食材验收的智能监测数据

食材验收数据的智能监测与分析是一个创新的量化工具，可用于有效管控数据，确保原料质量、降低食安风险，并优化供应链管理。 1.食堂可以通过本数据了解当前食堂食材库存及验收状况，出现食材品类不匹配和数量不匹配时可以通过食材批次号、验收时间等数据快速溯源，及时发现潜在的食材验收问题并做出针对性的措施。2.为食堂带来数字化流程优化，替代纸质验收单，通过移动端录入数据（如拍照上传检疫证明），提升效率和透明度。与ERP系统对接，自动生成采购对账和付款依据，减少纠纷。3.餐饮监管部门可以利用本数据作为监管食堂食材验收成果的依据之一，可通过指数的变化及时发现食材验收长期不合格的食堂，提前进行干预和指导。4.食堂或和监管机构可以将本数据对外披露公开，体现本单位或本地区对食品追溯工作的重视和承诺，有利于增强用餐者的信任。5保险公司可根据本数据提前识别目标食堂客户的投保风险，从而确定相关保险产品的定价，如食品安全责任险。1.数据抽取和预处理： （1）数据抽取：在自研的5G智慧食安工业物联网数字化管理平台数据库中抽取相关食堂的食材验收数据，包括操作时间、批次编号、供应商、合计金额（元）、明细批次号、食材分类、食材名称、计算规格、单位、单价（元）、数量（斤）、小计（元）、验收信息、异常次数、仓库等。（2）数据预处理：对抽取的数据进行清洗，去除重复、错误或无关的信息，以便后续的分析。本数据对供应商敏感信息进行匿名化，充分保障隐私。2.基于食材验收数据进行验收合规判定： （1）重量合规判定：若“验收信息-数量”的绝对值/数量≤5%，则判定为“ 合格”，反之则判定为“ 不合格”；（2）食材合规判定：若实际金额=该批次编号的小计总和，则判定为“ 合格”，反之则判定为“ 不合格”；（3）建立食材验收异常率：计算近30日异常率 = ∑[单日异常批次] ÷ 总验收批次 × 100%。

Intelligent monitoring and analysis of ingredient acceptance data is an innovative quantitative tool that can effectively manage data, ensure raw material quality, reduce food safety risks, and optimize supply chain management.
1. Canteens can use this dataset to understand the current inventory and acceptance status of canteen ingredients. When there is a mismatch in ingredient categories or quantities, they can quickly trace back through data such as ingredient batch numbers and acceptance times, identify potential ingredient acceptance issues in a timely manner, and take targeted measures.
2. It brings digital process optimization to canteens, replacing paper acceptance sheets. Data can be entered via mobile terminals (such as uploading quarantine certificates via photos), improving efficiency and transparency. It can be connected to ERP systems to automatically generate procurement reconciliation and payment basis, reducing disputes.
3. Food safety regulatory authorities can use this dataset as one of the bases for supervising the ingredient acceptance results of canteens. They can timely identify canteens with long-term unqualified ingredient acceptance through changes in indicators, and carry out early intervention and guidance.
4. Canteens or regulatory agencies can publicly disclose this dataset to demonstrate their attention to and commitment to food traceability work, which is conducive to enhancing the trust of diners.
5. Insurance companies can use this dataset to identify the insurance risks of target canteen customers in advance, so as to determine the pricing of relevant insurance products, such as food safety liability insurance.
1. Data extraction and preprocessing:
(1) Data extraction: Extract ingredient acceptance data of relevant canteens from the database of the self-developed 5G intelligent food safety industrial Internet of Things digital management platform, including operation time, batch number, supplier, total amount (yuan), detailed batch number, ingredient category, ingredient name, calculation specification, unit, unit price (yuan), quantity (jin), subtotal (yuan), acceptance information, number of abnormalities, warehouse, etc.
(2) Data preprocessing: Clean the extracted data to remove duplicate, erroneous or irrelevant information for subsequent analysis. Sensitive information of suppliers is anonymized in this dataset to fully protect privacy.
2. Acceptance compliance judgment based on ingredient acceptance data:
(1) Weight compliance judgment: If the absolute value of ("acceptance information - quantity") / quantity ≤ 5%, it is judged as "qualified"; otherwise, it is judged as "unqualified";
(2) Ingredient compliance judgment: If the actual amount = the total subtotal of the batch number, it is judged as "qualified"; otherwise, it is judged as "unqualified";
(3) Establish the ingredient acceptance abnormality rate: Calculate the 30-day abnormality rate = ∑[single-day abnormal batches] ÷ total acceptance batches × 100%.

搜集汇总

背景与挑战

背景概述

该数据集是浙江智飨科技有限公司自行产生的企业数据，包含3105条每日更新的食材验收记录，涵盖操作时间、供应商、合规判定等字段，用于智能监测食材验收合规性，优化供应链管理和降低食品安全风险。