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金属矿山 ›› 2024, Vol. 53 ›› Issue (01): 72-79.

• “智能矿山建设与实践”专题 • 上一篇    下一篇

基于CNAS体系标准的LIMS创新实践

李日平1 刘晓明1 马少维2 陈 省1 郑永祥1 周宇栋3
  

  1. 1. 深圳市中金岭南有色金属股份有限公司凡口铅锌矿,广东 韶关 512325;2. 中南大学资源与安全工程学院,湖南 长沙 410083;3. 伦图科技(长沙)有限公司,湖南 长沙 410083
  • 出版日期:2024-01-15 发布日期:2024-04-21
  • 基金资助:
    国家自然科学基金面上项目(编号:202352374256)。

Innovative Practice of LIMS Based on the CNAS System Standard

LI Riping1 LIU Xiaoming1 MA Shaowei2 CHEN Sheng1 ZHENG Yongxiang1 ZHOU Yudong3 #br#   

  1. 1. Fankou Lead-zinc Mine,Shenzhen Zhongjin Lingnan Non-ferrous Metals Co. ,Ltd. ,Shaoguan 512325,China;2. School of Resources and Safety Engineering,Central South University,Changsha 410083,China;3. LogicTrue Technology (Changsha) Co. ,Ltd. ,Changsha 410083,China
  • Online:2024-01-15 Published:2024-04-21

摘要: LIMS 是一种专为实验室设计的信息管理系统。 矿山企业引入该系统有助于实现检测业务的数字化管 理。 然而,市面上通用的 LIMS 软件普遍存在与 CNAS 体系结合不紧密、流程管理不严谨、行业适用性不强等缺陷,无 法满足矿山行业实验室的特殊需求。 为此,结合 CNAS 质量管理体系要求以及矿山化验检测业务特点,研发了一款符 合金属矿山行业特点的 LIMS 系统,对传统化验检测业务管理模式进行了全面改造和提升,内容涵盖业务管理、检测 流程、结果汇总、报告管理、报告溯源和 CNAS 体系运行管理等多方面。 该系统引入了样品类型、设备类型、化验岗位、 再现性限设置以及报告权限设置等概念,并建立了关联关系,能够批量委托检测任务、灵活设置用户报告审批权限。 根据关联关系,系统可自动将检测任务分配到特定的检测班组和化验岗位,自动计算检测项目的再现性限,判断平行 检测结果是否超差,确定重验方式及平均结果的计算方法。 此外,系统还利用 LT-IoT 数据采集平台,实现了分析仪 器、天平、温湿度计、二维码等数据的自动采集,确保数据准确性、完整性和可追溯性,有效避免了传统手工录入导致的 错误和不确定性。 应用效果表明:该系统的研发与应用可以为金属矿山行业提供了一个高效、严谨、规范化的实验室 信息管理系统,有助于提高检测业务的数字化管理水平,为行业的数字化转型提供强有力支持。

关键词: 化验检测, LIMS, 数字化, 矿山企业, 智能矿山

Abstract: LIMS is an information management system specially designed for laboratories. The introduction of the system by mining enterprises can help realize the digital management of testing business. However,the general-purpose LIMS software on the market generally has defects such as incomplete integration with CNAS system,imrigorous process management and weak industry applicability,which cannot meet the special needs of mining industry laboratories. Therefore,combined with the requirements of CNAS quality management system and the characteristics of mine laboratory testing business,a LIMS system that meets the characteristics of metal mining industry has been developed,and the traditional laboratory testing business management mode has been comprehensively reformed and improved. The content covers business management,testing process,result summary,report management,report traceability and CNAS system operational guidance. The system introduced the concepts of sample type,equipment type,laboratory post,reproducibility limit setting and report authority setting,and established the correlation relationship. It can batch commission test tasks and flexibly set the user report approval authority. According to the correlation relationship,the system can automatically assign the detection task to a specific detection team and laboratory post,automatically calculate the reproducibility limit of the detection item,determine whether the parallel detection result is out of tolerance,and clarify the retest method and the calculation method of the average result. In addition,the system uses the LTIoT data acquisition platform to achieve automatic data acquisition of analytical instruments,balances,hyhumidity meters,twodimensional codes,etc. ,to ensure data accuracy,completeness and traceability. It effectively avoids the errors and uncertainties caused by the traditional manual entry. The application results show that the development and application of the system provides an efficient,rigorous and standardized laboratory information management system for the metal mining industry,helps to improve the digital management level of the detection business,and provides strong support for the digital transformation of the industry. The application effect shows that the development and application of the system can provide an efficient, rigorous and standardized laboratory information management system for the metal mining industry. It is helpful to improve the digital management level of testing business and provide strong support for the digital transformation of the industry.

Key words: laboratory testing,LIMS,digitization,mining enterprise,intelligence mine