Around-the-clock uptime initiatives have begun to play a critical role in the success of today’s manufacturing organizations. Businesses considering 24/7 uptime must carefully assess the time and costs associated with industrial automation and increasing productivity.
Although 24/7 operations are a major goal of many manufacturers, other market sectors — such as retail, with just-in-time fulfillment of e-commerce orders — might also be well-suited to robots and 24/7 uptime production strategies.
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- Manufacturing and supply chain operations are reaping the benefits of 24/7 operations, but organizations adopting the practice should be aware of the technical and operational requirements.
- Hardware and software robots are key components of improving efficiency, but there is such a thing as too much maintenance, which can hamper productivity.
- The industrial Internet of Things and FANUC’s proprietary Zero Down Time are further examples of ways to reduce downtime and gain valuable data.
Traditional strategies to reduce downtime
The first thing that many organizations try to do when optimizing efficiency is to focus on traditional maintenance and operations.
Maintenance, particularly preventive maintenance, is considered a virtue. However, many manufacturers subscribe to the idea that over-maintenance can increase total costs. While some maintenance crews might argue that there is no such thing as over-maintaining equipment, there is typically a point where excessive preventive maintenance can indeed increase total costs and reduce production-line availability.
The need to balance best-in-class preventive and predictive maintenance with production disruptions is a classic functional challenge with 24/7 uptime. To maximize uptime, organizations have often turned to preventive maintenance (PM) and overall equipment effectiveness (OEE) programs.
OEE includes factors such as equipment availability, performance, and product quality. At the same time, terms such as mean time to failure (MTTF) or mean time before failure (MTBF) have been in the vocabulary of engineers and maintenance personnel for years.
How to balance reliability and maintenance costs
The manufacturing conundrum is deciding how often and to what extent planned, preventive maintenance should occur.
Conventional wisdom suggests that about one-third (and sometimes more, depending on the operation) of maintenance activities should be preventive, allowing for periodic inspections, lubrication, and adjustments of equipment. This offers an opportunity to find, predict, and schedule corrective maintenance activities before components or subassemblies fail.
A particularly perplexing challenge can occur in operations that are at or near full capacity, where any maintenance may require partial or full line shutdowns. In these cases, over-maintenance can actually increase overall downtime and result in lost production capacity.
Figure 1 below shows an example of when such conditions can occur. You may be familiar with the theory of optimizing asset management costs. As can be seen in this illustration, there is a point where maintenance and reliability-based costs (see blue curve) increase beyond an optimum low-cost equilibrium between these costs and manufacturing costs, which can include lost productivity. This would result in reduced manufacturing costs (red curve), but ultimately increasing total costs (black curve) as well.
Figure 1: Representation of equipment maintenance and operations cost curves
However, as the industry continues to evaluate best practices in today’s highly sophisticated manufacturing environments, which often use robotics, many companies are realizing that a holistic view of downtime is needed.
This approach includes not only the effects that preventive and corrective maintenance can have on operations, but also input from engineering data on production lines. This can include performance data on individual robots, as well as current and projected status of robotics applications, duty cycles, line speeds, and component hours.
In addition, a holistic approach should include predictions about required maintenance, periodic adjustments, and other activities.
Predictive software and IoT for 24/7 uptime
It’s important to know how maintenance can affect downtime, but that’s only one factor in improving productivity. Another way to address overall performance is with predictive maintenance and operations software.
There’s a lot more to operating in 24/7 uptime mode with robots and using predictive maintenance software than simply accounting for maintenance activities. You also need an in-depth of understanding of equipment specifications, duty cycles, and how robots are used in a factory or warehouse.
This last point is particularly important because equipment manufacturers do not always know how their robots are being used once they are installed on customers’ production lines. For example, a robot arm may be used in a manner that includes greater repeated motion than might initially be expected, increasing its effective duty cycle. Such conditions might also require a modified tracking and inspection schedule.
An effective 24/7 initiative includes the collection, monitoring, and tracking of customer data on what the robots are doing, how they are performing, and whether any anomalies in the data suggest possible future problems.
At the heart of this movement is the inclusion of Internet of Things (IoT) devices throughout the manufacturing process. The data gathered can also aid in the development of algorithms that drive proprietary predictive analytics.
Today’s modern factories rely heavily on robotics to achieve desired line speeds, so round-the-clock operations could suffer serious repercussions from unplanned downtime. Downtime in some operations costs up to $20,000 per minute.
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Robots spread to reduce downtime
Automakers were among the first companies to adopt 24/7 operations, but other high-volume, high-tech industries have begun relying on robots to maximize productivity. For instance, warehouses that support order fulfillment for e-commerce are high-volume, high-tech, and find automation to be particularly valuable.
For example, FANUC America Corp. can use its proprietary algorithms to predict potential failures well in advance, allowing customers to schedule and complete necessary work. And when these services are engaged, great outcomes can occur, said Joe Gazzarato, director of Zero Down Time (ZDT, a copyrighted product) at FANUC America.
“We have 8,000 robots connected to our ZDT database, and we have identified 80 issues before failure,” he said. “Also, we have not missed identifying a projected issue before failure, allowing customers time to take action before failures actually occurred.”
So these are indeed exciting times in manufacturing. With the use of highly efficient robotics components and initiatives like 24/7 operations, engineering and operations personnel can maximize plant productivity to levels not previously thought possible.
Predictive maintenance software such as FANUC’s ZDT promises even more innovation, dependability, and reliability in robotics — in a wide variety of manufacturing environments.