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应用统计过程控制图监测动物生产系统的变化。

Application of statistical process control charts to monitor changes in animal production systems.

机构信息

Department of Animal Sciences, University of Florida, Gainesville, FL 32611, USA.

出版信息

J Anim Sci. 2010 Apr;88(13 Suppl):E11-24. doi: 10.2527/jas.2009-2622. Epub 2010 Jan 15.

Abstract

Statistical process control (SPC) is a method of monitoring, controlling, and improving a process through statistical analysis. An important SPC tool is the control chart, which can be used to detect changes in production processes, including animal production systems, with a statistical level of confidence. This paper introduces the philosophy and types of control charts, design and performance issues, and provides a review of control chart applications in animal production systems found in the literature from 1977 to 2009. Primarily Shewhart and cumulative sum control charts have been described in animal production systems, with examples found in poultry, swine, dairy, and beef production systems. Examples include monitoring of growth, disease incidence, water intake, milk production, and reproductive performance. Most applications describe charting outcome variables, but more examples of control charts applied to input variables are needed, such as compliance to protocols, feeding practice, diet composition, and environmental factors. Common challenges for applications in animal production systems are the identification of the best statistical model for the common cause variability, grouping of data, selection of type of control chart, the cost of false alarms and lack of signals, and difficulty identifying the special causes when a change is signaled. Nevertheless, carefully constructed control charts are powerful methods to monitor animal production systems. Control charts might also supplement randomized controlled trials.

摘要

统计过程控制(SPC)是一种通过统计分析来监测、控制和改进过程的方法。SPC 的一个重要工具是控制图,它可用于检测生产过程的变化,包括具有统计置信水平的动物生产系统。本文介绍了控制图的原理和类型、设计和性能问题,并回顾了 1977 年至 2009 年文献中控制图在动物生产系统中的应用。主要介绍了 Shewhart 和累积和控制图在动物生产系统中的应用,在禽类、猪、奶牛和肉牛生产系统中都有应用实例。这些实例包括生长、疾病发生率、水摄入量、牛奶产量和繁殖性能的监测。大多数应用都描述了图表的结果变量,但需要更多应用于输入变量的控制图实例,例如遵守协议、饲养实践、饮食组成和环境因素。在动物生产系统中应用的常见挑战是确定常见原因变异的最佳统计模型、数据分组、控制图类型的选择、误报警和缺乏信号的成本,以及在发出变化信号时识别特殊原因的困难。然而,精心构建的控制图是监测动物生产系统的强大方法。控制图也可以补充随机对照试验。

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