Injection Molding Simulator – Tutorial (Print Version)

The KEEPLEAN Injection Molding Simulator is an interactive tool designed to teach Design of Experiments (DOE), PID Control and process variability concepts through the real-world context of plastic injection molding of automotive parts.

By adjusting process parameters (temperature, pressure, injection speed, mold temperature) and PID controller tuning, users observe how different settings affect part quality — weight, flatness — and the appearance of manufacturing defects.

Simulator Capabilities

2. Quick Start (90 Seconds)

3. Interface Overview

Layout — Top to Bottom

┌──────────────────────────────────────────────────────────────────────┐ │ 🔵 KEEPLEAN HEADER │ ├──────────────────────────────────────────────────────────────────────┤ │ 🔲 PART SELECTOR (4 cards: NOx Housing · Intake · EGR · Flange) │ ├──────────────────────────────────────────────────────────────────────┤ │ 📋 SPEC PANEL — Technical specs for selected part │ ├──────────────────────────────────────────────────────────────────────┤ │ 🎯 OBJECTIVE BANNER — Weight target · Flatness target (editable) │ ├──────────────────────────────────────────────────────────────────────┤ │ 🎛️ PID SECTION │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │ │ 🌡 Barrel │ │ 💧 Pressure │ │ ❄️ Mold Temp │ │ │ │ Temp (A) │ │ (B) │ │ (D) │ │ │ │ SP slider │ │ SP slider │ │ SP slider │ │ │ │ Kp Ki Kd │ │ Kp Ki Kd │ │ Kp Ki Kd │ │ │ │ Oscillograph│ │ Oscillograph│ │ Oscillograph│ │ │ └──────────────┘ └──────────────┘ └──────────────┘ │ ├──────────────────────────────────────────────────────────────────────┤ │ 💨 SPEED SECTION — S1 Fill · S2 Transition · S3 Pack/Hold │ ├──────────────────────────────────────────────────────────────────────┤ │ 🎬 ANIMATION SECTION │ │ ▶ LAUNCH RUN ⚡ DEMO ×4 ↺ RESET │ │ [Phase bar: 🔒→💉→⏸→❄️→🔓→⬇️] │ │ [SVG Animation: Barrel · Mold · Screw · Melt · Cooling] │ ├──────────────────────────────────────────────────────────────────────┤ │ 📊 RESULTS SECTION │ │ Defect Tracker (9 cards) + Run Results Table + Export │ └──────────────────────────────────────────────────────────────────────┘

Key Display Elements

4. PID Controllers — The 3 Process Regulators

Feature	Description
🔩 4 Automotive Parts	NOx Sensor Housing, Intake Manifold Cover, EGR Valve Housing, Fuel Pump Flange
🎛️ 3 PID Controllers	Barrel Temperature · Injection Pressure · Mold Temperature — each fully tunable
💨 3-Stage Speed Profile	S1 Fill · S2 Transition · S3 Pack/Hold — independent control
🎬 Cycle Animation	6-phase realistic injection cycle with SVG animation
⚡ DEMO Mode	Automatic 4-run tour with guided section highlighting
📊 Defect Tracking	9 defect types tracked cumulatively across runs
📋 Run History	Full results table with all parameters and measured outputs
📥 Export	Excel (.xlsx) data export for statistical analysis

Element	Location	Purpose
Part Selector	Top	Switch between 4 automotive parts — resets all results
Spec Panel	Below part cards	Shows dimensions, material, weight & flatness specs
Objective Banner	Below spec panel	Editable weight target and flatness max — customize your specs
PID Cards	Middle section	Set process setpoints and tune controller parameters
Oscillographs	Bottom of each PID card	Visual representation of process stability / noise level
Speed Stages	Below PID section	Set 3-phase injection speed profile
Phase Bar	Animation section	Shows current cycle phase highlighted in real time
SVG Animation	Animation section	Live visual of injection unit and mold during cycle
PV Displays	PID cards (after run)	Shows actual Process Value measured at end of cycle
Defect Grid	Results section	9 defect cards with risk level and cumulative count
Run Table	Results section	Full run history with all parameters and outputs

Each PID controller manages one critical process variable. The quality of your PID tuning directly affects the process variability — and therefore the scatter of your results.

Setpoint Slider

Each PID card has a Setpoint (SP) slider at the top. This is the target value you want the process to reach and hold. The slider range corresponds to the experimental window for that variable.

