MANUFACTURERS understand that digital transformation can be tough. Nevertheless, they’ve been making progress using more intelligent software, artificial intelligence, and even tapping into the internet of things (IoT).
To climb the digital maturity curve, the next thing to do is tie together all of the digital initiatives and transform existing production units into smart factories.
“From 3D drawings, to products and their design, engineering, quality control data, and even machines themselves are generating tremendous amounts of data about their operations in real-time,” said NC State-Tsinghua Center for Logistics and Enterprise Development Research Professor of Operations and Supply Chain Management Noel Greis.
Experts like Gris believe that the data that manufacturers are collecting can help build tomorrow’s smart factories today.
Smart factories are not only key to driving the kind of operational efficiency that businesses seek in the digital age, but also help harness the power of technologies such as artificial intelligence (AI), machine learning (ML) and enable use cases such as predictive maintenance and real-time quality monitoring.
Truth be told, manufacturers have been chasing predictive maintenance for a while now, especially with IoT deployments in place.
According to a recent forecast, the global manufacturing predictive analytics industry was estimated to be worth US$535.0 million last year and is expected to hit US$2.52 billion by 2026, growing at a CAGR of 21.7 percent between 2019 and 2026.
Gris, however, believes that ultimately, the goal of smart factories will be to enable machinery and equipment to communicate with each other, and maybe even with people and robots.
“I think we are heading towards an ecosystem of digital factories in the future. This is a big change from where we are today but it’s happening around the globe today and it will probably be here more quickly than everyone thinks.”
Smart factories use big data to achieve big goals
Big data is the foundation of tomorrow’s smart factories, but what can it really help manufacturers achieve?
The reality is that big data doesn’t do anything on its own; However, in a smart factory, manufacturers are able to leverage a combination of technologies such as AI, ML, IoT, and even 5G to achieve big goals.
Here are three examples of how smart factories help manufacturers climb the digital maturity curve:
# 1 | Lights out manufacturing
Let’s face it, the reality is that smart factories won’t need any labor. Instead, everything will be automated and production will run seamlessly, 24-hours a day, seven days a week.
That’s the very definition of lights out manufacturing, and their ability to produce at scale is what drives the efficiencies that organizations and business leaders chase today.
Lights out manufacturing makes economic sense as organizations can provide customers with products at a lower price, and possibly retrain workers for non-routine tasks in the factory, the warehouse, or maybe even the office.
# 2 | Demand-driven production
Smart factories have access to data from machinery and equipment inside the business — but they also have access to data from across the business.
Using intelligent software, smart factories could potentially become demand-driven production units, ensuring that the right quantities are produced, avoiding wastage and optimizing the working capital used by the organization.
At the end of the day, the reality is that demand-driven production is a sure-shot way to boost efficiencies and reduce costs, and smart factories make it all possible.
# 3 | Centralized operations
When you take into account that smart factories can lend themselves to lights out manufacturing and feed into an organization-wide data platform, it’s easy to see how they can enable centralized operations.
The benefit of centralized operations cannot be understated — it’s what helps optimize the business beyond just the operational facility and drives transformational change.
Overall, the ultimate goal is for smart factories to become an extension of the organization’s digital fabric, rather than serve as a contributor to the digital ecosystem.