Can AI reduce unplanned downtime?
Generative AI reduces unplanned downtime by making the signals that precede a stoppage cheap to investigate, a production team can ask what deviated this shift, on which line, and how it compares with normal, then act while the deviation is still small, reducing overall downtime.
This week, a production manager at a manufacturing plant must decide whether to invest in a new system to reduce unplanned downtime, and they are currently basing their decision on intuition and past experience. However, with the help of AI, they can make a more informed decision by analyzing their own data. The question is, can AI really reduce unplanned downtime in production?
What's in the data
To determine if AI can help reduce unplanned downtime, the production manager needs to look at the data they have available. Specifically, they need to have data on output against plan and cycle times. This data will show them where the bottlenecks are in their production process and where they are losing time. Without this data, it's impossible to know where to focus their efforts. Most people think that having some data is better than none, but they are wrong - having incomplete or inaccurate data can lead to misguided decisions.
A shift supervisor, for example, checks the maintenance log to see when equipment was last serviced and when it is due for maintenance again. They can then use this information to schedule maintenance during downtime, reducing the likelihood of unplanned downtime. But without data on output against plan and cycle times, they won't know which equipment to prioritize.
The mechanism
The mechanism by which AI can help reduce unplanned downtime is straightforward. By analyzing the data on output against plan and cycle times, AI can identify patterns and trends that may indicate potential downtime. For instance, if a particular machine is consistently producing less output than planned, AI can flag this as a potential issue and alert the production manager. The production manager can then investigate and take corrective action to prevent downtime.
This is not a complex process, but it does require accurate and complete data. Many people think that AI is a magic bullet that can fix all their problems, but it's not - it's just a tool that can help analyze data and make informed decisions.
What it will not fix
While AI can help reduce unplanned downtime, it's not a silver bullet. It won't fix underlying issues such as poor maintenance, inadequate training, or faulty equipment. These issues need to be addressed through other means, such as regular maintenance schedules, training programs, and equipment upgrades. AI can only analyze the data it has been given, it can't fix the underlying problems.
For example, if a machine is producing less output than planned because it's faulty, AI can flag this as a potential issue, but it can't fix the machine. The production manager needs to take corrective action to repair or replace the machine. To learn more about how to optimize production, visit our production page.
How you would know it worked
To know if AI is helping to reduce unplanned downtime, the production manager needs to track overall equipment effectiveness (OEE). OEE is a measure of how well equipment is performing, taking into account factors such as uptime, output, and quality. By tracking OEE, the production manager can see if AI is having a positive impact on reducing unplanned downtime.
For instance, if OEE increases after implementing AI, it's likely that AI is helping to reduce unplanned downtime. But if OEE remains the same or decreases, it may indicate that there are underlying issues that need to be addressed. To get help with implementing AI in your production process, visit our contact page.
When it's the wrong choice
AI is not the right choice for every production process. If the production process is highly variable or unpredictable, AI may not be able to accurately analyze the data. In these cases, other methods such as manual analysis or simulation modeling may be more effective. Additionally, if the production process is relatively simple and doesn't produce a lot of data, AI may not be necessary.
In these cases, the production manager needs to use their judgment to decide whether AI is the right tool for the job. They need to consider the complexity of the production process, the amount of data available, and the potential benefits of using AI. By doing so, they can make an informed decision about whether to invest in AI or not.
Frequently asked questions
How can AI help reduce unplanned downtime in production?
AI analyzes data on output against plan and cycle times to identify patterns and trends that may indicate potential downtime, enabling production teams to take corrective action.
What data is required for AI to effectively reduce unplanned downtime?
Accurate and complete data on output against plan and cycle times is necessary for AI to identify bottlenecks and potential downtime, allowing for targeted maintenance and repairs.
Can AI fix underlying issues that cause unplanned downtime?
No, AI cannot fix underlying issues such as poor maintenance or faulty equipment, but it can alert production teams to potential problems, enabling them to take corrective action.
How can the effectiveness of AI in reducing unplanned downtime be measured?
Tracking overall equipment effectiveness (OEE) can help measure the impact of AI on reducing unplanned downtime, providing insights into equipment performance and uptime.