The Top 10 Digital Transformation Trends in Manufacturing for 2022
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The Top 10 Digital Transformation Trends in Manufacturing for 2022
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Experienced Digital Marketing Executive with a history of working in the information technology and services industry.
Clearly, the thing that’s transforming is not the technology — it’s the technology that is transforming you.” — Jeanne W. Ross
Digitization has changed many industries' entire landscape, and the manufacturing sector is not an exception. Advanced technologies are taking this industry to greater heights.
As per the latest marketing reports, the global manufacturing industry's revenue was USD 116.14 billion in 2021. These numbers will grow to USD 337.10 billion in 2028 at a CAGR of 16.4%. This steady growth in CAGR results from the growing demand for digitized manufacturing technologies worldwide.
Manufacturers have started identifying digital transformation prospects to increase their business productivity, ensure rapid growth, and remain competitive.
Indeed digitization has greater impacts and can give your brand an edge in the market if done properly. The successful implementation comprises the latest digital manufacturing trends that include the Internet Of Things (IoT), Augmented Reality (AR), Artificial Intelligence (AI), Blockchain, and more.
My blog intends to provide you with a list of top trends that can help you establish a robust digital transformation foundation for your manufacturing business and derive maximum benefits from it. So, let's get started.
Top Digital Transformation Trends in Manufacturing
1. Artificial Intelligence (AI) for Greater Efficiency in the Manufacturing Process
Among the digital transformation trends in manufacturing, perhaps none is more prevalent than AI. Experts predict this technology will drive over 40 percent of all business value by 2022. What's more, Gartner estimates that 75% of customer interactions will be managed without a human agent by the end of 2022.
One of the primary reasons for the tremendous growth in AI-related revenue is that organizations want to take advantage of deep learning and predictive analytics to improve their business processes and boost their ROI. Many manufacturers have already adopted this technology and use it for various tasks, such as:
- Identifying profitable trends in sales and marketing.
- Removing humans from the equation in high-risk tasks, thus reducing the likelihood of human error
- Analyzing data collected from connected machines in real-time to predict machine failures
- Improving quality management by detecting defects before they become a problem
- Identifying profitable trends in sales and marketing.
2. Collaborative Robots to Speed up Manufacturing Process
Automating repetitive tasks performed by humans is a significant benefit for organizations that want to improve their ROI. Collaborative robots collaborate with human workers and increase productivity in the workplace. According to a report from Tractica, collaborative robots will be used in nearly every industry by 2025, including manufacturing.
Research from the International Federation of Robotics proves that the number of collaborative robots in operation worldwide will increase twofold in 2022. The report also forecasts an impressive compound annual growth rate (CAGR) of 32 percent for this technology over the next eight years.
3. Digital Twin to Bridge the Gap Between Data and Actionable Insights
A digital twin represents a digital representation of a real-world object or system, such as a product, machine, building, or process. For manufacturers, the management (ELM) stage.
It can help companies gather data from machines and incorporate it into smart manufacturing strategies. Manufacturers can use them to predict machine failures and increase equipment uptime.
For example- A manufacturer has a CNC machine that, over time, begins to show signs of stress. The company can use data from this machine and its twin to predict when the equipment will break down and deliver a replacement before it happens. Therefore, digital twins help manufacturers improve their operations and better serve customers.
4. Augmented Reality For Faster & More Efficient Maintenance Services
Augmented Reality and Virtual Reality technologies will play a significant role in the digital transformation trends in manufacturing because they allow organizations to offer customers better, faster maintenance services.
By leveraging AR devices for visual instructions, manufacturers can demonstrate how to fix defective products or equipment to resolve issues more quickly.
For example- Let's assume that a customer has purchased a faulty machine part. A manufacturer can send an engineer to the customer's location with an AR device, which shows them how to make the necessary repairs. It means customers spend less time waiting for maintenance services and get back up and running more quickly.
5. Blockchain to Boost Transparency in the Manufacturing Process
According to a recent report from Gartner, blockchain is becoming one of the top five technologies that manufacturers must consider. Its decentralized, transparent nature makes it a perfect fit for many business processes within verticals such as manufacturing.
