• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (24): 168-177.

• 论文 • 上一篇    

过程工业设备维修智能决策系统的开发与应用

王庆锋;杨剑锋;刘文彬;袁庆斌;马宏伟   

  1. 北京化工大学化工安全教育部工程研究中心;中国石油锦州石化公司;中国石油四川石化有限责任公司
  • 发布日期:2010-12-20

WANG Qingfeng YANG Jianfeng LIU Wenbin YUAN Qingbin MA Hongwei

WANG Qingfeng;YANG Jianfeng;LIU Wenbin;YUAN Qingbin;MA Hongwei   

  1. Chemical Safety Engineering Research Center of Ministry of Education, Beijing University of Chemical Technology PetroChina Jinzhou Petrochemical Company PetroChina Sichuan Petrochemical Co., Ltd.
  • Published:2010-12-20

摘要: 中国石化过程工业设备管理基本属于传统的事后维修模式,设备基础管理薄弱,依靠经验的、定性的方法确定设备检查/维护内容,缺乏对关键设备的识别和分类 ,维修资源不能合理分配,存在“维修不足”和“维修过剩”,系统安全生产隐患大、事故多,设备可靠性、可用性和安全性难以控制和保证。为保证过程工业安全生产,减少安全事故和环境事故,建立了过程工业设备维修智能决策信息系统,它以设备完整性管理系统为架构,综合集成了企业资源计划系统(Enterprise resource planning, ERP)、企业生产执行系统(Manufacturing executive system, MES)和基于风险的检测(Risk-based inspection,RBI)、以可靠性为中心的维修(Reliability-centered maintenance, RCM)、安全完整性水平分析(Safety integrity level, SIL)等风险评估系统与预知维修信息系统(Predictive maintenance information systems, PMIS),为企业提供设备动态风险等级数据、预知维修信息数据和设备绩效指标数据,使各级人员能够通过网络平台及时准确地掌握设备风险状态和优化的维修任务排程,为设备维修决策提供科学支持。实践结果表明:建立的设备维修智能决策信息系统对于提高设备可靠性、可用性和安全性产生了积极效果,它使设备故障频率降低、故障后果减小,维修资源得到了合理利用;高层领导和工程师的强力支持、针对员工的系统教育培训是智能维修决策系统成功应用的重要保证。

关键词: 过程工业, 可靠性, 可维修性, 可用性, 完整性管理, 预知维修

Abstract: Equipment management in Chinese petrochemical process industry basically belongs to the traditional breakdown maintenance pattern, and the basic inspection/maintenance decision-making is subjective and qualitative. Equipment inspection/maintenance tasks are mainly based on the empirical or qualitative method, and it lacks identification and classification of critical equipment, so that maintenance resources cant be reasonably allocated. Reliability, availability and safety of equipment are difficult to control and guarantee due to the existing maintenance deficiencies, maintenance surplus, potential danger and possible accidents. In order to ensure stable production and reduce operation cost, intelligent maintenance decision-making system(IMD) is established, which integrates enterprise resource planning(ERP), manufacturing executive system(MES), risk-based inspection(RBI), reliability-centered maintenance(RCM), safety integrity level(SIL), predictive maintenance information systems (PMIS), distributed control system(DCS) and other process data together. IMD can provide dynamic risk rank data, predictive maintenance data and equipment operation performance indicator decision-making data, through which the personnel at all levels can grasp the risk state of equipment timely and accurately and optimize maintenance schedules to support the decision-making. The result of an engineering case shows that the system can improve reliability, availability, and safety, lower failure frequency, decrease failure consequences and make full use of maintenance resources, thus achieving the reasonable and positive result. Experiences show that the key factors affecting the successful transition to an IMD informed approach include firm support from both the manager and the engineers as well as education and training for engineers, operators and maintenance staffs.

Key words: Availability, Integrity management, Maintainability, Predictive maintenance, Process industry, Reliability

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