The past couple of years have been turbulent for manufacturing, with the accelerated rate of digital transformation showing no sign of slowing down in 2022. Crucial supply chain issues, increasing customer demands, and the ongoing economic impact of the pandemic are definitely keeping manufacturers on their toes. In response, manufacturing leaders from all over the world are on the lookout for the right digital technologies and strategies to invest in, with a special focus on optimizing employee productivity, safety, and collaboration. Keep your finger on the pulse of the industry and read on to discover our top trends for manufacturing in 2022!
In safety-critical industries, precision matters more than anything, so it’s no wonder that traditional manufacturers can be hesitant to innovate. That being said, staying on the fence for too long also puts you at a disadvantage when it comes to remaining relevant, competitive, and in possession of a significant market share. We’ve put together our top trends for manufacturing in 2022, keep reading to learn more about what these emerging technologies bring to the table in the manufacturing world!
The Internet of Things (IoT)
Connectivity in manufacturing is still a major industry game-changer going into 2022. According to research conducted by Cognizant, 70% of companies are certain that IoT implementation is effective for improving product quality and reducing costs as a whole. IoT is enabling manufacturers across the board to:
- Speed up response times to factory issues
- Optimize efficiency, safety, and cost-cutting
- Track and collect machine data to create a data history
- Make informed and strategic decisions using that real-time data
According to a study from the MPI group, almost one-third (31%) of production processes now involve smart devices as well as embedded intelligence. So it’s no wonder that 34% of manufacturers are planning to incorporate IoT into their existing workflows moving forward.
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Predictive Maintenance
One of the biggest benefits of IoT in manufacturing is so vital that it merits its own section: the ability to carry out remote monitoring and predictive maintenance. Why is this such a huge perk? Simply put, critical equipment breakdowns are extremely costly for all stakeholders due to huge repair bills, the cost of downtime, and the loss of productivity that ensues. According to Gartner, the average cost of downtime in IT totals a jaw-dropping $5,600 per minute.
IoT-powered predictive maintenance allows manufacturers to:
- Devise performance metrics
- Monitor equipment performance from afar
- Automate the data collection process
- Reduce the number of unexpected outages
- Improve machinery life by years
In other words, predictive maintenance means that manufacturers can remotely observe how their machines are running, why they fail, and when it’s likely to happen. This means that instead of being called in to deal with an issue on short notice, they can often identify issues before they even occur and come up with potential solutions in advance. This makes technician visits much faster, more strategic, and more efficient overall.
Deloitte states that “on average, predictive maintenance increases productivity by 25%, reduces breakdowns by 70%, and lowers maintenance costs by 25%”, so we’re likely to see many more manufacturers getting it in place as 2022 moves along.
Cobots
A cobot or collaborative robot is designed to work closely together with humans in a shared workspace. Cobots are typically programmed to carry out repetitive tasks, allowing their human counterparts to focus on problem-solving or coming up with creative solutions instead. They are highly versatile and can be used for a variety of functions, including but not limited to:
- Measuring specific components in the assembly line
- Ensuring that components are in the right stream
- Inspecting products for defects using cameras and sensors
- Carrying out tasks like sanding, grinding, painting, soldering, welding, and more
Cobots are a hit with manufacturers due to their precision, lack of mistakes, and the fact that they can repeat monotonous tasks all day without tiring.
And as a result of the COVID-19 pandemic and the sudden need for social distancing in workplaces, the number of cobots on factory floors has soared. The collaborative robot market is predicted to be worth a whopping $11.8 billion by the time we reach 2030, a huge leap from the $711 million it was worth in 2019.
3D printing
The advent of 3D manufacturing, also known as additive manufacturing, has revolutionized how the industry goes about prototyping and creating tooling. It’s a cost-effective way to test new designs, incorporate feedback efficiently, and troubleshoot issues, fast. It also helps manufacturers produce items on demand instead of in bulk, meaning that they don’t need to store them in warehouses and can create niche products based on specific consumer requirements.
Although 3D printing has been around for a while now, it has gained even more prominence in the last two years and is being lauded as one of the top emerging technologies for smart manufacturing. According to Plex’s 5th Annual State of Manufacturing Technology Report, 3D printing is one of the manufacturing industry’s most important emerging technologies to keep an eye on.
This is due to turbulent disruptions to the global supply chain because of the pandemic, climate change, and events like the obstruction of the Suez Canal in 2021. As the European Association of the Machine Tool Industries and related Manufacturing Technologies, CECIMO states, “One of many lessons we have learned during the last two years is the importance of reducing international dependencies and increasing supply chains’ resilience”.
As a result, there has been a huge push to reduce outsourcing and opt for localized manufacturing instead, something 3D printing empowers manufacturers to do. With 3D printing, manufacturers can create their own tooling onsite instead of outsourcing it, which significantly speeds up the process and reduces external dependencies and waiting times.
Big Data, Machine Learning, Artificial Intelligence, and Digital Twins
There is an enormous amount of data (growing exponentially by the day) that flows through manufacturing ecosystems. Machine learning (ML) and Artificial Intelligence (AI) are what empower manufacturers to effectively collect, process, and measure this data on a huge scale. Those data-backed insights then allow manufacturers to make informed, strategic decisions to optimize their operations. For example, if an unexpected disruption or fault pops up in a factory, AI can analyze historical data to suggest solutions that will minimize those pesky costs and downtime based on historical data.
Some other uses for ML/AI include:
- Visually inspecting, at high rates to avoid missing anything, product parts at different stages of production
- Enforcing quality control throughout the assembly line
- Automatic monitoring of systems and machines
- Processing consumer data to produce customized and personalized products
AI/ML also enable the use of digital twins, or virtual models designed to mirror the characteristics of a real-life, physical object or process. In the context of manufacturing, a digital twin can be used to demonstrate how a piece of machinery will respond under certain conditions.
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Digital Twins in Product Development
Although the concept of a digital twin is not new, according to ARC Advisory Group research, we’re seeing a renewed focus on the benefits of implementing them in the context of driving smart, connected manufacturing.
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5 Advantages of Digitizing Your Product Development Process
VR and AR
In the past, customers were reluctant to administer repairs themselves with only the guidance of technicians, but COVID-19 catalyzed significant changes in that area, too. Since technicians were not able to go to job sites to install equipment or carry out repairs themselves, they had to rely on augmented reality (AR) and virtual reality (VR) tech to provide remote assistance. Now it’s not an uncommon practice to send customers devices that support AR and VR in order to walk them through the steps to fix whatever’s not working.
This presents a huge opportunity to manufacturers, as well as AR/VR tech providers, who now have the customer buy-in to explore how these assistive technologies can be increasingly incorporated into day-to-day operations. PwC research has shown that the use of VR and AR in product development has the potential to “deliver a 360 billion GDP boost by 2030.”
Closing thoughts
Manufacturing trends in 2022 are in large part a response to the challenges that have surged since 2020, some of which are evolving with time. The industry still faces global supply chain disruptions, a worrying talent shortage, and increasing customer demands as well as unstable international prices. In order to prepare for the year ahead, manufacturers should focus on increasing their business agility and looking for ways to support their workers' onsite safety and productivity.
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