Kp, Ki, Kd Parameters

The Oscillograph

Parameter	Full Name	Role in the Controller
Kp	Proportional Gain	Reacts to current error. Too low = slow response. Too high = oscillation.
Ki	Integral Gain	Eliminates steady-state error over time. Too high = instability.
Kd	Derivative Gain	Anticipates future error. Reduces overshoot. Too high = noise amplification.

Each PID card displays a real-time oscillograph — a signal trace showing the simulated PV fluctuation. A flat, stable line near center = well-tuned controller. A noisy, oscillating signal = poor tuning and high process variability.

5. Injection Speed — 3-Stage Profile

Unlike a simple single speed, real injection machines use a multi-stage speed profile to optimize part quality at each phase of cavity filling. The simulator implements 3 stages:

Effective Speed (Weighted Average)

The simulator calculates an Effective Speed (C) as a weighted average of the 3 stages, reflecting the dominant influence of each phase on the overall process. This is the value used in the DOE model.

6. Injection Cycle Animation — 6 Phases

Stage	Volume Range	Slider Range	Typical Effect
S1 — Fill	0 → 80%	80–100 mm/s	Too fast → Jetting, Silver Streak. Too slow → Short Shot.
S2 — Transition	80 → 95%	40–60 mm/s	Too fast → Flash, Weld Lines. Controls V/P switchover quality.
S3 — Pack	95–100%	5–30 mm/s	Too fast → Sink Marks, Sticking. Too slow → incomplete pack.

When you click ▶ LAUNCH RUN, the simulator runs a complete injection cycle, animated in 6 sequential phases. Each phase is highlighted in the phase bar and shown in the SVG animation.

Control Buttons

7. Understanding Results

Quality Outputs — What is Measured?

PV vs SP — After the Run

Phase	What Happens	What to Watch
🔒 Mold Close	Mobile platen moves to close mold. Clamping force applied.	Mold halves come together in animation
💉 Injection	Screw advances, pushing molten plastic through nozzle into mold cavity at set speed & pressure.	Screw moves forward · Melt flow visible · Cavity starts filling
⏸ Hold Pressure	Screw maintains pressure to compensate for shrinkage as material begins to cool. Critical for part weight.	Pulsing indicator at nozzle · Partial fill visible
❄️ Cooling	Mold cooling channels remove heat. Part solidifies. Screw retracts to prepare next shot.	Animated cooling lines · Screw retracts · Part color changes
🔓 Mold Open	Clamping force released, mobile platen retracts. Part remains on core side.	Mold halves separate
⬇️ Ejection	Ejector pins push part out of mold. Part drops. Weight and conformity displayed.	Part appears below mold · Weight shown with ✓ or ✗

Button	Function	Notes
▶ LAUNCH RUN	Starts one complete injection cycle	Disabled during animation. Results added to table after cycle.
⚡ DEMO ×4	Automatically runs 4 cycles in sequence with a guided tour of sections	Uses current parameter settings. Ideal for demonstrations.
↺ RESET	Clears all run results and resets the animation	Does NOT change your parameter settings

Output	Unit	What it Represents	Conformity
Weight	grams (g)	Mass of the ejected part. Reflects how completely the cavity was filled and packed. Influenced by pressure, temperature, speed.	Must be within Target ± Tolerance (e.g., 48 ± 1 g)
Flatness	mm	Geometric deviation of the part's reference surface. Reflects warpage and residual stress from cooling and pressure gradients.	Must be below maximum (e.g., < 0.20 mm)

At the end of each cycle, the PID cards update their PV (Process Value) display, showing the actual value achieved during the run. Compare PV to SP to understand control performance:

The Run Results Table

Conformity Rate

Column	Content
Run #	Sequential run number
Barrel °C (PV)	Actual barrel temperature achieved · SP shown in parentheses
Press. bar (PV)	Actual injection pressure achieved · SP in parentheses
S1 / S2 / S3 mm/s	Injection speed at each stage (as set)
Mold °C (PV)	Actual mold temperature achieved · SP in parentheses
Weight (g)	Measured part weight — green if within spec, red if out
Flatness (mm)	Measured flatness — green if within spec, red if out

The header area shows a running Conformity Rate (%) — the percentage of runs producing parts that meet both weight AND flatness specifications. This is your key process performance indicator.

