planning across shifts and production lines.
- Downtime analysis & categorizationTrack planned versus unplanned downtime with frequency and duration visibility. Quantify the financial impact of availability improvements and prioritize maintenance initiatives effectively.
What holds operations back
- Melt temperature instabilityInconsistent barrel and nozzle temperatures create dimensional variation, surface defects, and higher scrap rates from out-of-spec parts that fail quality inspection.
- Injection pressure variationPressure inconsistency causes short shots, flash, and fill pattern instability, resulting in material waste and rejected parts that require line adjustments.
- Cycle time unpredictabilityVariable cycle times reduce throughput forecasting accuracy, cause overtime costs, and create missed delivery commitments that damage customer relationships.
- Material waste visibility gapsPurge waste, startup scrap, and runner system inefficiencies compound material costs without clear tracking or visibility into optimization opportunities.
How we solve it
- Melt temperature monitoringTrack barrel temperature, nozzle temperature, and melt consistency in real-time. Early detection of temperature drift enables corrective action before dimensional quality degrades.
- Injection pressure trackingMonitor injection pressure profiles and holding pressure stability across cycles. Pressure consistency prevents short shots, flash, and fill pattern variation.
- Cycle time analysisReal-time cycle time monitoring identifies process inefficiencies and throughput bottlenecks. Optimize cooling times and process parameters for maximum efficiency.
- Material efficiency trackingMonitor resin consumption relative to good parts produced, including purge and startup waste. Identify hidden waste sources and optimize material usage without impacting output.
6-14% lower material waste
5-12% higher first-pass yield
What holds operations back
- Disconnected financial systemsProduction data remains isolated from ERP and costing systems, making true production costs invisible and preventing accurate margin analysis on complex parts.
- Outdated quoting assumptionsQuotes rely on historical cycle time and scrap rate estimates rather than real-time data, leading to margin erosion and missed profit opportunities.
- Reactive production schedulingScheduling operates without real-time machine availability or process capability data, creating frequent disruptions, excess WIP inventory, and poor on-time delivery.
- Siloed multi-site operationsEnterprise operations lack unified visibility across facilities, preventing cross-plant optimization and keeping best practices isolated within individual locations.
How we solve it
- ERP & costing system integrationReal-time cycle time, scrap rates, and utilization data feed directly into job costing and quoting workflows, enabling accurate margin analysis and pricing decisions based on verified production data.
- Automated scheduling supportProduction scheduling receives real-time machine availability, process capability, and material status, enabling predictive capacity planning and dynamic optimization based on actual equipment performance.
- Enterprise dashboards & benchmarkingUnified visibility across multiple plants with facility-specific and enterprise-wide tracking. Supports cross-plant benchmarking, resource allocation decisions, and replication of best practices.
Start where your operation needs it most
When stability improves, margins follow
Reduced scrap
Process stability in temperature and pressure reduces scrap rates, depending on part complexity and material type.
Higher yield
Consistent cycle times and pressure profiles increase first-pass yield, reducing rework and improving delivery predictability.
Lower material waste
Visibility into purge waste and startup scrap reduces material costs without impacting production output.
Reduced downtime
Early detection of temperature drift and pressure anomalies reduces unplanned stops and maintenance costs.
From installation to insights
Three proven steps to transform your manufacturing operations
Sense
Plug-and-play IoT sensors attach to any machine in as little as one minute. Capture real-time data with zero integrations or downtime.
Under 60 seconds per machine
Works with any equipment
No wiring or programming
Analyze
FloControl™ processes thousands of data points per second, turning raw signals into actionable manufacturing intelligence.
Real-time pattern detection
Predictive maintenance alerts
Automatic anomaly detection
Optimize
Transform insights into results with automated alerts, operator tools, and proven workflows that drive continuos improvement.
Smart alert routing
Operator workflow tools
20% min utilization gains
Operational control is a financial strategy
Book a call and see how SensFlo scales with your production environment
Other industries
Common questions
Direct answers to key operational and financial questions
Pricing is based on machine count, monitored variables, and facility scope. The model aligns costs with operational value. Detailed pricing structure and ROI modeling are available on our pricing page. For more information, be sure to check out our Pricing page!
Implementation requires coordination with production and maintenance teams. SensFlo provides onsite training and deployment support. No specialized IT or data science resources are required for ongoing operation.
No. SensFlo complements existing MES and ERP systems by providing real-time process visibility and anomaly detection. It does not replace production scheduling, order management, or quality tracking systems.
Most facilities see measurable scrap reduction and material waste improvement within the first 90 days. Full ROI, including throughput gains and downtime reduction, typically occurs within 12 to 18 months, depending on facility scale and baseline performance. Feel free to use our ROAI calculator for a rough estimate.
All data is encrypted in transit and at rest. SensFlo operates within your network security framework. Access controls are role-based and configurable. Data does not leave your facility environment unless explicitly authorized.
Yes. SensFlo is designed to work with both modern and older injection molding machines. Sensors monitor process variables independently of machine controllers, providing visibility without requiring equipment upgrades.
SensFlo uses retrofit sensors that monitor temperature, pressure, and cycle data from existing injection molding machines and auxiliary equipment. No machine replacement is required. Installation connects to standard facility network infrastructure.
Initial sensor installation typically completes within 2 to 4 weeks for a standard injection molding operation. Full data integration and AI-driven insights are operational within 60 to 75 days. Deployment is modular, allowing phased rollout across production lines.
