5 Connected Innovation Trends in Manufacturing

Like all other sectors, advanced manufacturing has had to meet the pandemic’s unprecedented disruption by leveraging and deploying innovative technologies. Workforce challenges, changing customer needs, supply chain issues, and much more have made innovation foundational to competitiveness and growth moving forward.

Innovation in manufacturing environments is as much about opening new business possibilities as improving current processes. While many ways support this type of innovation in manufacturing, we’ll look at five connected trends that are high on the list.

#1. IIoT

The industrial internet of things (IIoT) is a necessary area of innovation for any manufacturer that is looking to maximize productivity, machine life, uptime, and throughput while lowering costs and waste. This collection of sensors, data collection devices, measurement systems, and actuators can provide powerful analytics on systems and processes in the manufacturing environment. It can also provide insights that lead to innovation in terms of new processes and machines that expand markets, products, and services.

These systems can feed powerful analytics that enables real-time visualization of the factory floor or across distributed manufacturing environments. This data and two-way connection can feed autonomous and semi-autonomous actions such as robotics, cobots, and digital twins. Manufacturers can use artificial intelligence (AI) and machine learning (ML) for further analysis and actions that drive tangible business outcomes.

Cloud technologies make it much easier to grab sensor data, while edge connectivity can put the processing closer to its origins when time and latency are factors. It is imperative to have a means to easily connect and manage edge assets to realize innovation possibilities. These are all trends in our top five that show how innovation needs to be part of a long-term strategy of digital transformation that sets the stage for digital innovation.

#2. Smart Manufacturing

Smart manufacturing is an innovation engine for modern factories that rely on IIoT by digitally connecting machines and distributed manufacturing environments for automation, robotics, and analytics. Smart technology adoption and implementation empower manufacturers to see and harness innovation possibilities while improving productivity, efficiency, resiliency, and sustainability.

The goal of smart manufacturing and the broader concept of innovation in manufacturing is to go beyond utilizing technology to realize efficiency gains and optimize processes. These strategies enable things like robotics and digital twins, which are both on our list of the top five innovation trends.

#3. Digital Twins

Digital twins are about creating a digital version of a real process or machine to optimize productivity and profitability without investment in a physical product. The digital twin can mirror a real or imagined machine or system to provide insights on operational improvement along with new designs and uses that expand products, services, and markets.

Digital twins can encompass systems and processes along with machines and production lines. They can also model things like supply chain management to improve fleet and routing efficiency or packaging performance. This can make a critical difference in the current just-in-time manufacturing environment.

The ability to test new processes and products before introducing them to the real world can save massive costs. It also maximizes and broadens the innovation aspects that lead to improved customer and employee experiences. Using causal digital twins, companies can improve processes, control quality, and safety tests, improve supply chain management (modeling fleet and route efficiency and package performance), and determine just-right production for just-in-time manufacturing.

Digital twins can also improve things like customer and employee experience by allowing those groups to test new processes and products before they ever make it to the real world. While IIot, cloud, and smart manufacturing are all vital components of innovation with digital twins. It’s always about the data, which is where AI/ML is a vital innovation trend.

#4. Machine Learning and AI

AI/ML works broadly across the modern manufacturing environment as integral parts of an IIoT platform via control, management, and analytics. This is the fulcrum that leverages data from the cloud to the edge. It makes usage, condition, predictive and prescriptive-based maintenance possible. This supports innovation by helping manufacturers:

• Better understand processes and machine lifecycles,
• Implement autonomous or semi-autonomous actions by machines and systems via robotics and digital twins
• Support and help develop new processes and systems to be more resilient or adaptable to new lines of business

AI/ML processes are also the foundation of computer vision, which can enable quality management. They can provide monitoring and anomaly detection in processes, systems, or products in ways and places that humans cannot.

This ability to monitor production processes and product QA from the production line to warehousing and shipping can feed data analysis to improve and develop new processes. There are countless ways that computer vision can drive business value in the broader manufacturing sector and beyond. The goal is to improve accuracy, reduce waste, and maximize speed to open innovation possibilities. It even plays a critical role in our last innovation trend of robotics.

#5. Robotics

From the production floor to warehousing, eCommerce, and the supply chain, industrial robotics have become commonplace across the manufacturing sector. There was a 10 percent jump to a record 3 million industrial robots operating in factories around the world in 2021, according to the 2021 Industrial Robots report from the International Federation of Robotics.

AI/ML, IIoT, and the cloud play a major role in robotics from programming and control to data collection and analysis. This all allows for innovations in safety, speed, efficiency, and accuracy while also enabling forward-thinking analysis for new products. From autonomous robots to cobots that work collaboratively with humans, robotics enables manufacturers to pivot for future market disruptions and emerging market possibilities.

Conclusion

Innovation in manufacturing requires merging innovative technology approaches like AI, IIoT, hyper-automation, 5G, and cloud computing to support highly distributed organizations. An important point made in an earlier blog post on innovation was that digital transformation has little meaning unless it is driven by a digital innovation mindset. That type of long-range planning for creation can be daunting for manufacturers that are occupied with meeting current output, product, and service needs.

Innovation is not a core skill for manufacturing companies. The challenge is that manufacturers must compete with every sector for data science, and AI/ML application/cloud specialists to create this path to innovation. This is where the importance of having a co-creator like Techolution comes into play.

Scaling digital transformation for digital innovation across distributed manufacturing plants can take time. This makes it imperative to have a long-term plan, strategy, and co-creator partner. They can adjust the strategy to meet developing needs, markets, and business climates.

Having Techolution as your co-creation partner enables us to provide the fractional or end-to-end services that manufacturers may need in terms of:

• Personnel
• Expertise
• Planning
• Implementation
• Digital transformation
• Innovation consulting

By helping to develop a long-term vision for developing a culture of innovation, manufacturers can:

• Incrementally deploy technologies based on budgets and specific business outcomes
• Scale these efforts across individual facilities or even departments
• Always remain focused on significant real-time improvements in business outcomes via innovation

We bring the expertise within a fixed-bid model devoted to business outcomes. That helps manufacturers make innovation a product rather than a byproduct of digital transformation. To learn more about how the Techolution team can act as your co-creator for innovative business outcomes, visit our Solutions Briefs Page.