10 Common Challenges in Pharmaceutical Packaging and How Vision Inspection Systems Solve Them

Pharmaceutical packaging lines run fast, change formats often, and carry zero tolerance for
error. A single defective blister reaching the market can trigger a recall, a regulatory
observation, and lasting brand damage. Yet most quality teams still rely on manual checks,
sampling plans, or ageing rule-based cameras that were never designed for today's product
mix. Below are ten recurring pharmaceutical packaging challenges — and how a modern vision
inspection system solves each one.

1. Missing, Broken or Damaged Units in Blisters

Empty pockets, half tablets, chipped edges and cracked softgels escape human inspection at
line speed. At 600–800 blisters per minute, no operator can reliably detect a hairline crack in a
capsule shell. AI-driven blister inspection handles tablets, capsules, bilayer tablets, softgels and
transparent capsules with multi color granules — including the notoriously difficult clear-shell
products where conventional contrast-based systems fail. Every pocket is inspected, every
batch, with image evidence retained.

2. Colour and Shape Mix-Ups

Colour mix, wrong orientation and foreign tablets are high-risk defects because they signal a
line-clearance failure, not just a cosmetic one. Deep-learning models classify variants that rule-
based algorithms confuse — two pink tablets differing only in emboss depth, or a bilayer tablet
loaded upside down. This is genuine packaging quality control, not approximate sorting.

3. Transparent and Reflective Products

Transparent capsules, pre-filled syringes, vials and injectables reflect and refract light
unpredictably. Standard lighting produces glare that masks defects and creates phantom ones.
Purpose-built optics and lighting geometry make these products inspectable at full production
speed, without slowing the line to compensate.

4. Tablet in Bottle Packaging Blind Spots

Tablets in bottles present count accuracy, cap presence/absence and seal integrity risks that
blister lines don’t share.

5. Vial Cosmetic Defects

Cracked necks, chipped flanges, incorrect fill level and misapplied labels (Flagging, Cross
labeling, Double Labelling, wrong alignment or missing label) are core vial rejects, and for sterile
products they are patient-safety issues. Automated vision inspection grades cosmetic and
dimensional defects consistently across every unit, not on a sample basis — removing the
statistical gamble that sampling inherently accepts.

6. Label Placement and Content Errors

Skewed, torn, missing, wrinkled or wrong labels are among the most common recall triggers
globally. A wrong-market label on a correct product is still a recall. A label inspection system
validates presence, position, artwork version and print quality simultaneously, comparing
against the approved master rather than a loose tolerance band.

7. Illegible Overprinting Data

Batch number, MFG, EXP, GTIN, 2D Data Matrix or any other code (1D, Pharmacode, Crypto
Code, etc) and MRP printed on foil or carton must be machine-readable at the pharmacy, the
distributor and the border. OCR/OCV verifies every character against the batch record, rejecting
broken, smudged or shifted text before it becomes a distribution problem.

8. Variable Data and Serialisation Failures

Unique codes, GTIN and aggregation data demand barcode grading, not just decoding — a code
that scans on your line may fail on a supermarket scanner. Print-and-inspect on cartons
validates each code against ISO/GS1 grades before the pack advances, protecting DSCSA, EU
FMD and MoH compliance and preventing costly rework of serialised stock.

9. False Rejects Destroying Yield

Over-sensitive systems reject good product, inflate material cost, and — worse — train
operators to override alarms, which quietly defeats the entire inspection strategy. Inspection
that avoids false rejects is where AI matters most: trained models separate acceptable
cosmetic variation from genuine defects, cutting false reject rates sharply while maintaining
zero-escape performance.

10. Manual Inspection Fatigue and Documentation Gaps

Human inspectors tire within twenty minutes of repetitive visual work, and audit trails go
missing between shifts. Automated product inspection delivers 21 CFR Part 11-compliant
records, batch reports, and defect images — evidence auditors accept immediately, without a
scramble through paper logs.

The Business Case

Pharma manufacturers deploying AI vision inspection typically report fewer market complaints,
higher OEE, faster changeovers and stronger audit outcomes. Recall avoidance alone usually

justifies the investment; yield recovery from reduced false rejects funds it twice. The objective
is simple: catch every defect, reject nothing good, and prove it.
Jekson Vision is among the few suppliers offering AI-integrated inspection across blister, bottle,
vial, label, variable data and carton applications on a single platform — so quality standards
stay consistent across every line in the plant.

Talk to our application team to review your line and defect library.
Calculate ROI for purchasing a Vision System, contact us on marketing@jeksonvision.com