Last updated: 2026-09-05 · 5 min read

In-Process Monitoring for Injection Molding — What Sensors Are Used, What Do They Detect and When Do They Justify the Investment?

In-process monitoring uses cavity pressure sensors (0–2,000 bar, 1,000+ Hz sampling), thermocouples (±0.5°C) and machine data acquisition (injection pressure, screw position, cushion size) to detect defects in real time — short shots, flash, sink, dimensional drift — before the part leaves the mold. The system compares each shot against a learned baseline and flags deviations beyond ±3% for cavity pressure or ±2°C for melt temperature.

Key Facts

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  • Five sensor types: cavity pressure piezo ($1,500–3,000/point), cavity thermocouple ($200–500), machine data acquisition ($500–2,000), mold protect force sensor ($800–1,500), post-eject vision system ($3,000–10,000). Each detects different defect categories.
  • Cavity pressure is the most valuable single data point — it integrates material viscosity, melt temperature, injection speed and packing pressure into one signal. If the pressure curve deviates from baseline, something has changed and the part is likely out of spec.
  • Investment: $2,000–5,000 for single-cavity machine data, $15,000–40,000 for full multi-cavity system with cavity pressure in every cavity. Payback from catching defects before they the customer — eliminates sorting, rework and field returns.

    • Cavity — The hollow space inside the mold that forms the part shape. Multi-cavity molds produce multiple parts per shot. Cavity count determines production output but also mold cost and complexity. Each cavity must be balanced for uniform fill. The related guide covers adjacent topics.

    What Types of Sensors Are Used and What Does Each One Detect?

    Sensor Type What It Measures Defects Detected Cost per Point
    Cavity pressure (piezo) Pressure inside cavity during fill, pack and hold Short shots, flash, sink, over-packing, viscosity shift $1,500–3,000
    Cavity thermocouple Melt temperature at cavity wall Melt temp drift, degraded material, heater band failure $200–500
    Machine data acquisition Injection pressure, screw position, cushion size, cycle time Cushion loss (leakage), cycle time drift, check ring wear $500–2,000
    Mold protect (force sensor) Clamp force on tie bars Flash from insufficient clamp, over-packing, mold damage $800–1,500
    Vision system (post-eject) Part presence, color, surface defects, dimensions Short shots, stuck parts, cosmetic defects, flash $3,000–10,000

    The cavity pressure sensor is the most valuable single data point because it integrates the effects of material viscosity, melt temperature, injection speed and packing pressure into one signal. If the cavity pressure curve deviates from baseline, something in the process has changed — and the part from that shot is likely out of spec.

    When Does In-Process Monitoring Justify the Investment?

    1. High-volume commodity parts (below $0.10 per part, above 1M shots/year). Machine data acquisition only ($500–2,000). Monitors cushion size, cycle time and injection pressure. If cushion drops below setpoint, short shot risk is flagged.
      Payback: 3–6 months from reduced scrap and eliminated manual inspection.
    2. Engineering parts with tight tolerances ($0.50–5.00 per part, 100K–500K shots/year). Cavity pressure sensors in critical cavities ($3,000–9,000 for 2–4 cavities). Detects viscosity shifts from regrind ratio changes, moisture contamination or resin lot variation. Payback: 6–12 months from eliminated customer returns.
    3. Safety-critical or medical parts (above $1.00 per part, any volume). Full monitoring: cavity pressure in every cavity, machine data, mold protect and post-eject vision ($15,000–40,000).
      Every shot documented with pressure curve; out-of-tolerance shots automatically rejected with timestamp. Payback: immediate if a single field failure is prevented.
    4. Multi-cavity molds above 8 cavities. Cavity pressure in every cavity ($1,500–3,000 per cavity). Detects cavity-to-cavity imbalance — some cavities over-pack while others short-shot — invisible to machine-level sensors that only see the combined signal.
      Payback: 6–18 months.

    Shrinkage — The dimensional reduction from mold cavity to cooled part. Amorphous resins: 0.4–0.7% (uniform). Semi-crystalline: 1.0–2.5% (directional). Mold makers apply shrinkage factor when machining cavity. Actual shrinkage varies with wall thickness, gate location and packing pressure. The related guide covers adjacent topics.

    Five sensor types: cavity pressure ($1,500–3,000/point), thermocouple ($200–500), machine data ($500–2,000), mold protect ($800–1,500), vision ($3,000–10,000). Cavity pressure is the most valuable — integrates viscosity, temperature, speed and packing into one signal. Investment from $2,000 to $40,000 depending on application criticality.

  • Key parameter identified — critical variable confirmed against spec.
  • Tolerance within achievable range — commercial ±0.15mm or tighter as needed.
  • Material matched to application — resin grade selected for end-use environment.
  • Process window validated at T1 — parameters locked after first trial.
  • Inspection method defined — CMM, visual, or functional test specified.

    • Frequently Asked Questions

    Can in-process monitoring replace end-of-line quality inspection?

    For dimensional and weight-based defects, yes — cavity pressure monitoring detects the same defects as post-mold inspection, but in real time and on every shot. For cosmetic defects on Class A surfaces, vision inspection is still needed because surface appearance depends on mold texture, gloss and color, not fully captured by pressure data.

    Most programs use both: cavity pressure for structural and dimensional integrity, vision for cosmetic appearance.

    Does the monitoring system require a special mold or sensor installation?

    Cavity pressure sensors require a pocket machined into the cavity insert (typically 6 mm diameter × 10 mm deep) and a wire channel to route the sensor cable to the mold connector. The pocket is usually added during initial mold build — retrofitting an existing mold requires disassembly and re-machining.

    Machine data acquisition requires no mold modification — it connects to the machine’s existing sensors through a data acquisition card or Ethernet interface.

    How long does it take to set up the baseline and start monitoring?

    After the mold is running stable, the baseline is learned automatically over 50–100 consecutive good shots — typically 2–5 minutes of production. Once established, the system monitors every subsequent shot in real time.

    If the process is re-optimized (new material lot, changed parameters), the baseline must be re-learned — another 2–5 minutes. Total setup time is less than 10 minutes per mold changeover.

    Key Takeaways

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  • Five sensors: cavity pressure, thermocouple, machine data, mold protect, vision — each detects different defects.
  • Cavity pressure most valuable — integrates viscosity, temperature, speed, packing into one signal.
  • Investment: $2K–5K machine data, $15K–40K full system.
    Payback 3–18 months depending on part criticality.
  • System catches defects before bad parts ship; operator still diagnoses and corrects root cause.

    • In-process monitoring is not a substitute for good mold design and stable process parameters — it is a safety net that catches what those systems miss. For programs above 100,000 shots with tight tolerances or high defect costs, the investment pays for itself within the first year.

    Sources: Kistler — Cavity Pressure Monitoring Application Notes · RJG — Decoupled Molding Publications · Society of Plastics Engineers (SPE) — Process Monitoring Papers · Priamus — Injection Molding Monitoring Systems · SensoPart — Vision Systems for Injection Molding

    — Arthur, Tooling Engineer at aCatMould