Unscheduled downtime wreaks havoc on production schedules and stresses people to make up for lost time while protecting cost objectives. Strategies for minimizing downtime used to focus on scheduled equipment maintenance and the ability to quickly repair anything that went wrong. Now, with automation, there is software and technology as well as hardware to manage.
Having good service agreements and skilled repair people are still essential for keeping production running smoothly. However, technology has changed the playing field for preventing downtime by making data more accessible. Knowing exactly what is going on in your production process can completely alter the way problems are managed and mitigated. Data eliminates much of the guesswork about how much maintenance is needed, and what causes downtime.
A system with built-in intelligence can also start to recognize patterns such as a temperature shift that regularly precedes equipment failure. Knowing the precursors to equipment failure can help preventive maintenance be much more effective. Critical equipment can be set up with monitoring sensors so that you aren’t limited to doing maintenance on a schedule, but rather by what the equipment actually needs.
To minimize downtime, multiple strategies can and should be deployed. We’ll explore some of the most effective strategies in this article.
Identify root causes
What if downtime isn’t caused by machinery malfunction, but rather by process inefficiency? By monitoring the production line and gathering data, inefficient processes can be identified. For example, does a robotic arm “fail” because there is no part ready for it to pick up? The root cause of that problem lies further downstream, even though it might be the stopped robot that causes a production downtime event.
Is setup taking much longer than it should? When retooling takes longer than it should, it moves from planned downtime to unplanned. In some cases, downtime costs may outweigh the cost of having extra equipment available to eliminate time lost to setup. It’s a good idea to re-examine setup processes to look for ways to improve efficiency.
Prevent human errors
Humans make errors, but some of them can be prevented. Knowing which errors are made repeatedly can help identify training needs or a procedure that needs optimization to minimize errors. In some cases, a “poka-yoke” may be needed. Poka-yoke is a Japanese term for mistake proofing. An example would be re-designing a component or tray so that it can only be oriented the correct way. Eliminating the possibility to do things wrong makes training new operators easier, and minimizes mistakes that cause downtime.
Mitigate supply chain issues
Keeping a minimal inventory works well when you can count on parts arriving just in time. Unfortunately, supply chain issues have compromised inventory predictability. Downtime caused by “waiting for parts” needs to be identified and addressed with procurement personnel. Reliability should be factored in to decisions about sourcing essential parts, and setting minimum inventory levels.
Allow time for equipment care
When setting KPIs, be careful to ensure that machine operators aren’t penalized for taking the time to stop and care for equipment. The old adage “a stitch in time saves nine” applies here. If operators are under pressure to keep production running at maximum speed at all times and not stop except for dire circumstances, they won’t be able to make small adjustments that can prevent a bigger stoppage later.
Instead, build in time allowances and rewards for operators who do take the time to check, care, and maintain equipment to keep it running optimally even after their shifts are over.
Train operators using digital tools
Having properly trained operators is essential to keep equipment running; however, training people can slow down production. To optimize training, take advantage of simulators and digital options to allow adequate time for explanations and a complete understanding of how all equipment works, without the pressure of training on a running production line.
Multi-faceted strategies, data analysis, and digital tools offer many opportunities to minimize automation downtime.
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