8. Defect Tracker — 9 Defect Types

The simulator tracks 9 classic injection molding defects, each linked to specific process conditions. Cards show cumulative count and percentage across runs, with colour-coded risk levels:

Defect Reference Guide

9. Exporting Data

Export to Excel (.xlsx)

Risk Level	Threshold	Card Colour
✅ Low	< 20% of runs	Green border
⚠️ Medium	20–50% of runs	Orange border
❌ High	> 50% of runs	Red border + glow

Stage	Defect	What it Looks Like	Parameter Direction to Watch
S1 Fill	Short Shot ◼	Incomplete cavity fill — part is missing material	Pressure too low · Speed S1 too slow · Temp too low
Silver Streak ∿	Silvery streaks on surface — moisture or gas trapped during filling	S1 speed too high · Temperature too high
Jetting ⤳	Worm-like marks from melt jetting across open cavity before wall contact	S1 speed very high · Pressure high · Mold temp low
S2 Trans.	Weld Line 〰	Visible line where two melt fronts meet — potential weakness	S2 speed too high · Temperature too low
Flash ⚡	Thin film of plastic at parting line — overflow outside cavity	Pressure too high · S2 speed too high
Bubble / Void ○	Internal air pocket or surface blister — gas entrapment	S2 speed too high · Mold temp too low · S3 too slow
S3 Pack	Sink Mark ⌣	Surface depression on thick sections — insufficient pack	S3 too fast · Pressure insufficient during hold
Warpage ⌇	Part bends or twists after ejection — uneven residual stress	Flatness out of spec · Cooling imbalance · Pressure issues
Sticking ⊡	Part difficult to eject — adheres to mold surface	S3 too fast · Mold temp too low · Pressure too high

Click the 📥 Export Excel button in the results section to download all run data as an Excel file. The file is named automatically with the part name and date:

10. DOE Applications

Factors and Their Levels

Suggested Experiment Designs

Response Variables

Column in Export	Content
Run #	Sequential run number
Barrel SP / PV	Setpoint and actual barrel temperature
Press. SP / PV	Setpoint and actual injection pressure
S1 / S2 / S3 mm/s	Injection speed at each stage
Mold SP / PV	Setpoint and actual mold temperature
Weight (g)	Measured part weight
Flatness (mm)	Measured part flatness
OK?	OK or NOK conformity verdict

Factor	Symbol	Low Level (−)	High Level (+)	Units
Barrel Temperature	A	250	270	°C
Injection Pressure	B	1000	1400	bar
Injection Speed (eff.)	C	Low	High	mm/s
Mold Temperature	D	50	80	°C

Design	Runs Required	What You Learn
One-Factor-at-a-Time (OFAT)	8–12	Individual effects only — misses interactions
Full Factorial 2² (A, B only)	4	Effects of Temp + Pressure + their interaction
Full Factorial 2³ (A, B, C)	8	3 main effects + 3 two-factor interactions
Full Factorial 2⁴ (A, B, C, D)	16	All 4 factors, all interactions
Fractional Factorial 2⁴⁻¹	8	Efficient screening — half the runs of full 2⁴

Run your DOE using Weight (g) and Flatness (mm) as responses. You can run separate analyses for each or use a multi-response optimization approach.

Mistake	Consequence	Solution
Changing PID settings between DOE runs	Uncontrolled variability confounds results	Fix PID at start and keep constant
Only running 1 replicate per condition	Cannot estimate process noise	Run 2–3 replicates per factor combination
Changing part mid-experiment	Different model — incompatible data	Select part first, keep constant throughout
Ignoring defect tracker	Miss root causes of non-conformities	Check defect cards after every few runs
Forgetting to export before Reset	All data lost	Export Excel before clicking Reset

Objective	Key Parameters to Adjust
Increase part Weight	↑ Pressure · ↑ Hold time (S3 slower) · ↑ Temperature
Improve Flatness	Balanced cooling · Moderate pressure · Reduce S3 speed
Eliminate Short Shot	↑ Pressure · ↑ S1 speed · ↑ Temperature
Eliminate Flash	↓ Pressure · ↓ S2 speed
Eliminate Jetting	↓ S1 speed · ↑ Mold Temperature
Reduce variability	Improve PID tuning (Kp, Ki, Kd near optimal)
Maximize conformity	Run a DOE — find the sweet spot for all 4 factors

Plastic Injection Molding Process Simulator

📋 Table of Contents

1. Introduction

What is the Injection Molding Simulator?