3 Metrics You Need to Know About Predictive Maintenance
Updated: Nov 16, 2020
Downtime has been cited as one of the major issues most manufacturers struggle to reduce. To some extent, it is inevitable. Every factory loses at least 5% of its productivity to downtime, but that number can be as high as 20% when a proper response is not taken.
Minimizing this type of waste is critical to any industry, particularly food manufacturing. Below, we investigate the types of downtime that food manufacturers face, the responses taken to mitigate losses, and how using data-driven tracking of Overall Equipment Effectiveness helps control lost time.
In Search of Lost Time: Planned and Unplanned Downtime
Think of time the same way that you might think of a material, an employee, or a budget. While it is more abstract than other aspects of managing a factory, it is finite and can be measured. As a result, it can be wasted in the same way that excess materials can be spent, employees mismanaged, or money directed inappropriately. Time is a type of waste.
It is impossible to reduce downtime to zero, but in a manufacturing setting the objective should be to bring downtime as low as possible. This can be determined by examining the two types of downtime that manufacturers face.
· Planned Downtime – Maintenance, cleaning, minor adjustments, product changeover – planned downtime is any planned activity that is necessary to keep production running and product volume high. In food manufacturing, planned downtime is particularly important to meet food safety standards for consumers.
· Unplanned Downtime – Machine jams, breakdowns, accidents – unplanned downtime hits when you least expect it, and can have devastating effects on day-to-day operations.
The solution to downtime? Knowing that you have a problem before it becomes a problem. Whether planned or unplanned, the best solution to mitigating losses in downtime is through data collection
Expecting the Unexpected
A Vanson Bourne Research Study recently concluded that 82% of companies experienced an average of two outages over the course of three years, costing each company roughly $2 million in total. This is largely attributed to companies not knowing when their machines require maintenance.
Reactive downtime is the response to unplanned downtime as it unfolds. Production halts as a problem is solved, and costs accrue not only in maintenance, but in lost time. A better approach comes with predictive downtime.
Predictive downtime calculates issues before they become a problem by planning responses to issues before they metastasize.
As a practice, predictive downtime has been calculated to reduce downtime costs by around 40%. But what is predictive maintenance, and how can I implement it into my manufacturing line?
Predictive Maintenance and Overall Equipment Effectiveness
Overall Equipment Effectiveness, or OEE, is the sum of factors that stack against your manufacturing line from working at peak efficiency. It factors in several factors to identify constraints that can be fixed in the production line:
· Availability loss – Planned and unplanned downtime
· Performance loss – Inefficiencies in the production line
· Quality loss – Product defects and losses in yield
By multiplying these variables together, a percentage of effectiveness emerges.
Many tools exist on the market to gather this information on your machines and workflow, with Redzone being one of the most popular options for those in food manufacturing.
The granularity of this data allows manufacturers to see exactly what parts of their work flow need to be optimized so that they can take action. One of the major issues that manufacturers face, for instance, is knowing when machines need maintenance. OEE tools are able to track this information in real time, allowing these companies to implement predictive maintenance on machines that need repair or replacement.
But the benefits do not end there. Integrated food safety and quality management can be visualized into key metrics. These same tools can help illustrate where blockages are forming on the production line, which can be extremely useful for learning where to install automated machine tools to reduce inefficiencies.
Automated Machines and Overall Equipment Effectiveness
Maximizing your OEE depends on finding the damaged or broken links in your production chain and fixing them. Automated machines in food production target performance and quality losses, but can they also assist with downtime?
Today’s automated machines are designed with predictive maintenance in mind. Monitoring tools and easy access to internal parts allow for minimized downtime, making every part of the factory line more efficient.
Custom Cut Metals provides automated machine solutions at a fraction of the cost of our competition. Developments like our water jet celery cutter give small manufacturers the ability to take advantage of the benefits that normally only larger manufacturers can reap. Contact us today to learn more.