摘要
石油化工生产在我国国民经济发展中具有重要的作用,但其工艺介质具有易燃、易爆、毒性的特点,一旦设备发生事故,不仅造成巨大的经济损失,而且还会影响到人身安全和环境,有时会造成无法估量的损失,甚至会给社会带来灾难性后果。所以采取有效的手段,预防事故的发生和提高设备的可靠性,对于石化企业意义重大。随着石化生产逐渐向大型化、复杂化和自动化方向发展,危险物质的数量和种类都在不断增加,因此对其生产设备的安全性、可靠性就提出愈来愈高的要求。设备维修是安全生产、提高产品质量和增加企业经济效益的重要保证。目前,石油化工企业维修成本占生产总成本的比例越来越高。因此,在确保安全和可靠的前提下,如何有效地降低维修成本,对维修进行有效地决策与优化,已经成为人们关注的焦点,也是目前迫切而且必须解决的问题。
与静设备相比,动设备一般故障率较高,为了保证整个生产系统的安全、平稳和可靠地运行,必须对动设备进行有效的维修管理,以确保石油化工企业的安全长周期运转。
本文在总结了各种先进的设备维修管理理念的基础上,对石化动设备维修决策方法进行了研究。具体研究内容主要包括以下几个方面:
(1)基于风险的动态智能维修系统的建立
运用先进的计算机技术、网络技术、数据库技术,利用系统工程方法,建立了基于风险的动态智能维修系统。在此系统中,通过基于风险的维修决策指导智能监/检测,同时把智能监/检测与动态风险评价相结合,根据设备状态监测与故障诊断结果确定出设备的动态风险等级,实施风险预警。随着设备状态的变化,维修计划不断更新和调整,从而形成一个动态闭环智能维修系统。
(2)石化动设备重要度评价方法研究
设备重要度评价是维修资源合理分配的重要依据,把故障模式和影响分析方法引入设备重要度评价,并且针对设备重要度评价过程中的模糊性、不确定性和多因素的特点,建立了基于模糊综合评价方法的设备重要度评价模型。由于基于误差反向传播(BP:Back—propagation)算法的人工神经网具有很强的学习能力而且结构简单,把模糊综合评价方法与神经网络技术相结合。实例分析表明,该模型能够真实地反映出设备在生产中所处的地位,而且实现了设备重要度的智能评价。
(3)石化动设备视情维修周期优化研究
目前,视情维修对石化动设备是一种有效的维修方式。视情维修的成本是设备寿命周期费用的重要组成部分,因此,降低视情维修成本是维修管理追求的一个主要目标。在本研究中建立了视情维修成本优化模型。在模型中,首先提出了视情维修应用的判别条件,然后以单位时间内维修成本最低为目标,把潜在故障与功能故障之间的时间间隔引入维修成本优化模型中,针对故障发生的随机性,开发了蒙特卡罗计算机优化仿真流程。以一台离心泵为分析实例,结果表明:与优化前相比,可节省维修费用14,327元/年,取得明显的经济效益。
(4)基于风险的石化动设备维修决策方法研究、软件开发及工程应用
引入了风险评价理论,对石化动设备的维修决策过程进行了研究。建立了适合石化动设备的风险评价准则和基于风险的维修决策方法。以故障根本原因分析为依据,提出故障根治维修措施。
依据基于风险的石化动设备维修决策的研究成果,开发了计算机辅助分析软件。结果表明,与传统的人工决策方式相比,该软件实现了维修分析决策过程的规范化和流程化,大大提高了维修决策的效率和有效性。
将基于风险的石化动设备维修决策方法在中石化某乙烯厂进行了工程应用。对乙烯装置141台动设备先后进行了故障模式分析、风险评价和根本原因分析,共得到549种故障模式,高风险故障模式有67个,占12%。依据基于风险的维修决策流程,提出根治维修和状态监/检测建议。应用结果表明,该方法对企业的维修资源进行了合理的分配,充分考虑了生产的安全性与经济性,提高了维修的效益。
The petrochemical industry plays an important role in national economic development. However, its process media are inflammable, explosive and toxic. Therefore, the failure of equipment may cause great economic losses. Furthermore, it may lead to serious personnel injury even death and environment pollution. And social disaster will be a nightmare. So it is of great significance for petrochemical industry to take effective measurements to prevent failures and improve the reliability of equipment. With the production trend of large-scale, complication and automation, dangerous media keep increasing both in species and quantity. Hence, it requires stringent regulations on equipment safety and reliability. Maintenance is extremely essential for ensuring the equipment to keep running safely, improving product quality and increasing economic benefits of plants. Nowadays, the maintenance cost takes a great proportion of the total production cost. How to reduce it and how to effectively make decisions and optimize maintenance have caused great concerns. It is an urgent problem to be solved.
