Are you tired of navigating the pitfalls of manual label validation? In most cases, food manufacturers cannot implement label validation technology due to the high cost of equipment and implementation. At Thingtrax, we offer a cost-effective solution leveraging our AI technology. This solution is highly effective and affordable for the entire food manufacturing market.
- Cost effective vision AI technology using IP rated cameras
- Can be integrated with ERP
- Real-time label monitoring and validation
- Instantly highlight errors with alerts and PLC integration to reject product, stop line, etc.
- Shared data and reporting
Solving the label validation pitfalls:
Mislabelling poses significant risks, particularly in emergency product withdrawals, compromising consumer safety and escalating recall urgency. Swiftly addressing label mistakes is crucial to prevent harm and mitigate the strain on the supply chain. Beyond immediate consequences, mislabelling heightens the risk of business loss, with retailers prioritising accurate labels to uphold consumer safety and regulatory standards, potentially leading to contract terminations or hesitancy in forming new agreements. Some of the core pitfalls are as follows:
Accuracy of information: Product labels must accurately reflect the contents of the package. This includes information such as ingredient lists, nutritional values, expiration dates, and usage instructions. Any discrepancies or inaccuracies can lead to customer dissatisfaction, legal consequences, and damage to the brand’s reputation.
Regulatory Compliance: Keeping up with constantly evolving regulations and standards can be a significant challenge. Different regions and countries may have varying requirements for product labels, including information on ingredients, nutritional facts, allergens, language, and more. Ensuring that all labels comply with these regulations is crucial to avoid legal issues and penalties.
Consistency: Maintaining consistency across different product labels is challenging. Each product may have unique requirements and ensuring that the labels are consistent in terms of design, branding, and information presentation is crucial for brand identity and customer trust.
Retail Pack Label Validation powered by AI: A Game Changer
Ideal for Food and Beverage manufacturers and perfect for QA Managers aiming to streamline quality checks and audits. Mitigate risk effectively within your retail pack labelling processes for bottles, beverages, baked goods, and produce. Thingtrax Vision AI enables manufacturers to have:
- Proactive Identification: Real-time monitoring for early detection of label discrepancies.
- Swift Correction: Efficiently address label mistakes, preventing market distribution.
- Supply Chain Efficiency: Minimise disruptions, reducing financial losses, and preserving relationships.
- Consistency Across Product Lines: Ensure uniformity in design and information presentation.
- Regulatory Compliance: Streamline compliance processes for label validation.
- Transparency and Reliability: Build trust with retailers through accurate and reliable information.
Thingtrax Vision AI serves as a comprehensive solution to address these challenges, offering a transformative approach to label validation, supply chain efficiency, and overall risk management.
How does it work?
- Inspect every label with a low-cost camera: Use AI to thoroughly examine each label, ensuring a comprehensive overview of all details and elements.
- Check predefined elements: Scrutinise text, dates, imagery, and positioning on the label, confirming accuracy and adherence to established standards.
- Validate against product specifications: Compare the label against product specifications to ensure it meets predetermined standards, maintaining consistency and accuracy.
- Instantly highlight errors, stop the line, and reject products depending on requirements: Implement a robust reporting system to highlight discrepancies; halt production and reject products if they surpass predefined standards.
- Full data insights and reporting: Enabling the introduction of redundancy checks, continuous training, and process refinements to proactively mitigate risks.