In this episode of the Quality Leaders Podcast, Mandy van den Broek from 4sprong shares her insights on the intersection of quality assurance and artificial intelligence. Van den Broek is a consultant in risk management, specialised in the food industry, currently working with dairy company FrieslandCampina. She discusses how AI has become a crucial tool in achieving consistent quality evaluation and improved classification of quality levels in the food industry. Her experience covers various facets of quality assurance, from her own podcast about entrepreneurship during the Covid crisis to her consultancy work with different companies in the food industry.
WHAT DID WE LEARN FROM THIS EPISODE?
From pigs to pixels: AI has revolutionised quality assurance
AI tools have transformed the process of quality assurance in the food industry completely. They’ve moved the industry away from paper-based quality control to a more data-driven and predictive approach. Van den Broek highlights a specific example where an AI tool was developed to monitor pig welfare in slaughterhouses: something that was previously impossible. AI is also used to classify meat quality by identifying differences in colour, size, and any potential defects. This application of AI ensures a more consistent and reliable evaluation of quality, eliminating human errors and variability.
Blockchain isn’t just for bitcoins
Blockchain technology is gaining more and more importance within the food industry, specifically in quality assurance. The use of blockchain allows for an immutable, traceable record of a product’s journey from farm to consumer. This level of transparency can help ensure the product’s quality and safety while also boosting consumer confidence. “In the future, consumers may even be able to use QR codes to access this blockchain information, providing them with detailed traceability and giving a whole new level of insight into the food they consume”, says the risk manager.
Ensuring consistent quality is possible despite varying conditions
Implementing AI in quality assurance is not without its challenges. According to van den Broek, one of the biggest hurdles is ensuring that the AI tool delivers the expected results under different conditions. Each factory has its own unique environment and set of circumstances, which can affect the functionality and effectiveness of the AI tool. Despite these challenges, the benefits of implementing AI in quality assurance outweigh the difficulties. AI tools provide a more stable quality guarantee, performing consistently under varying conditions and circumstances, something that is particularly valuable in the food industry where quality assurance is paramount.