How do you maintain processing equipment? And how will you do it in the future?

从维护初级和辅助加工设备开始，保持塑料加工厂的每个元素运行是一个巨大的挑战。而且，我发现人们以不同的方式遇到了这一挑战。

你是怎么做到的？您的维护“风格”是什么？未来有什么影响？

‘运行'直到打破。’这种维护风格肯定是经过尝试和真实的，其优势是您不必在计划中做很多事情，直到出现问题并且您必须做出反应。然后，您必须拉出所有停靠点，拨打所有手，诊断问题，获取零件并开始工作。如果您可以快速进行修复，那么您是英雄，但是如果山羊的进展不顺利，则一只山羊，因为计划外的停机时间可能非常昂贵。希望您永远不会遇到“ 500年的维护问题”。

‘An ounce of prevention.’对于预防性维护风格来说，有很多话要说，因为它认识到常规的维护输入可以防止许多设备问题并支持更可靠的生产。但是，预防性维护的目标（例如定期吃蔬菜的目标）是要获得足够的有益，但不是太多，因为更多的是更好。实际上，提供比设备需求更多的预防性维护可能是浪费劳动力和物资的昂贵。因此，任何PM计划的秘诀是保留良好的设备维护记录，然后根据其测量的可靠性水平来衡量和平衡您应用于各种机械的常规维护输入水平。

'你感觉怎么样？'超越预防性的维护, there are a range of innovative predictive or condition-based maintenance approaches. These generally combine periodic equipment assessments with ongoing process and equipment monitoring and data collection, resulting in measures of the overall “health” of entire production processes or individual pieces of equipment. This proactive approach is very ambitious because it aims not just to reduce unexpected downtime, but to dramatically improve overall asset reliability, productivity, and profit.

这个想法是，通过监视设备或其组件零件，您可以避免使用不足或过度维护它。取而代之的是，通过“聆听”它说的话，您可以根据需要维护它，从而实现更大的可靠性和较低的长期维护成本。一个简单的例子：考虑使用枕头块轴承的传送带系统。PM方法说，无论是否需要，您的技术每周都会行走这条线，每次都有两次轴承。一种基于预测/条件的方法说，该技术会定期检查线条，检查压力或磨损的迹象，然后每隔几个月提供半泵的油脂。

但是，主要和辅助设备比轴承要复杂得多，对吗？因此，您可以使用技术检查它们，例如温度和振动传感器，电消耗，超声波泄漏检测，热特征，流量分析等。随着时间的推移收集的类似测量值可以标记设备状态的变化，突出显示可以快速固定和最低成本固定的早期维护问题。

That technology is available today. For example, you could create a maintenance program to monitor a key aspect of chiller performance – vibration – using either dedicated vibration sensors or sensors that work remotely through a tablet or phone. Through routine monitoring, or by setting a threshold level for a remote alarm, maintenance professionals could quickly identify excess vibration or other equipment problems and respond immediately. In this case, excess vibration caused by an out-of-balance fan could be identified and repaired well in advance of much more serious problems, such as cracked refrigerant lines on the chiller and diminished cooling capacity resulting in product quality problems.

So, what will the future bring? Innovations spurred by行业4.0将自动化越来越分享的过程和equipment measurement and data collection. Cloud-based analytics will receive and analyze machine data, identify possible problems, then report to maintenance personnel who can complete the diagnosis, prioritize maintenance for immediate completion, or schedule major maintenance during well-planned scheduled shutdowns. You may even enter a relationship with your equipment provider, in which they monitor your equipment using this cloud-based data, and provide predictive maintenance data and services to your maintenance team.

Today, it’s comparatively rare to find plastics processors whose maintenance operations achieve the “holy grail”: total annual maintenance costs less than or equal to 1.5% of Asset Replacement Value (RAV).* But that’s what top-quartile manufacturers do in many global industries. Think of it: running plant equipment with a replacement cost of $2 million for a total maintenance cost of about $30,000 per year—including people, supplies, everything. Can you do that? Would you like to?

*维护成本占替换资产价值（RAV）的百分比是维护和可靠性专业人员协会建立的比例，并由维护专业人员协会和许多世界领先的制造商使用。