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从人工智能概念到实际应用:人工智能如何帮助提高食品安全和质量.pdf

上传人: Fl****zo 编号:724370 2025-07-01 18页 8.76MB

1、From AI concepts to real-world use:How AI helps improve Food Safety and Quality.DNV ModeratorSilvana Susi,Food&Beverage Certification and Training Specialist for DNV2DNV We are in the AI-driven eraDNV We are at Rapid AI Adoption Rate DNV What is AI?DNV Think about the Challenges in Food and Beverage

2、 How can AI Assist?FSQ in Design Specifications HACCP/FSP Allergen Mgmt Supplier QA Plant&Equipment Design/Capability Package Integrity Contracts Selection/Approval Material Monitoring Continuous Improvement Specifications HACCP/FSP Supplier QA Traceability Sanitation&Allergen Control Complaint Mgmt

3、 Process Capability/Lean Six Sigma Infrastructure Investment FS Culture Traceability Warehouse Controls Complaints Warehouse Control Specification Labelling Consumer Feedback Process CapabilitiesFSMS&Quality Systems DATA DATA INSIGHTSCOMPLEX REGULATORY FRAMEWORKPrimary ProductionFood Safety QualityF

4、ood Supply ChainFood Raw MaterialsIndustrial ProductionTransport logisticsStorage HouseholdUse ConsumptionStorage HouseholdDNV Expert Panel7Dr.Vera Dickinson,Founder&CEO of Innova-QKathleen Wybourn,Director of Food&Beverage North America for DNVDNV What are the top challenges in the industry seen fr

5、om certification?DNV Can these challenges be addressed by AI?DNV What are the watch-outs that you see associated with implementing AI solutions?DNV Managing AI risks and rewards ISO/IEC 22989 Information Technology Artificial Intelligence concepts and terminology ISO/IEC 42001 Information Technology

6、 Artificial Intelligence Management systems Worlds first AI management system standard providing guidance on rapidly changing field of technology.ISO 42001 addresses the challenges with AI such as ethical,transparency and continuous learning.The main objective is a providing a structured way to mana

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本文概述了AI在食品安全和质量管理中的应用。以下是关键点: 1. **AI应用增长**:处于AI驱动时代,AI采用率迅速上升。 2. **AI定义挑战**:AI可在食品饮料行业的多个方面提供协助,如HACCP、供应商质量保证、包装完整性等。 3. **监管框架**:AI帮助应对复杂的监管框架,确保合规性。 4. **技术标准**:ISO标准如ISO/IEC 22989和ISO 42001提供AI管理的指导,强调风险与创新之间的平衡。 5. **NLP模型**:AI通过自然语言处理,理解多语言标签,匹配监管要求。 6. **风险管理与决策**:AI结合机器学习和认知计算,提供现代化的风险管理,支持决策过程。 7. **过程控制与追溯性**:计算机视觉和AI数据智能改善过程控制和产品追溯。 8. **合规管理**:AI助力生成合规报告,自动识别和标记风险。 9. **竞争优势**:AI在FSQ和监管管理中的应用成为不仅是技术优势,也是竞争力的必要条件。 核心数据引用: - AI在标签审查中可自动标记缺失或不正确的项目,如致敏原或未批准的声明。 - AI能够实现实时数据集成,自动化标签和条形码验证,实时监控原料和产品流,预测追溯性差距。 总结:文章强调了AI在食品安全和质量系统中的应用,以及它如何成为合规性和竞争力的关键因素。
"AI如何提升食品安全?" "食品行业AI应用的挑战有哪些?" "AI如何助力食品合规管理?"
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