Global 
United States 
What is Label Inspection System?
A product label is a type of wrapper or tag made of paper or film type of foundational material (substrate) that provides necessary information regarding a product. It usually has a laminated layer on top, an adhesive layer on the other side to affix the label on to a surface, followed by a liner that can be separated to attach the label over the product. It contains information such as multilingual instructions for use, pricing, warnings, alerts, ingredients, allergens, nutritional level, branding elements like logo, brand name, tagline, product name, imagery, graphics, brand story, values, legal information, barcode, certifications, quality marks, call to action, social media handles, website information and more.
Given the importance, label inspection plays a pivotal role in the manufacturing industry by assuring quality standards and regulatory compliance related to product labels against human-prone errors, inconsistent quality control, assembly issues and excessive time consumption. AI-based label inspection system is capable of utilizing computer vision and image processing services, as well as machine learning algorithms to automate verification, evaluation and inspection of product labels. Key components include high-resolution cameras, lenses as per factors like depth of field, field of view, imaging technology, lighting setup including diffused lighting, bright and dark field, sensors etc. They capture images of labels, products, packages and detect minute errors such as minor misprints, inaccurate barcodes, inconsistencies, anomalies etc. These systems are trained on predefined criteria as per varying product characteristics in large datasets of product label defects to recognize errors accurately, swiftly and consistently that might get overlooked in traditional methods.
As of 2023, the global market size of label inspection solutions was valued at US $2.1 billion, which is projected to increase at a CAGR of 8.5% reaching a value of about US $4.5 billion by 2032. This growth is majorly driven by the surging demand for quality control, safety, efficacy and compliance in pharmaceuticals, FMCG and other industries. This blog explores the various types of product label defects, advantages of incorporating these systems in manufacturing environments for maintaining product quality and future trends related to this domain.
Growing market size of automated label verification in packaging
Types of Product Label Defects
Issues and errors occurring in product labels during manufacturing can affect the quality standards, safety, legality, readability and cause misinterpretation towards the product. Some common types of label defects observed by any label verification system in product manufacturing are given below –
1. Missing Information: At times, essential details such as instructions for use, ingredients, warnings, important information related to the manufacturer etc., may be omitted.
2. Poor Print Quality: These defects usually include low-resolution printing, smudges, faded text etc. that directly impact the perception of product quality.
3. Incorrect Information: These may include inaccurate data like incorrect nutritional facts, ingredient quantities, allergen information, misleading, false and unsubstantiated claims about the product’s effectiveness, origin and others.
4. Textual Errors: These often refer to misspelled words, incorrect grammar and other textual mistakes identified using Optical Character Recognition (OCR services) leading to diminished credibility of the product and brand.
5. Outdated Information: Such defects include incorrect expiry dates or expired products, labels that reflect older versions of ingredients, instructions that are not applicable, post-formulation changes etc.
6. Inconsistent Design: At times, labels may appear unprofessional by not aligning with established branding guidelines creating distrust amongst customers.
7. Regulatory Issues: There are defects detected through automated label verification related to specific legal requirements in the case of product labels in terms of font size, language, disclosure rules like Occupational Safety and Health Administration (OSHA), Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) mandated by regulatory bodies such as FDA, EU regulations etc.
8. Placement Issues: These defects involve labels that are incorrectly placed on the product, making it difficult for the consumers to abstract necessary information.
9. Dimensional Issues: These types of defects include labels that are inadequately or inappropriately sized that are either too large or too small.
Benefits of Automated Label Verification
Let us go through some of the benefits of utilizing these systems in manufacturing environments for packaging –
Regulatory Compliance
The imaging software compares the captured images against predefined criteria during training. It reports defects against region-specific stringent labeling regulations such as ingredients, nutritional level, allergens etc. This is important to avoid regulatory fines, complaints, product recalls and maintain market credibility. The system enhances traceability by detailed activity and label inspection event logging, which are necessary during audits and quality control processes.
