mean time between failures

简明释义

平均无故障时间

英英释义

例句

1.To minimize downtime, we need to monitor the mean time between failures 故障平均间隔时间 closely.

为了最小化停机时间，我们需要密切监控故障平均间隔时间。

2.The engineering team calculated the mean time between failures 故障平均间隔时间 for the new software to ensure its reliability.

工程团队计算了新软件的故障平均间隔时间，以确保其可靠性。

3.A higher mean time between failures 故障平均间隔时间 indicates a more dependable system.

更高的故障平均间隔时间表明系统更可靠。

4.During the meeting, we discussed ways to improve the mean time between failures 故障平均间隔时间 of our production line.

在会议中，我们讨论了改善生产线的故障平均间隔时间的方法。

5.The IT department reported that the mean time between failures 故障平均间隔时间 for the servers had increased significantly over the past year.

IT部门报告称，过去一年服务器的故障平均间隔时间显著增加。

作文

In the world of engineering and technology, reliability is a paramount concern. One of the key metrics used to assess the reliability of a system is the concept of mean time between failures. This term refers to the average time that elapses between one failure of a system and the next. Understanding this metric is crucial for engineers and managers alike as it helps them gauge the performance and dependability of their systems. The mean time between failures (MTBF) is often used in various industries, including manufacturing, aerospace, and information technology.The significance of mean time between failures lies in its ability to provide insights into how often a system is likely to fail during operation. A higher MTBF indicates that a system is more reliable, while a lower MTBF suggests that failures are more frequent. For instance, in the field of computer systems, an MTBF of several thousand hours means that the system can be expected to run for a long time before any issues arise. This information is invaluable for businesses that rely on these systems to operate efficiently and effectively.Calculating the mean time between failures involves tracking the operational time and the number of failures that occur within a given period. The formula for MTBF is relatively straightforward: it is the total operational time divided by the number of failures. For example, if a machine operates for 10,000 hours and experiences two failures during that time, the MTBF would be 5,000 hours. This calculation helps organizations identify potential weaknesses in their systems and take proactive measures to enhance reliability.Furthermore, the mean time between failures can influence maintenance strategies. If an organization knows the MTBF of its equipment, it can schedule maintenance activities more effectively. By performing maintenance just before a predicted failure, companies can minimize downtime and reduce costs associated with unexpected breakdowns. This predictive approach not only saves money but also improves overall productivity.In addition to its practical applications, the mean time between failures serves as a benchmark for comparing different systems or products. When evaluating multiple options, businesses can use MTBF to make informed decisions about which equipment to invest in. A product with a significantly higher MTBF may be worth the extra cost, as it could lead to lower long-term operational expenses and increased efficiency.However, it is essential to recognize that the mean time between failures is not the only indicator of a system's reliability. Other factors, such as the severity of failures and the impact on operations, must also be considered. A system with a high MTBF might still experience catastrophic failures that could halt production or compromise safety. Therefore, while MTBF is a valuable metric, it should be used in conjunction with other reliability assessments to gain a comprehensive understanding of a system's performance.In conclusion, the mean time between failures is a critical metric in the realm of engineering and technology. It provides valuable insights into the reliability of systems, informs maintenance strategies, and aids in decision-making processes. By understanding and utilizing MTBF, organizations can enhance their operational efficiency and reduce costs associated with equipment failures. As technology continues to evolve, the importance of reliability metrics like MTBF will only grow, making it essential for professionals in the field to master this concept and apply it effectively in their work.

在工程和技术的世界中，可靠性是一个至关重要的关注点。用于评估系统可靠性的关键指标之一是平均故障间隔时间（mean time between failures）的概念。这个术语指的是系统发生一次故障与下一次故障之间的平均时间。理解这一指标对工程师和管理者来说至关重要，因为它帮助他们评估系统的性能和可靠性。平均故障间隔时间（MTBF）通常在制造业、航空航天和信息技术等多个行业中使用。平均故障间隔时间的重要性在于它能够提供有关系统在运行过程中可能发生故障的频率的洞察。较高的MTBF表明系统更可靠，而较低的MTBF则表明故障更频繁。例如，在计算机系统领域，几千小时的MTBF意味着系统可以预期在出现任何问题之前运行很长时间。这些信息对于依赖这些系统高效有效运作的企业来说是非常宝贵的。计算平均故障间隔时间涉及跟踪操作时间和在给定时间内发生的故障数量。MTBF的计算公式相对简单：它是总操作时间除以故障次数。例如，如果一台机器运行了10,000小时，并在此期间经历了两次故障，那么MTBF将为5,000小时。这个计算帮助组织识别其系统中的潜在弱点，并采取主动措施提高可靠性。此外，平均故障间隔时间还可以影响维护策略。如果组织知道其设备的MTBF，就可以更有效地安排维护活动。通过在预测故障之前进行维护，公司可以最大限度地减少停机时间，并降低与意外故障相关的成本。这种预测性的方法不仅节省了资金，还提高了整体生产力。除了实际应用之外，平均故障间隔时间还作为比较不同系统或产品的基准。当评估多个选项时，企业可以使用MTBF做出关于投资哪个设备的明智决策。具有显著更高MTBF的产品可能值得额外的成本，因为它可以导致较低的长期运营费用和更高的效率。然而，必须认识到，平均故障间隔时间并不是唯一的系统可靠性指标。其他因素，如故障的严重性和对操作的影响，也必须考虑在内。一个MTBF高的系统仍然可能经历灾难性故障，这可能会停止生产或危及安全。因此，尽管MTBF是一个有价值的指标，但它应该与其他可靠性评估结合使用，以全面了解系统的性能。总之，平均故障间隔时间是工程和技术领域中的一个关键指标。它提供了有关系统可靠性的宝贵洞察，告知维护策略，并帮助决策过程。通过理解和利用MTBF，组织可以提高其运营效率并降低与设备故障相关的成本。随着技术的不断发展，像MTBF这样的可靠性指标的重要性只会增加，因此该领域的专业人士掌握这一概念并有效应用它将变得至关重要。