Technical Study Summary · Process Engineering

Improving Packaging Seal Strength
Through Design of Experiments

A structured Design of Experiments (DoE) study applying a 2³ Full Factorial design to identify the optimal machine settings for maximising seal strength on food wrapping equipment.

Study Period: January – March 2013 Design: 2³ Full Factorial · 24 Randomised Runs Application: Food Wrapping Machinery Analysis Tool: Minitab 16 · ANOVA

Section 01

Study Background & Objective

Business Driver

Recurring customer complaints regarding package seal failures during transit had led to an estimated 3–4% product return rate in the quarter preceding the study. The QA team identified inconsistent sealing as the root cause, prompting a structured DoE investigation rather than continued OVAT (one-factor-at-a-time) testing.

Primary Objective

Identify the optimal combination of sealing temperature, sealing pressure, and machine speed on the food wrapping machine to maximise seal strength, ensure product integrity, and reduce field returns — while building internal statistical capability within the engineering team.

Context note: This study represented a significant methodological step forward — moving from OVAT testing to a statistically rigorous full factorial framework. Analysis was performed in Minitab 16. Seal strength was measured using a calibrated digital tensile tester per ASTM F88 Standard Peel Test on 5 samples per run.

Section 02

Experimental Design

Sealing Temperature

Factor A · Positive Effect

Drives polymer chain diffusion to sealing initiation temperature. Largest positive lever in the study.

150°C (Low) 170°C (High)

Sealing Pressure

Factor B · Positive Effect

Acts as a thermal conductor — compresses film layers, removes air pockets and enables heat penetration to the sealant core.

40 psi (Low) 60 psi (High)

Machine Speed

Factor C · Negative Effect

Higher speed reduces dwell time between jaws — film core cannot reach sealing initiation temperature, producing a shallow bond.

80 ppm (Low) 100 ppm (High)

Response Variable

Seal Strength — N/m

Force required to peel apart sealed edge per ASTM F88. 5 samples per run, averaged. Minimum specification: 650 N/m.

Min spec: 650 Target: 887+

Design structure: 2³ full factorial · 8 unique treatment combinations · 3 replicates = 24 total randomised runs · Resolution V (no confounding between main effects or 2-factor interactions) · Statistical power >90% for effect sizes ≥30 N/m · Software: Minitab 16

Section 03

Theoretical Foundations

✓ Full Factorial 2³ — Used Here

✓Orthogonality: Each factor's effect is estimated independently — no cross-contamination of results.
✓Interaction Detection: Captures synergies like Temp × Pressure that OVAT permanently misses.
✓Efficiency: 8 unique runs cover the complete experimental space. With replication: 24 total runs.
✓Resolution V: No confounding between main effects or 2-factor interactions — all terms estimable.

✗ OVAT — Avoided in This Study

✗Interaction Blind: Changes one variable while holding others fixed — cannot detect synergies between factors.
✗Runs Inefficient: More total experiments for less information; poor signal-to-noise ratio.
✗Optimum Missed: The true optimal is often at an interaction point invisible to OVAT.
✗No Error Estimate: Without replication structure, experimental error cannot be properly quantified.

ANOVA — Key Statistical Concepts

Variance Decomposition

SS_Total = SS_Model + SS_Error

Separates the variation explained by controlled factors from random experimental noise.

F-Statistic & p-value

F = MS_Factor / MS_Error. If p < 0.05, reject H₀ — factor has a real effect with 95% confidence.

R² & Adequate Precision

R² = proportion of variance explained (0–1). Adequate Precision = signal-to-noise; must exceed 4.0 for a navigable model.

Section 04

2013 Analytical Dataset

Run	Temp A (°C)	Pressure B (psi)	Speed C (ppm)	Rep 1 (N/m)	Rep 2 (N/m)	Rep 3 (N/m)	Average (N/m)
1	150 (−)	40 (−)	80 (−)	610	625	618	617.7
2	170 (+)	40 (−)	80 (−)	755	740	762	752.3
3	150 (−)	60 (+)	80 (−)	690	705	698	697.7
4	170 (+)	60 (+)	80 (−)	880	895	887	887.3 ★
5	150 (−)	40 (−)	100 (+)	550	565	558	557.7 ▼
6	170 (+)	40 (−)	100 (+)	640	655	647	647.3
7	150 (−)	60 (+)	100 (+)	615	630	622	622.3
8	170 (+)	60 (+)	100 (+)	710	725	718	717.7

Optimal (Run 4)

887.3

N/m · 170°C / 60 psi / 80 ppm

Worst (Run 5)

557.7

N/m · 150°C / 40 psi / 100 ppm

Range

329.6

N/m spread · Min spec: 650 N/m

★ Optimal row highlighted blue ▼ Worst row highlighted amber · Runs 5 & 6 below the 650 N/m minimum specification at original settings.

Section 05

ANOVA Results & Factor Coefficients

A POSITIVE · p < 0.001

+65

Sealing Temperature

Highest sensitivity. Drives polymer diffusion; dominant single factor in the model.

C NEGATIVE · p < 0.001

−55

Machine Speed

Reduces jaw dwell time. Film core cannot reach sealing initiation temperature — shallow bond results.

B POSITIVE · p < 0.001

+40

Sealing Pressure

Thermal conductor — flattens film layers, removes air pockets, enables heat to reach sealant core.

AB INTERACTION · p = 0.015

+20

Temp × Pressure

Significant synergy. Benefit of increasing temperature is much greater at 60 psi than at 40 psi.

