Unexpected down time reduces manufacturing plant productivity and can be costly. Machine reliability is key to consistent productivity and plant up time and predicting machine failures is the best way to keep maintenance cost and unpredictable down times in check. Every single day, in every manufacturing environment, failures and downtime happen. That’s just a reality when you’re dealing with equipment that perform a repetitive task. The issue however is that manufacturing in today’s markets requires efficiency and quality production. Unplanned downtime in just one machine, in a ‘just-in-time’ manufacturing environment, can cause delays that lead to unhappy customers, possible attrition of those customers to a competitor and a direct hit to a company’s bottom line.
What is Predictive Maintenance?
Predictive maintenance is a technique to predict the future failure point of a machine component, so that the component can be replaced, based on a plan, just before it fails. Thus, equipment downtime is minimized and the component lifetime is maximized. It can also be defined as a method of preventing asset failure by analyzing production data to identify patterns and predict issues before they happen.
The ultimate goal of the maintenance technician in a manufacturing company is to keep production going by limiting downtime as much as possible. Today there are a series of technologies that constantly monitor the state of the machines in order to support the maintenance technician. The collected data are usually shown on dedicated panels, which the maintenance technician must be able to use and interpret. The task is not always simple but the reward makes the effort worthwhile. So, what are the benefits of this approach? Let’s look at some of them.
Benefits of Predictive Maintenance
1. Downtime reduction
This is the best benefit of a predictive maintenance: the lower the chances of a machine failing during processing, the lower the downtime will occur. The advantages of this result are obvious. On the one hand it saves time and money, on the other, it will be easier to avoid delays in deliveries and also prevent customer dissatisfaction.
2. 360-degree visibility
Collecting data to implement a predictive maintenance program is an important step to gain complete visibility into the process. Through technological tools, it will be possible to know in real time the state of the machinery by all the people involved, from the operator to the production manager.
In particular, we are talking about three different types of data:
Environmental data such as temperature, humidity, frequency of vibrations, etc.
Historical data, such as failures that occurred and the maintenance operations performed.
Operational data such as, the utilization rate of the plants.
3. Optimize resources
Reducing waste in this case means not only reducing production waste due to malfunctioning but also lengthening the average life of important production system components: carrying on maintenance before a critical situation leads to less stress on the systems.
4. Data-driven culture and continuous improvement
To conclude, a preventive maintenance approach, aided by the digitization of production processes, that is the possibility of collecting factory data in real time and storing them correctly, allows to know the problems of machinery and to avoid downtime. This makes for a seamless manufacturing process and keeps production level high all the time.
Keeping up with trends is not always easy in a factory, but knowing how to build a long-term strategy is necessary to stay competitive in the market. A Preventive maintenance approach equips you with data that can be improved upon, and this when properly implemented will keep you competitive all the time.
