| 批次清单结合Petri网追溯模型提高小麦粉加工过程追溯精度 |
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| 引用本文： | 王姗姗,赵春江,钱建平,吴保国,陈栋,宋英卓.批次清单结合Petri网追溯模型提高小麦粉加工过程追溯精度[J].农业工程学报,2018,34(14):263-271. |
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| 作者姓名： | 王姗姗 赵春江 钱建平 吴保国 陈栋 宋英卓 |
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| 作者单位： | 北京林业大学信息学院;国家农业信息化工程技术研究中心;农产品质量安全追溯技术及应用国家工程实验室 |
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| 基金项目： | 国家自然科学基金面上项目"连续闭环加工中智能柔性追溯模型构建及系统验证：以小麦粉加工为例"（31671593）;北京市农林科学院2017年度科研创新平台建设（KYCXPT201723）联合资助 |
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| 摘 要： | 为解决小麦粉加工过程追溯质量安全信息交叉、单位个体追溯困难等问题,该研究在分析小麦粉加工流程和追溯关键信息的基础上,研究基于批次清单的信息追溯方法,以加工时间为依据结合高津托图(Gozintograph)数据结构构建批次清单(bill of lots,BOL),实现小麦粉产品信息和关键节点活动信息的精确追溯;在BOL的基础上,利用鱼骨图和Petri网分别描述小麦粉质量追溯点的位置和危害指标;结合山东某面粉厂实际生产参数对追溯模型进行验证,实现小麦粉产品与原料的批次关联和其质量危害传播路径的预测。分析结果表明,通过使用BOL和Petri网追溯模型与传统方法相比实现召回批次数量由7个减少到4个、危害因素查找数量由6个减少到5个。该研究提高了小麦粉追溯精度和缺陷召回效率,为粮食等小颗粒产品加工过程的追溯提供了理论支持。
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| 关 键 词： | 农产品 模型 供应链 小麦粉加工 追溯 加工时间 批次清单 Petri网 |
| 收稿时间： | 2018/2/5 0:00:00 |
| 修稿时间： | 2018/5/9 0:00:00 |
Bill of lots combined with Petri tracing model improving traceability of wheat flour processing |
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| Wang Shanshan,Zhao Chunjiang,Qian Jianping,Wu Baoguo,Chen Dong and Song Yingzhuo.Bill of lots combined with Petri tracing model improving traceability of wheat flour processing[J].Transactions of the Chinese Society of Agricultural Engineering,2018,34(14):263-271. |
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| Authors: | Wang Shanshan Zhao Chunjiang Qian Jianping Wu Baoguo Chen Dong and Song Yingzhuo |
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| Institution: | 1. College of Information, Beijing Forestry University, Beijing 100083, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China,1. College of Information, Beijing Forestry University, Beijing 100083, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China,2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China,1. College of Information, Beijing Forestry University, Beijing 100083, China;,1. College of Information, Beijing Forestry University, Beijing 100083, China; and 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China |
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| Abstract: | Abstract: With the development of information technology and people''s awareness of food safety, traceability information technology has become an indispensable technology and tool for food and agricultural enterprises to handle quality and safety accidents, achieve product traceability, and solve the problem of defective products in time. Grain has a strategic position in China. The Chinese government and people have attached importance to the quality and safety of food. Wheat flour was one of the main grain products. However, the wheat flour processing was a complex technique, which was made up of many links, and had complicated batch mixing. Due to these characteristics, the traceability information of wheat flour quality and safety was crossed and it was difficult to trace the single individual. Most of the current tracing methods were not suitable for wheat flour traceability. Therefore, there was a pressing need to improve the precision of wheat flour tracing and solve its quality and safety problems by using raw materials and product batches as traceability units in wheat flour traceability. First of all, through case investigation, the processing flow of wheat flour was summarized, and the key nodes and traceability information affecting the quality and safety of wheat flour in the process were analyzed in this study. Then, the concept of batch list was introduced and the construction process was improved. The composition relationship and activity process of wheat flour and raw materials batch were analyzed. The relevant parameters in the production line such as flow volume and storage capacity were added to build and update the batch list based on the node processing time. Gozintograph method was used for data storage. The construction process and information tracing of BOL (bill of lots) were described in detail, which can achieve the accurate tracing of product information and key node activity information. On the basis of BOL''s "parent-child" node, the location of wheat flour quality traceability points, hazard indicators, and structural relationships between nodes were clearly described using fishbone maps. The fishbone map was transformed into Petri net to construct the Petri net model of quality and safety relationship during wheat flour processing. The information that affected wheat flour quality and safety in wheat flour processing, such as laboratory results and environment conditions, was decomposed and quantified. The entire process of quality tracking hazard change was expressed by defining Petri Net''s six-tuple. The dynamic characteristics of Petri net were used to estimate the pathway of hazard propagation, and the efficiency was improved. The batch list of wheat flour was constructed by using practical cases to prove the accuracy of Petri net and the feasibility of the tracing method. The results showed that BOL can analyze material batch information and activity information, and trace the information of wheat flour processing. By using the tracing model for wheat flour processing based on BOL and Petri, the number of recalled batches was reduced from 7 to 4 and the number of hazards searched was reduced from 6 to 5 compared to the traditional method. The Petri net model can quickly and effectively predict the hazard propagation pathway and improve the tracing accuracy of wheat flour and the efficiency of defects recalling. The results provide theoretical support for the traceability of grain and other small-sized products, as well as the information technology of traceability for related production enterprises. |
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| Keywords: | agricultural products models supply chain wheat flour processing traceability processing time BOL Petri net |
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