Unplanned manufacturing interruptions can be very costly and lead to massive workflow disruptions. However, the Internet of Things (IoT) can help companies reduce manufacturing downtime in many ways. Although the use of technology requires financial and time investments, the associated positive results are often worth it.
Downtime could have many ramifications
Something that is often overlooked is that the effects of downtime extend beyond the single machine experiencing the problem. The most obvious initial problem may be that the company cannot use a certain piece of equipment.
However, overall downtime can increase if a company has to specially order a part or wait longer than expected for a service technician to confirm the problem and offer a solution. Then, depending on the purpose of the machine, a company may need to completely reorient production or temporarily shut down part of the plant due to the breakdown.
In other cases, an outage could restrict business productivity and mean fewer people can work a shift at any given time. If a business is facing a tight deadline impacted by machine failure, it risks disappointing customers or potentially defaulting on an associated contract.
Manufacturers have various options for using the IoT to minimize downtime. However, a popular solution is to apply the technology for predictive maintenance. Research indicates that the approach could lead to a 70-75% reduction in breakdownsas well as a 35 to 45% reduction in downtime.
So, for starters, the IoT could reduce the frequency of machine failures. Then, when they occur, the time during which the equipment cannot operate should be shorter. These effects should mean that issues are less disruptive overall and give companies more flexibility when reps choose how to handle them.
IoT can keep people safe and healthy
Broken machines aren’t the only reason for downtime in manufacturing. A survey of Asia-based manufacturers during the COVID-19 pandemic showed they faced multiple challenges. The most relevant question for this topic is that 30% had difficulties with the availability of team members.
COVID-19 is highly contagious and conditions in many factories facilitate its spread. If all or most of the people on a given shift contract it, this could lead to manufacturing downtime. This is particularly likely if the company concerned is already struggling with staff shortages.
In Singapore, Shell used IoT devices to speed up the contact tracing process for manufacturing workers at an oil and gas plant. Prior to the deployment of the technology, it would have been took hours to complete contact tracing on all parties in an affected area. Now, users use portable devices with built-in connectivity that can store and share the necessary contact tracing information with the right parties, simplifying the overall approach.
IoT can also reduce manufacturing downtime caused by injuries. Many jobs in this industry require repetitive movements. If workers are unaware of the proper ways to lift, bend and reach, they could be at increased risk of injury requiring time off work and contributing to plant downtime.
Connected portable devices could also reduce fatigue. Statistics show that companies with 1,000 employees could lose up to $1 million annually due to fatigue.
Wearable devices in the workplace can make people more aware of when they need to adjust their movements or posture. Vigilant Technologies makes the Arc portable. It’s a clip-on product that detects risky movements and then vibrates to help people make corrections. A company representative says the companies have been successful in reducing more than 33% for dangerous behaviors and injuries requiring lost time.
Avoid time-consuming situations with IoT
Leaders are also keen to reduce manufacturing downtime as there are often aspects that make replacing certain parts time consuming. For example, some industrial machinery parts used in manufacturing reach extremely high temperatures. In such cases, it is usually necessary to cool them before replacing a part. However, this step could take hours.
The best approach is to turn off a component for a period that will cause the least disruption. A plant can do this over a weekend if the facility only operates during the week. The IoT provides data that allows decision makers to have more control over when maintenance or part replacements take place. If a machine breaks down suddenly, it is not possible to have this flexibility.
A global automotive component manufacturer wanted to reduce instances of fan failures inside soldering furnaces. When the fans broke, the factory reps needed 36 hours to solve the problem. However, the sensor data allowed them to intervene before the fans stopped working. Specifically, the company’s data scientists warned that the ventilators would fail in 58 hours.
Maintenance crew members doubted the information. However, their superiors insisted that they modify the components according to what the data said. The maintenance team was surprised that half of the fan blades had disintegrated, proving that the sensor data was accurate.
As this example shows, following the recommended or expected maintenance schedule with critical machines doesn’t always help manufacturers avoid problems. One of the main advantages of IoT is that it can detect things that humans may miss. When technology detects these anomalies, manufacturing managers can save time and spend resources keeping equipment working or reducing manufacturing downtime.
IoT speeds up response times
When someone initially notices a problem with a piece of machinery, it can take a while to get to the root of the problem. When a person examines the equipment, they can ask questions about when the abnormal behavior started, what symptoms first appeared, and whether certain factors make the machine more likely to show these unusual signs. Perhaps they appear only after the first start of the machine or after at least four hours.
However, some IoT platforms send real-time data to people inside and outside of a business. For example, the information can be transmitted to the on-site maintenance team, as well as to service technicians associated with the company that manufactures the equipment.
A company specializing in heating, ventilation and air conditioning (HVAC) equipment has developed its Virtual Technician application. When technicians need help in the field, they launch it with the press of a button. This contacts all of the company’s internal engineers. It takes less than 10 seconds to connect an available the engineer to the field technician who needs assistance.
In other cases, the IoT allows outside technicians to access information about a customer’s system before arriving onsite to take a close look at the problem. Then it takes much less time to diagnose the problem after getting there. A machine specialist may even be able to troubleshoot some things off-site, making it easier to determine the cause of the fault and how to fix it.
Provide evidence for machine replacements or user training
Most IoT products also allow users to track trends. This capability allows a company’s decision makers to see when it might make more sense to replace equipment rather than continuing to repair it when problems arise. Sensor data can reveal that a particular machine has broken down or had urgent maintenance six times in the past year. Perhaps all similar equipment only needed attention twice. Having this information makes it easier to justify replacing a machine.
Without the data provided by the IoT, a business decision maker may be less likely to trust a service technician’s recommendation to proceed with a replacement. However, having the data available helps create context around it. After seeing that a machine has required maintenance six times in the past year, a person can then look at the supporting data to see how much money the business has lost due to the breakdown or the number of hours it took to fix the problem.
Likewise, IoT data could show that manufacturing downtime can occur because users do not follow proper steps when operating a machine. Some industrial machines require a certain warm-up period before someone uses the equipment for tasks. However, sensors could reveal that some people do not complete this warm-up period.
Alternatively, many manufacturers use equipment such as forklifts. Operators could engage in behaviors such as turning too quickly or braking too hard. Many IoT sensors function as asset trackers, so these products could capture data about people using the equipment inappropriately and potentially contribute to avoidable downtime.
Leaders could then draw on the data to see if particular individuals or people working specific shifts need more training to break bad habits. They can also create team resources, like checklists, to emphasize that relatively simple actions can go a long way in preventing machine failures.
IoT applications can reduce manufacturing downtime
These examples confirm that IoT equipment and data can be instrumental in helping manufacturing companies reduce instances where machinery is down. However, simply deciding to invest in technology is not enough.
Instead, people need to take the time to understand their current challenges and how the IoT could alleviate them. Likewise, it helps to choose specific metrics to track. Then it becomes easier to verify that the IoT reduces the frequency of downtime. If this does not have the desired effects, then individuals can look for ways to alter their system or their goals.