Seal Strength (N/m) = 715 +65·A +40·B −55·C +20·A×B
Coded factors: A=(T−160)/10 · B=(P−50)/10 · C=(S−90)/10

⚠ Important gap: The model as reported does not include the ABC three-factor interaction term, and R², Adjusted R², Predicted R², and Adequate Precision were not formally presented. Published comparable 2³ studies have found the three-factor interaction highly significant. This term should be estimated and tested before deploying the regression model for process control.

Section 06

Temperature × Pressure Interaction (AB)

The Physics Behind the Interaction

→Thermal Conductivity: High pressure (60 psi) compresses film layers, removing microscopic air pockets that otherwise act as thermal insulators.
→Sealing Initiation Temp: At 40 psi, only the film surface reaches sealing temperature. The polymer core remains unactivated, producing a shallow bond.
→Synergistic Gain: At 60 psi + 170°C, both film surfaces achieve full polymer diffusion — the mechanism behind the non-parallel interaction plot lines.
→Practical Implication: Optimising temperature or pressure independently misses the true optimum. Both must be set jointly.

INTERACTION PLOT — Temp × Pressure

Non-parallel lines confirm significant interaction · p = 0.015

Key implication: The gain from raising temperature is +190 N/m at 60 psi but only +135 N/m at 40 psi. Operating at high temperature with low pressure wastes energy and underperforms. The two parameters must always be set in concert.

Section 07

Identified Optimal Process Settings

Temperature

170°C

Factor A — High Level

Pressure

60 psi

Factor B — High Level

Machine Speed

80 ppm

Factor C — Low Level

Section 08

Study Gaps vs. Modern DoE Best Practice

Gap Area	2013 Original Approach	Recommended Improvement	Priority
ABC 3-Factor Interaction	Not tested in ANOVA table	Published 2³ full factorial studies have found the three-factor interaction significant (F>100, p<0.0001) in comparable processes. This term must be explicitly estimated — omitting it leaves the model underspecified.	High
Model Diagnostics	R², Adj R², Pred R² not reported	Report R², Adj R², Pred R², and Adequate Precision (must exceed 4.0). A well-specified 2³ model should achieve R²>0.98 and Adequate Precision>30 for reliable process navigation.	High
Gage R&R	No measurement system study conducted	Pre-study Gage R&R required per AIAG MSA 4th Edition. Measurement variation must be <10% of total process variation before committing to a DoE.	High
Centre Points	Not included — curvature undetectable	Add 3–5 centre-point runs (160°C, 50 psi, 90 ppm) in Phase 2 to detect non-linearity in the response surface.	Medium
Residual Analysis	No normality / variance checks shown	Generate: normal probability plot of residuals, residuals vs. fitted, and run-order plot. Non-constant variance is common in heat-sealing processes.	Medium
Response Surface & Contour Plots	Not generated in either document	Phase 2 RSM study (Central Composite Design) to map the full seal strength response surface — identify exact optimal ridge and throughput trade-off zones.	Phase 2

Section 09

Implementation Roadmap

Four immediate actions before full plant deployment, followed by a structured Phase 2 programme:

Parameter Locking — SOP Update

Lock 170°C / 60 psi / 80 ppm as the standard SOP for the food wrapping machine. Update machine setup card and Andon board immediately. Maintain 60 psi jaw pressure via bi-weekly mechanical audit.

Jaw Hardware Audit

Inspect seal jaw heating elements for cold spots using a thermal camera. Temperature uniformity across the jaw face is critical — localised cold zones directly undermine the large positive effect of Factor A.

Sensor & PID Upgrade

Upgrade thermocouple precision to ±1°C. Install jaw pressure transducers for real-time PSI monitoring. Consider PID loop auto-tuning to eliminate thermal drift between production shifts.

Cpk Validation Run

Execute 50-pack stress run at optimal settings. Compute Cpk (Process Capability Index). Target Cpk ≥ 1.33 before full plant rollout. Document prediction interval compliance and confirm model predictions.

Phase 2 Roadmap

→Conduct RSM study (Central Composite Design) with centre points to explore non-linear response and generate full 3D contour maps of the seal strength surface.
→Investigate film type and thickness as additional factors — significant cost levers in the FMCG packaging market.
→Explore whether intermediate speed (90 ppm) with compensated temperature/pressure settings can recover throughput without sacrificing seal quality.
→Consider pre-heating film as a mechanism to unlock higher throughput (100–120 ppm) without dwell-time trade-off.

Section 10

Key Takeaways

✓

Optimal settings confirmed: 170°C / 60 psi / 80 ppm delivers 887.3 N/m seal strength — 59% above the worst-case combination and well above the 650 N/m minimum specification.

✓

Factor hierarchy established: Temperature is the primary lever (+65), Machine Speed the greatest threat (−55), and Pressure the structural foundation (+40). Speed should never be increased without compensating adjustments to the other two.

✓

Temperature × Pressure interaction is real and significant (p = 0.015): The synergy is not additive — temperature and pressure must be jointly optimised. Setting them independently leaves significant seal strength on the table.

✓

Full Factorial design was the correct choice: The AB interaction would have been permanently invisible under OVAT. The 2013 team's decision to use a 2³ full factorial was methodologically sound and enabled the most important finding of the study.

Three open items before production rollout: (1) ABC three-factor interaction not tested, (2) model diagnostics (R², Adequate Precision) not reported, (3) pre-study Gage R&R on the tensile tester not conducted. All three are classified High Priority.

→

Phase 2 path is clear: RSM study with centre points to map the full response surface, detect curvature, and unlock throughput at 90–100 ppm without sacrificing seal integrity.