Compared with static equipment, the failure rate of rotating machinery is generally higher. In order to ensure process safety, stability and reliability, modern industry requires effective maintenance management in rotating machinery so that the safe and long-life running of the petrochemical plant can be achieved.
Based on the kinds of advanced equipment maintenance management concepts, our particular focus is on maintenance decision-making for petrochemical rotating machinery. The studies in this dissertation include following parts.
(1) Establishment of a dynamic risk-based intelligent maintenance system
A dynamic risk-based intelligent maintenance system (RBIMS) was established by using the advanced information science technology, and systems engineering methods. The maintenance decision-making is taken as a guidance of condition monitoring / inspection and monitoring / inspection has been integrated with dynamic risk assessment. Based on the results of condition monitoring and fault diagnosis, the equipment dynamics risk level is determined, and the risk early-warning is carried out. With the changes in equipment condition, the plans are keeping updating and adjusting. In this way, a dynamic closed-loop maintenance system is achieved.
(2) Research on criticality evaluation method for petrochemical rotating machinery
Equipment criticality evaluation is an important foundation for reasonable maintenance resources allocation. Aiming at the uncertainty, fuzzy and multivariable of the evaluation factors, an equipment criticality evaluation model based on fuzzy comprehensive evaluation is set up. Benefit from the strong learning ability and simple structure of BP neural network, a fuzzy comprehensive evaluation model with BP neural network is established. The result of case study shows that this model not only truly represents the equipment importance in the whole production process, but also realizes intelligent evaluation of the equipment criticality.
(3) On Condition Maintenance (OCM) optimization study of petrochemical rotating machinery
Presently, OCM is an effective predictive method for maintaining petrochemical rotating machinery. Its cost is an important part in the equipment life cycle cost. Therefore, to reduce OCM cost is an important mission in maintenance management. In this study, an OCM cost optimization model is established. First, the judgment conditions are considered as a necessary criterion of the OCM feasibility. Moreover, in order to minimize maintenance costs per unit time, the concept that there must be an interval between the potential failure point (P) and the functional failure point (F) was introduced into the optimization model of OCM. Considering the randomness, a Monte Carlo simulation program for optimizing monitoring period was developed. Finally, an optimization study case on centrifugal pump shows that compared with the existing monitoring plan, the maintenance costs saved 14,327 RMB/year. The economic benefit is obvious.
(4) Study on risk-based maintenance decision-making for rotating machinery, development of analysis software and engineering application
With the introduction of risk assessment theory, the maintenance decision-making process of rotating machinery was studied. The risk assessment criteria are set up, which is suitable for petrochemical rotating machinery in China. The method of risk-based maintenance decision-making is established. On the basis of failure root cause analysis, radical maintenance has been proposed.
Based on the research results of risk-based maintenance decision-making for rotating machinery, computer-aided analysis software has been developed. Compared with traditional manual decision-making methods, the results show that the normalization and ordering analysis of maintenance decision-making process can be achieved and this software takes advantages in efficiency and effectiveness.
The risk-based maintenance decision-making method for rotating machinery has been applied in a SINOPEC ethylene plant. Failure mode analysis, risk assessment and root cause analysis had been carried out for 141 rotating machinery. 549 failure modes were obtained, including 67 high risk models (12%). Then, according to the process of maintenance decision-making, the radical maintenance and condition monitoring / inspection recommendations were proposed. The results of engineering application shows that this method could realize reasonable allocation of maintenance resources, highly consider the safety and economy, improve maintenance benefits.
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