Enhanced Productivity
Vision inspection systems can improve productivity as they automate inspection processes without any compromise related to quality, accuracy, prescribed format for cans, cartons, pouches, bottles, jars etc. This leads to higher outputs, lesser duration of production cycles, reduced time-to-market, optimized utilization of equipment and resources etc.
Improved Efficiency
Label verification system streamlines overall production, diminishes manual processes, enhances throughput and enables savings in terms of costs. It supports brand reputation for market competitiveness, operational efficiency, reduces downtime and optimizes resource utilization.
Working mechanism of a label inspection system
Scalability Support
These systems harness advanced AI/ML algorithms to automatically detect and check labels accurately for discrepancies, to maintain product aesthetics and comply with regulations. They can easily support high precision scale up, large volume production and product line diversification while meeting standards.
Amplified Brand Presence
As these systems lead to consistent labeling, they enhance brand integrity while reflecting its values through high-quality images and content. This forms a positive perception for the brand in the customer’s mind, thus increasing brand loyalty, sales and market share.
Seamless Integration
These systems can be installed and integrated with existing camera and sensors systems in the production facility and packaging lines. It ensures smooth operations while diminishing downtime for activities such as capping, filling etc.
Faster Operations
Incorrect labels can lead to increased recall costs, legal fines and diminished brand reputation, imparting the importance and non-negotiability of the accuracy and quality of labels. While label tags cost lies in the range of $0.10 – $10, manual inspection may take about 30 seconds to 1 minute, that is, about 50 to 90 labels can be checked in an hour approximately. If we take the average wage per hour in the USA to be around $28.34, the cost for manually checking labels within this time interval can come out to be about $0.57 – $1 per label. On the other hand, on deploying label verification system, the same task can be done within a few seconds, leading to double the number of labels checked per hour at half the costs involved otherwise.
Real-Time Feedback
These systems can monitor the manufacturing process in real-time, rectify issues, provide immediate feedback and allow quick adjustments to avoid defective product labels leaving the production line.
Future Trends in Label Inspection
- Sustainability: Manufacturers are adopting eco-friendly label materials and energy-saving labeling machinery alongside recyclable options. They are looking to optimize resource utilization in more creative works than monotonous tasks like label checking. The manufacturing industry is leaning towards the trend of incrementing product reliability with minimal waste generation.
- AI/ML Applications: Use of artificial intelligence and machine learning algorithms is on the rise for correction of label placement, swift defect detection in manufacturing, pattern identification, error reduction and automation of various decisions related to anomaly detection.
- Others: The future of label inspection system will be shaped by AI and machine learning, enhancing accuracy, speed, and defect detection. Real-time analytics will provide manufacturers with valuable insights, reducing downtime. Automation, digitalization, and eco-friendly materials will streamline processes and meet regulatory standards, ensuring competitiveness and higher product quality.
Implement AI Label Inspection in Your Manufacturing Setup
In conclusion, labeling innovations have significantly transformed packaging machinery, enhancing efficiency, compliance, and product integrity. To stay competitive, manufacturers must embrace these innovations, tackle integration challenges, invest in sustainable practices, and utilize AI-driven solutions. KritiKal’s AI integration in label inspection solutions is revolutionizing quality control by improving accuracy, speed, and consistency, addressing limitations of traditional methods, and driving cost savings. As industries evolve, adopting AI for label inspection is crucial for meeting high standards of quality and compliance. Implementing AI solutions requires adapting current practices, training models, and working with experts to ensure effective integration and optimal results. Please get in touch with us at sales@kritikalsolutions.com to know more about our products and realize your automotive requirements.
Siddharth Tyagi has a diverse skill set in C#, Entity Framework, ASP.NET, Microsoft SQL server complemented by practical experience in Azure Services, DevOps and Django. With his proficiency in designing, deploying, managing cloud-based solutions and agile development methodologies, he has assisted KritiKal in delivering various projects to some major clients.