Skip to content

Industry 4.0 is here to stay, but is your factory smart enough?

When we think about smart factories, the first thing that comes to mind often relates to technology, like robotics, automation, and highly modern production lines. However, before a factory, plant, or mill can benefit from the latest gadgets and equipment, they need to pay attention to the basics – the smart in smart factories stems from somewhere else entirely. We sat down with Etteplan’s Smart Factory experts Juha Nieminen and Kari Jussila about what exactly makes factories smart.

The telling signs of smart factories are actually quite simple. Such as a shared situation awareness throughout the entire company, as common goals always require a solid understanding of how to get there. This is among the very first steps that advance the company from exploration to migration on the maturity ladder. 

“It says a lot if every employee possesses a unified state of situation awareness and understands the challenges or benefits the same way. That’s already being smart. And without paying attention to information and data, you can’t start thinking about automating decision-making or other more advanced steps,” says Juha Nieminen, Etteplan’s Services Development Director.

Sometimes factories are so keen to utilize the latest automation technology, for example, that they forget to invest in people and processes first. This waters down any intended productivity boosts, as they do not know how to fully take advantage of the technology.

“One common mishap I keep seeing are companies who buy expensive software and think that one solution alone is enough to make your operations more efficient. At the same time, they may not pay attention to their processes and the data they are providing, let alone use that information to their advantage,” Kari Jussila, the Director of Business Development, explains.

Improving a process of production requires smart thinking and planning as much as modern technology and result-driven processes. Leading with data and getting the hang of your asset information management are the basic building blocks for any factory aiming to become smarter – and eventually reach the highest maturity level where predictive analytics, for example, is your everyday bread and butter.

Data enables constant learning and development, but it is vastly underused

Information and data play a key role in today’s business, and for a good reason. You may have a warehouse consisting of 40 000 spare parts and nearly a million related documents. If that information is scattered, it’s impossible to achieve a comprehensive overview – let alone even dream about efficiency improvements. 

“It takes some coordination and meaningful solutions to have your asset information properly managed. But once you do, you will see immediate benefits in terms of time savings, for example, on top of any long-term effects of using your assets efficiently,” Nieminen points out.

Many facilities are also fully equipped to gather data from various sensors and systems, but the processes for using all that information can be lacking. In terms of sustainability, for example, it is impossible to make an actual impact for the better without measurements and concrete actions to reduce emissions.

“The first step is always to develop an understanding of the goal and how to measure the outcome. That way, you can put your focus to the solutions which really add value to your operations and avoid investing to the unnecessary ones. This is also crucial for older factories looking to retrofit their equipment to answer today’s demands. In this case, smart doesn’t come from the latest technology, but again, smart planning,” Jussila adds.

Today’s maturity level paves the way for an improved tomorrow

One way to address the state of factories and how smart they are is to use the maturity ladder. Phase zero revolves around exploration, where there are little to no actions taken, or merely initial attempts made towards a smarter factory. 

In stage one, integration, we start seeing a variety of actions from connected data and devices to digital twins and improved and standardized processes. This is the step on which most companies are or are aiming towards.

“Digital twin essentially means having your physical items represented in the virtual space, so you can run simulations for different scenarios before committing to any changes or improvements in the existing facility. For this, you need processes for data management as much as connected devices, so it takes some setting up if your base level is around zero,” Nieminen says.

The final stage, adaptation, is well advanced and includes, for example, big data analytics, self-optimization, and continuous adaptation. If existing factories are about retrofitting and optimization, the new and upcoming facilities are built and designed to support different smart factory features.

So, the level of maturity varies due to many factors, but what is the status of European companies, factories, and mills overall?

“There’s a big difference between process and manufacturing industries, and some companies are more advanced than others. Also, factories that produce something in high volumes are more likely to have sophisticated automation in place than those that work with smaller volumes. The trend is positive, though, and most of the companies are already at least exploring and testing suitable options for their needs,” Nieminen explains.

And of course, the smartest factories are keen to include stakeholders, such as contractors, retailers, licensing, and end customers in their journey towards more intelligent operations – that way, the entire chain can utilize the benefits.