In manufacturing, downtime is any kind of plant shutdown or work stoppage. These shutdowns can be either planned or unplanned. Regardless of the type of downtime your organization may be dealing with, the goal is the same: to reduce downtime overall. Downtime can be very costly to a company, in terms of both maintenance spending and production losses. Unplanned downtime, in particular, can increase the likelihood of workplace injuries and environmental incidents, such as unintended fuel spills. Reducing downtime with the right technology and analysis tools can save your organization millions of dollars and weeks of lost production time.
Downtime can occur for a variety of reasons. Planned downtime happens when a machine or plant is scheduled to shut down. Typical reasons for planned downtime include routine plant maintenance, equipment inspections, and part replacement. Maintenance and inspections can and should be a normal part of plant operations, as they play an important role in preventing accidents and minimizing age-related equipment failure. Part replacements are inevitable — parts can and do break, and they must be replaced. Schedule your part replacements in advance if possible, especially if you are using predictive maintenance software.
In contrast, unplanned downtime is when you are forced to shut down operations for an unforeseen reason. The cost to reduce downtime and fix repairs associated with unplanned downtime can be up to five times higher than costs associated with reducing planned downtime. Not only does unplanned downtime result in expensive emergency repairs and direct costs, such as buying new replacement parts, but also in higher rates of worker injury, environmental incidents, and potentially damaged customer relationships.
How to reduce downtime
Your first step towards reducing downtime should be to reduce unplanned downtime. Working towards this goal involves employing thoughtful and thorough downtime analysis to understand exactly why, when, and how your plant experiences unplanned downtime. Using tools such as Aspen Mtell®, an asset management software, can vastly improve your downtime analysis and help answer these questions.
Once you have reduced your unplanned downtime, you should be able to manage your planned downtime in a way that only minimally interferes with your manufacturing operation. Optimal downtime management should involve: a regular maintenance schedule; a well-stocked supply of spare parts; a well-informed and qualified maintenance team; and up-to-date asset management software. The last step towards reducing overall downtime is optimizing and streamlining these processes.
Use machine learning to reduce downtime
Advancements in artificial intelligence (AI) have led to vast improvements and practical applications in the industrial Internet of Things (IoT). The right software can now integrate seamlessly with your manufacturing plant, using machine learning to provide insights on real-time data and develop accurate pattern recognition to predict equipment failures well in advance. These types of asset management software and predictive maintenance tools are essential for understanding and mitigating downtime before it occurs.
The Aspen Mtell® prescriptive maintenance software uses low-touch machine learning to assess incoming data, predict equipment failures and reduce downtime. Using AI, Aspen Mtell can recognize precise patterns in operating data that indicate degradation and impending failure — well before it happens. To help predict and reduce downtime, the software has Autonomous Agents, to detect issues and announce them the second they are detected. These Agents learn and adapt over time to improve their predictions. Using this type of software is the most effective way to predict and reduce downtime.
What is machine downtime?
Machine downtime, or equipment downtime, is any amount of time that a machine is not working. The reason for this may be planned (such as a routine inspection) or unplanned (such as a broken part).
How do you reduce machine downtime?
The most efficient way to reduce machine downtime is to employ manufacturing downtime tracking software or a predictive maintenance tool. These programs use sophisticated tracking software to observe how your equipment is running and provide alerts when something is going amiss. Many of these programs provide ample lead time for mitigating a problem; some machine failures may be predicted days or even weeks in advance. Knowing how to anticipate problems and plan for them accordingly is one of the best ways to reduce downtime.
What is downtime analysis?
To learn how to reduce downtime you must first understand it. Proper downtime analysis involves not only keeping track of when downtime is happening, but also for how long, what type of downtime it is, which machine or piece of equipment is down, and its effects on revenue, inventory, and worker safety. Downtime analysis may involve several key components. An effective asset management software program can evaluate many of these elements, but it is also important to have good team communication among your staff.
How does increasing OEE help reduce downtime?
Overall equipment effectiveness (OEE) is a commonly used metric for understanding the manufacturing process. It takes into account several factors—such as machine availability, performance, and quality—and compares those factors to a manufacturing plant’s full capabilities. Increasing OEE means that some of those factors have improved. Generally, reducing downtime will always result in an increased OEE metric.