For example- Blockchain enables manufacturers to eliminate intermediaries and increase transparency in the supply chain process. This technology allows organizations to share information securely without compromising data integrity.
6. Sensors & Smart Devices for Better Quality Control
In order to keep pace with the expectations of the digital consumer, businesses must ensure that their products delivered to the market are safe, high-quality goods. Manufacturers can use a variety of sensors and smart devices in real-time to track everything from the environmental conditions of a product to its location.
For example- A manufacturer has multiple facilities that produce metal parts for machinery. Sensors and smart devices allow them to track these goods at each step in the process to ensure they don't fall into the wrong hands or travel too far from their original destination.
7. Advanced Analytics for Real-time Risk Prevention & Management
Manufacturers can use advanced analytics to gain real-time insights into potential risks throughout their production processes, which helps them avoid costly issues before they occur.
For example- an energy company operates a chemical plant that produces harmful gases and flammable liquids. It uses advanced analytics to monitor the equipment in real-time for temperature fluctuations. If the system detects an issue, it sends an automatic alert to nearby personnel, who can address the problem before it becomes severe.
8. 3D printing for a Faster & More Efficient Prototyping Process
As a result of rising product complexity and customer expectations for customized goods, manufacturers must adopt technologies that help them improve turnaround times and cut costs. A viable option for many businesses is 3D printing, which enables them to quickly build a new product or component model before it goes into full production.
For example- a manufacturer has created an innovative ax design with interchangeable heads for different uses. Before investing in expensive tooling, they can 3D print several versions of the ax, which helps them test its features and make any necessary adjustments.
9. The Internet of Things (IoT) to Create a Smarter and More Secure Production Environment
Smart devices can play a significant role in helping manufacturers deliver better customer experiences and generate new revenue streams by making new business models that support digital transformation.
For example- An industrial manufacturer has built a network of smart devices around its facilities that monitor the environment, including temperature fluctuations, energy consumption, and unexpected noise levels. This data can predict breakdowns before they occur and make any necessary adjustments to improve uptime.
10. 3D Scanning for Better Part Inspection During Production
Due to the rising products' complexity, manufacturers must verify that their components are manufactured to the correct specifications. One way to do this is through 3D scanning, which gives them a digital blueprint of each product to compare it with design specs before allowing its release into the production process.
For example- a semiconductor manufacturer uses 3D scanning to ensure its parts meet specific requirements in the production test phase. If not, they can make necessary adjustments before the product goes into full production.
11. Predictive Maintenance for Greater Equipment Uptime
Predictive maintenance is a technique manufacturers can use to keep their equipment in optimal working order for extended periods. According to research from McKinsey, this technology can reduce unplanned downtime by up to 50%.
By using sensors and advanced data analytics tools, manufacturers can more accurately identify potential problems before they occur and make necessary adjustments, such as changing the lubricant levels or cleaning equipment components.
For example- A business that manufactures parts for jet engines has installed sensors on some of its machinery to monitor critical metrics like temperature and usage hours. These devices send regular reports back to a central system to alert operators to any abnormalities before impacting productivity.
12. Edge computing to Improve Services for Smart Factories, cities, and infrastructure
As the number of connected devices grows higher than ever before, businesses struggle to achieve the speed, security, interoperability, and efficiency needed for success.
Fortunately, edge computing can help them overcome these challenges by providing continuous access to big data and advanced analytics applications via the network's edge.
For example- a manufacturer has created a smart factory that houses thousands of sensors throughout its facilities, including monitoring machines, materials, and other vital areas. It makes so much data that it can overwhelm even the most powerful servers. To keep up with demand, they use edge computing, which routes the data to the network's edge before moving it back through a central hub.
Conclusion
We can conclude that digital transformation is a significant opportunity for manufacturers to become more agile, efficient, and competitive based on emerging technologies and trends.
Manufacturers must be willing to take risks and adopt the tech advancements to succeed in the market. The smart factory is changing everything from traditional manufacturing processes to business models.
So, it’s high time to embrace technologies in your manufacturing business, and if needed assistance, get in touch with the business transformation agency. They’ll guide you out better.
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