mean time between defects

简明释义

欠缺之间平均时间

英英释义

例句

1.The software development team aims to increase the mean time between defects by implementing better testing protocols.

软件开发团队旨在通过实施更好的测试协议来增加缺陷平均发生时间。

2.Monitoring the mean time between defects helps us maintain high-quality standards.

监控缺陷平均发生时间有助于我们维持高质量标准。

3.By analyzing the mean time between defects, we can identify areas for process improvement.

通过分析缺陷平均发生时间，我们可以识别出流程改进的领域。

4.The engineering team focused on improving the mean time between defects to enhance product reliability.

工程团队专注于提高缺陷平均发生时间以增强产品可靠性。

5.A lower mean time between defects indicates a more stable production line.

较低的缺陷平均发生时间表明生产线更稳定。

作文

In the world of quality assurance and software development, the term mean time between defects plays a crucial role in measuring the reliability and performance of a system. This metric, often abbreviated as MTBD, helps organizations understand how frequently defects occur in their products or services. By calculating the average time that elapses between one defect and the next, companies can identify patterns, assess risks, and ultimately improve their processes.The importance of mean time between defects cannot be overstated. For instance, in a software development environment, a high MTBD indicates that the team is successfully delivering quality code with fewer bugs. This not only enhances user satisfaction but also reduces the cost associated with fixing defects after deployment. On the other hand, a low MTBD may signal underlying issues in the development process, such as inadequate testing, rushed releases, or lack of proper documentation.To calculate the mean time between defects, organizations typically track the total operational time and divide it by the number of defects that occur within that timeframe. For example, if a software application runs for 1,000 hours and encounters 10 defects, the MTBD would be 100 hours. This simple calculation provides valuable insights into the health of the software product and guides teams in making informed decisions about future releases.Moreover, understanding the mean time between defects can help teams prioritize their efforts in quality assurance. By analyzing historical data, teams can focus on areas that are prone to defects and allocate resources more effectively. For example, if a particular module of the software consistently shows a lower MTBD, it may require more rigorous testing or even a redesign to improve its stability.In addition to software development, the concept of mean time between defects is applicable in various industries, including manufacturing and service delivery. In manufacturing, for instance, a company may track the MTBD in relation to production defects to enhance quality control measures. A longer MTBD indicates a more reliable production process, which can lead to higher customer satisfaction and reduced warranty claims.Furthermore, the mean time between defects can serve as a benchmark for continuous improvement. Organizations can set goals to increase their MTBD over time, fostering a culture of quality and accountability. By regularly reviewing and analyzing their MTBD, teams can celebrate improvements and identify areas needing further attention.In conclusion, the mean time between defects is a vital metric for any organization focused on delivering high-quality products and services. It provides a clear picture of reliability and helps teams make data-driven decisions to enhance their processes. As businesses strive for excellence in an increasingly competitive landscape, understanding and leveraging the MTBD will undoubtedly contribute to their success. By prioritizing quality and aiming for a higher MTBD, organizations can ensure that they meet customer expectations and maintain their reputation in the market.

在质量保证和软件开发的领域中，术语缺陷平均发生时间在衡量系统的可靠性和性能方面发挥着至关重要的作用。这个指标，通常缩写为MTBD，帮助组织理解其产品或服务中缺陷发生的频率。通过计算一个缺陷与下一个缺陷之间的平均时间，企业可以识别模式、评估风险，并最终改善他们的流程。缺陷平均发生时间的重要性不容小觑。例如，在软件开发环境中，高MTBD表明团队成功地交付了质量较高的代码，缺陷较少。这不仅提高了用户满意度，还减少了发布后修复缺陷所需的成本。相反，低MTBD可能表明开发过程中存在潜在问题，例如测试不足、发布匆忙或缺乏适当的文档。为了计算缺陷平均发生时间，组织通常跟踪总操作时间，并将其除以在该时间范围内发生的缺陷数量。例如，如果一个软件应用程序运行了1000小时并遇到10个缺陷，则MTBD将为100小时。这个简单的计算提供了有关软件产品健康状况的宝贵见解，并指导团队在未来的发布中做出明智的决策。此外，了解缺陷平均发生时间可以帮助团队优先考虑质量保证方面的工作。通过分析历史数据，团队可以集中精力在容易出现缺陷的领域，更有效地分配资源。例如，如果软件的某个模块持续显示较低的MTBD，可能需要进行更严格的测试甚至重新设计以提高其稳定性。除了软件开发，缺陷平均发生时间的概念还适用于各个行业，包括制造业和服务交付。在制造业中，例如，一家公司可能会跟踪与生产缺陷相关的MTBD，以增强质量控制措施。较长的MTBD表明生产过程更可靠，这可以带来更高的客户满意度和减少保修索赔。此外，缺陷平均发生时间还可以作为持续改进的基准。组织可以设定目标，以随着时间的推移提高其MTBD，从而培养一种质量和责任感的文化。通过定期审查和分析他们的MTBD，团队可以庆祝改进并识别需要进一步关注的领域。总之，缺陷平均发生时间是任何专注于提供高质量产品和服务的组织的重要指标。它提供了可靠性的清晰图景，并帮助团队做出基于数据的决策，以改善他们的流程。随着企业在日益竞争的环境中追求卓越，理解和利用MTBD无疑将有助于他们的成功。通过优先考虑质量并努力提高MTBD，组织可以确保满足客户期望并维护其在市场上的声誉。