Case Study: How Digital Transformation Paved the Way for One Refinery's Predictive Maintenance Strategy

Peter Zornio, Mike Boudreaux
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引用次数: 2

Abstract

Across the energy industry, leading companies are eager to embrace digital innovation and all the predictive benefits it offers. Yet some of the largest companies still rely on sporadic, manual inspections to ensure the smooth operation of their machinery, equipment, instrumentation and systems. One international oil and gas company realized even the most skilled plant technicians could miss certain warning signals. If equipment like heat exchangers, pumps or critical valves are checked only periodically, manufacturers can risk equipment failure, outages or worse — health and safety incidents. Thanks to advancements in the quality and affordability of sensors as well as wireless technologies and cloud-based applications to gather and analyze data being streamed from devices in the field, companies like this one can gain better insights from equipment and take proactive measures to prevent failures and plant shutdowns. The company worked with third-party technology vendors to implement a predictive reliability and maintenance program that will save millions of dollars a year in operational costs by instrumenting and monitoring heat exchangers in one of the company's refineries. The program is designed to digitally transform the company's heat exchanger maintenance activities and free refinery personnel from laborious manual monitoring, enabling them to focus on other functions and operational needs. A typical refinery will have 200-400 heat exchangers, the majority of which are manually monitored, with months passing between inspections. If undetected, heat exchanger fouling can cause degraded performance, reduced energy efficiency, process slowdowns and unscheduled shutdowns. Installation of more sensors to drive plant monitoring applications is an option, but the cost and disruption of installing new, conventional wired temperature sensors to an existing facility is prohibitive. One of the vendors developed and installed unique cost-effective sensors to provide accurate measurements from the refinery's heat exchangers without thermowell process penetration. These sensors allow for remote monitoring of heat exchanger data in real time. As part of the ongoing program, the data is transmitted through a secure, wireless architecture and transferred to the cloud using cloud-computing technologies. Using advanced analytics, the data is then interpreted to provide plant personnel with actionable data to optimize operational performance. There have been significant savings in sensor installation (a fraction of the cost of conventional sensors) and commissioning time (one week versus the typical six weeks). The plant has also seen savings in staff time. The company can detect small variations well before any fouling issues start. The program is proving that, by understanding the health of the heat exchangers, the company can help prevent unplanned outages and reduce the number of scheduled repairs. Facilities can reduce energy and capacity loss due to fouling by up to 10 percent. For a 250,000-barrel-a-day refinery, that could translate to a savings of as much as $3.5 million or more annually. Wireless sensors and secure, cloud-based condition monitoring can be expanded to other equipment, such as pumps and cooling towers throughout the plant. Ultimately, these predictive maintenance programs will improve and transform operations, and the data analytics and insights will accelerate business decisions. Cloud-based hosting of these monitoring systems allow monitoring by any personnel, anywhere, including the option of having a third-party vendor provide the service.
案例研究:数字化转型如何为一家炼油厂的预测性维护策略铺平道路
在整个能源行业,领先的公司都渴望拥抱数字创新及其提供的所有可预测的好处。然而,一些最大的公司仍然依靠零星的人工检查来确保其机器、设备、仪器和系统的顺利运行。一家国际石油和天然气公司意识到,即使是最熟练的工厂技术人员也可能错过某些警告信号。如果只是定期检查热交换器、泵或关键阀门等设备,制造商可能会冒设备故障、停机或更糟的健康和安全事故的风险。由于传感器的质量和价格的提高,以及无线技术和基于云的应用程序可以收集和分析从现场设备传输的数据,这样的公司可以从设备中获得更好的见解,并采取主动措施防止故障和工厂关闭。该公司与第三方技术供应商合作,实施了一项预测可靠性和维护计划,通过对该公司一家炼油厂的热交换器进行仪器和监控,每年将节省数百万美元的运营成本。该计划旨在对公司的热交换器维护活动进行数字化改造,并将炼油厂人员从繁重的人工监控中解放出来,使他们能够专注于其他功能和运营需求。一个典型的炼油厂将有200-400个热交换器,其中大部分是人工监控的,检查间隔数月。如果未被发现,热交换器结垢会导致性能下降、能源效率降低、过程减速和计划外停机。安装更多的传感器来驱动工厂监控应用是一种选择,但在现有设施上安装新的传统有线温度传感器的成本和中断令人望而却步。其中一家供应商开发并安装了独特的具有成本效益的传感器,以提供来自炼油厂热交换器的精确测量,而无需穿透热电偶过程。这些传感器允许对热交换器数据进行实时远程监控。作为正在进行的项目的一部分,数据通过安全的无线架构传输,并使用云计算技术传输到云端。利用先进的分析技术,这些数据将被解释,为工厂人员提供可操作的数据,以优化运营绩效。在传感器安装(传统传感器成本的一小部分)和调试时间(一周,而不是典型的六周)方面有很大的节省。工厂还节省了员工的时间。该公司可以在任何污染问题开始之前检测到微小的变化。该项目证明,通过了解热交换器的健康状况,该公司可以帮助防止计划外停机,减少定期维修的次数。设施可以将因污染造成的能源和容量损失减少10%。对于一家日产量为25万桶的炼油厂来说,这意味着每年可节省多达350万美元或更多。无线传感器和安全的基于云的状态监测可以扩展到其他设备,如整个工厂的泵和冷却塔。最终,这些预测性维护程序将改善和改变运营,数据分析和洞察将加速业务决策。这些监控系统的云托管允许任何人员在任何地方进行监控,包括让第三方供应商提供服务的选项。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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