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PERFORMANCE INDEX (PI) HOW TO ANALYZE AND IMPROVE PACKAGING LINE PERFORMANCE

机译:性能指标(PI)如何分析和改善包装线性能

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Most companies that are involved with automated packaging systems, monitor their output in either "cases per day" or "hectoliters per shift" or some other suitable output figure. "Case Counts" is a good bottom line measure considering the typical requirements of upper management. If the case count drops, it's time for upper management to ensure that appropriate action is taken to correct matters. All too often though, they send messages to middle management to "Get More Cases Out Of The Line Any Way You Can" ! This message is heard loud and clear through the ranks, through middle management, supervisors, operators and the maintenance team. Everyone's world revolves around the case counts. The problem with this type of direction is that it is often accompanied by little or no other information about how to analyze the packaging line and where to begin looking for the fault. Inevitably different parties start chopping at each and every visually apparent symptom. If by chance, the real problem is not stumbled upon, then this is typically followed by a more structured Downtime Analysis study and closely monitoring machine efficiencies. Downtime Analysis is undoubtedly effective but has its limitations as we will see later on . There just has to be a smarter system and one which is easy to apply and does not require additional time to use. This is why the "Performance Index" or "PI" has been developed. The philosophy behind "PI" is to help the packaging manager break down the lower case counts into general problem areas, then further into real individual causes and potential solutions. These can then be formed into an action plan, which when properly executed, will alter the case count in a positive manner. Coupled with PI are newer, more advanced analysis techniques that can be used together with Downtime Analysis, to help find the real causes of the problem areas and are very useful in line utilization improvement programs. It is, however, essential that PI be generally understood at the highest possible levels of management in order to affect lower case counts in a positive manner.
机译:涉及自动包装系统的大多数公司都以“每天的情况”或“每班百公升”或其他一些合适的输出数字来监视其输出。考虑到高层管理人员的典型要求,“案例计数”是一个很好的底线度量。如果案件数量下降,则是高层管理人员确保采取适当措施纠正问题的时候了。但是,他们经常将消息发送给中层管理人员,以“尽你所能”处理更多案件。通过高层,中层管理人员,主管,操作人员和维护团队,这些消息被清晰而清晰地听到。每个人的世界都围绕着案件数。这种方向的问题在于,它通常伴随着很少或没有其他信息,如关于如何分析包装线以及从何处开始寻找故障的信息。不可避免地,不同的参与者开始砍伐每一个视觉上明显的症状。如果偶然发现了真正的问题,那么通常会进行更结构化的“停机时间分析”研究并密切监视机器效率。停机时间分析无疑是有效的,但它也有其局限性,我们将在下文中看到。只是必须有一个更智能的系统,而这是一个易于应用且不需要额外时间使用的系统。这就是为什么要开发“性能指数”或“ PI”的原因。 “ PI”背后的理念是帮助包装经理将小写字母分解为一般问题区域,然后进一步分解为实际的个人原因和潜在的解决方案。然后可以将其形成一个行动计划,该计划一旦得到适当执行,将以积极的方式改变案件数量。与PI结合使用的是较新的,更高级的分析技术,可以将它们与停机时间分析一起使用,以帮助找到问题区域的真正原因,并且在生产线利用率改善计划中非常有用。但是,至关重要的是,必须在最高可能的管理级别上理解PI,以便以积极的方式影响小写数量。

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