Unplanned manufacturing disruptions can be costly and lead to massive workflow disruptions. However, the Internet of Things (IoT) can help companies reduce manufacturing downtime in a number of ways. Although using technology requires an investment of money and time, the associated positive outcomes are often worth it.
Downtime can have many consequences
Often overlooked is the impact of downtime beyond the single machine experiencing the problem. The most obvious initial problem may be the company’s inability to use a device.
However, overall downtime may increase if companies have to specifically order parts or wait longer than expected for service technicians to confirm the problem and provide a solution. Then, depending on the purpose of the machine, the company may need to completely reorient production or temporarily shut down parts of the plant due to a malfunction.
In other cases, power outages can limit business productivity and mean fewer people can work shifts at any given time. If a business faces tight deadlines affected by machine failures, it could disappoint customers or potentially breach related contracts.
Manufacturers have several options for using IoT to minimize downtime. However, a popular solution is to apply the technology to predictive maintenance.Research has shown that this approach may lead to 70-75% reduction in failuresDowntime is reduced by 35% to 45%.
So, for starters, IoT can reduce the frequency of machine failures. Then, when they happen, the time the device can’t operate should be shorter. These effects should mean issues are less disruptive overall and give companies more flexibility when reps choose how to deal with them.
IoT can keep people safe and healthy
Broken machines aren’t the only cause of manufacturing downtime. A survey of Asian manufacturers during the COVID-19 pandemic revealed that they face multiple challenges.The most relevant questions on this topic are 30% have difficulty With the availability of team members.
COVID-19 is highly contagious, and conditions in many factories facilitate its spread. This can lead to manufacturing downtime if all or most people on a given shift are contracted. This is especially likely to happen if the companies involved are already struggling with staff shortages.
In Singapore, Shell used IoT devices to speed up the contact tracing process for manufacturing workers at oil and gas plants. Before deploying the technology, Took a few hours to complete Conduct contact tracing for all parties in affected areas. Using a portable device with built-in connectivity, users can now store the necessary contact tracing information and share it with interested parties, simplifying the overall approach.
IoT can also reduce manufacturing downtime due to injuries. Many jobs in the industry require repetitive motions. If workers don’t know the proper way to lift, bend and reach, they may be at increased risk of injury, requiring time off work and causing plant shutdowns.
Connected portable devices can also reduce fatigue.Statistics show that companies with 1,000 employees Possibility to lose up to $1 million Every year because of fatigue.
Wearables in the workplace can make people more aware of when they need to adjust their movements or posture. Vigilant Technologies makes Arc portable. It’s a clip-on product that detects dangerous movements and then vibrates to help people correct them.A company representative said the companies have successfully reduced Over 33% of risky behaviors and injuries that require wasting time.
Avoid time-consuming situations with IoT
Leaders are also keen to reduce manufacturing downtime, as there are often aspects that make it time-consuming to replace certain parts. For example, some industrial machinery parts used in manufacturing can reach extremely high temperatures. In this case, it is often necessary to cool the part before replacing it. However, this step may take several hours.
The best approach is to shut down a component for a while, which will cause the least disruption. If the factory only operates during the week, the factory can do the work on the weekend. The data provided by the IoT gives decision makers greater control over when maintenance or parts replacement occurs. This flexibility is not possible if a machine suddenly fails.
A global auto parts manufacturer wanted to reduce fan failures in welding ovens.When the fan fails, the factory Delegate takes 36 hours Solve the problem. However, sensor data allows them to intervene before the fans stop working. Specifically, the company’s data scientists warned that ventilators would fail within 58 hours.
Maintenance personnel are skeptical of the information. However, their superiors insisted that they modify the components based on what the data said. The maintenance team was surprised to find that half of the fan blades had disintegrated, proving that the sensor data was accurate.
As this example shows, following a recommended or expected schedule of critical machine maintenance does not always help manufacturers avoid problems. One of the main advantages of IoT is that it can detect things that humans might 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 machine, it can take a while to get to the source of the problem. When a person examines equipment, they can ask questions such as when the abnormal behavior started, what symptoms first appeared, and whether certain factors predispose the machine to these abnormal signs. Possibly they only appear after the machine is first turned on, or at least four hours later.
However, some IoT platforms send real-time data to people inside and outside the enterprise. For example, information can be communicated to field maintenance teams, as well as service technicians associated with the company that manufactures the equipment.
A company specializing in heating, ventilation, and air conditioning (HVAC) equipment developed its virtual technician app. When technicians need help in the field, they can activate it with the push of a button. This contacts all of the company’s internal engineers.it needs less than 10 seconds available for connection Engineers to field technicians who need help.
In other cases, IoT allows outside technicians to access information about customer systems before they arrive on-site to take a closer look at the problem. Then it takes far less time to diagnose the problem once you get there. Machine experts can even troubleshoot certain issues off-site, making it easier to determine the cause of the failure and how to fix it.
Evidence for machine replacement or user training
Most IoT products also allow users to track trends. This ability allows a company’s decision makers to see when it makes more sense to replace equipment than to continue repairs if something goes wrong. Sensor data can show that a particular machine has had six failures or emergency maintenance in the past year. Maybe all similar devices just need attention twice. Armed with this information, it’s easier to justify replacing the machine.
Without the data provided by IoT, business decision makers may be less likely to trust a service technician’s recommendation for a replacement. However, having data available helps create context around it. After discovering that a machine has required maintenance six times in the past year, people can look at support data to see how much money the business lost to failures or the hours it took to resolve the issue.
Likewise, IoT data may show that manufacturing downtime may occur because users are not following the correct steps when operating machines. Some industrial machines require a certain warm-up time before anyone can perform a task with the device. However, sensors may show that some people did not complete this warm-up period.
Alternatively, many manufacturers use equipment such as forklifts. The operator may turn too fast or brake too hard. Many IoT sensors act as asset trackers, so these products can capture data about people who are using equipment incorrectly and can lead to preventable downtime.
Leaders can then use this data to see if specific individuals or people working specific shifts need more training to break bad habits. They can also create team resources, such as checklists, to emphasize that relatively simple actions can go a long way in preventing machine failure.
IoT applications can reduce manufacturing downtime
These examples confirm that IoT devices and data can help manufacturing companies reduce machine downtime. However, simply deciding to invest in technology is not enough.
Instead, people need to take the time to understand their current challenges and how IoT can alleviate them. Again, it helps to choose specific metrics to track. It is then easier to verify that IoT has reduced the frequency of downtime. If this does not have the desired effect, then the individual can look for ways to change their system or goals.
