How Smart Factories Drive Remote Work Capabilities

By Poornima Apte, Contributor | May 21, 2020

At a time when China was going through a sudden economic disruption due to COVID-19, Hytera, a manufacturer of private communication devices, managed to do what many other manufacturers could not: It continued production in its Shenzhen facility. Hytera responded quickly to changing market demand and reassigned a few of its 10 production lines to produce disposable face masks.

Similarly, Baoshan Iron and Steel kept its facility in Shanghai running around the clock with automated production. The factory met new health guidelines with its existing operation. According to a news report, “The two 200-meter-long major production lines in Baoshan are fully unmanned, and each line needs just two to three workers for inspections.”

State of the art manufacturers like Hytera and Baoshan are likely the envy of companies that weathered a significant dip in production due to COVID-19. Close to 80% of U.S. companies surveyed by the National Association of Manufacturers in late February to early March said they anticipated a financial impact. More than half anticipated a change in operations.

Shift to the Smart Factory

That “change in operations” could be for the better. Manufacturers can follow the lead of other manufacturers like Hytera and Baoshan. To get there, they need to embrace the principles of Industry 4.0 for adaptability now—and for greater resilience in the future.

As Hytera and Baoshan show, human workers are still required to supervise operations and troubleshoot if needed, but these manufacturers were able to continue mostly autonomous production because of one important reason:  The factories are smart.

While manufacturing is no stranger to automation, a smart factory goes beyond compartmentalized automated processes. As Deloitte defines it, a smart factory is a “fully connected and flexible system—one that can use a constant stream of data from connected operations and production systems to learn and adapt to new demands.”

The smart factory anchors Industry 4.0, the next Industrial Revolution. This time around, the revolution is fed by data that can be aggregated and analyzed.

A smart factory that uses data is:

  • Connected: Data flows across all aspects of manufacturing from the supply chain down to production, distribution, and beyond.
  • Optimized: Machines that are idle can take on new work loads and that saves downtime and increases productivity.
  • Transparent: All stakeholders can access real-time data.
  • Proactive: Problems are spotted using data analytics and solved before they cascade into larger bottlenecks.
  • Agile: Can shift production according to market demands.

Studying the outcomes from simulations allows management to evaluate the risk of change and move forward (or not) accordingly.

What does a smart factory look like? The Nokia production facility in Oulu, Finland, which is 99% automated, is one fine example. If management wants to change any aspect of production, they conduct a dry run using a “digital twin,” that highlights how a change affects production and other processes. Studying the outcomes from simulations allows management to evaluate the risk of change and move forward (or not) accordingly. The plant developed a private wireless network to help speed up reconfiguration of production lines through data. And they use cloud technology to keep an eye on processes in real-time with automated internal logistics via connected mobile robots.

Nokia adopted the principles of Industry 4.0 so effectively that the World Economic Forum designated it as an “Advanced Fourth Industrial Revolution Lighthouse.” A “lighthouse” is a manufacturing facility that has integrated principles of Industry 4.0 to its entire operation, moving beyond the pilot stage. As of 2020, there are 44 lighthouses in manufacturing. The Nokia site goes one step further as an end-to-end lighthouse, meaning its smart principles go beyond the manufacturing site and up and down its supply chain, automating inventory management so vendors know when to ship new materials.

Lessons for All

While not all manufacturers need the scale of Nokia, the key takeaway is that the principles of a smart factory can apply to all businesses large and small. The journey to near-total automation comprises many incremental steps.

The first step starts with digitization. Since the smart factory runs on data that is easily available, aggregated, and analyzed, pen-and-paper processes no longer work. Petrosea Mining, a company in Kalimantan, Indonesia, suffered from a lack of data from all processes. Even when data was available, it was not easily aggregated.

Helping digitize all processes helped the company realize efficiencies in many areas including worker training. Where earlier, workers had to comb through long pages of standard operating procedures on the company intranet, they now access training through a proprietary mobile app on their phones. The company also “gamified” training, which led to more employee engagement. The app uses animation and visuals to make learning more fun. Employees compete to advance from a “soldier” to a “general” on a leaderboard by answering more than 3,000 training-related questions.

The Building Blocks of a Smart Factory

If data lays the foundation for a smart factory, a few technologies comprise the building blocks. Following are examples of how smart factories use these technologies.


Schneider Electric, a lighthouse smart factory, uses IIoT to monitor production processes and relay information about production variations in real time. Vendors that access this data can adjust their inventory accordingly and ship supplies proactively.

Cloud Technology

In the case of a sudden disruption of labor, it would be ideal to move production to another location. Or to have plant managers monitor production from a remote location. Cloud technology provides those capabilities.

Volkswagen is investing in a proprietary cloud platform that will not just facilitate production, but also transmit data to their fleet of vehicles for enhanced customer experiences such as custom media streaming. With data from constant machine monitoring fed into the Manufacturing Execution System, cloud technology helps offsite plant managers view real-time data through mobile devices or computers. The technology enables remote access for oversight into the production line and bottlenecks.

3D Printing

This is a manufacturing process that deposits materials layer by layer. A computer file stores information for the design, which is fed into a 3D printer. This kind of manufacturing is especially useful for precision parts with complicated designs. GE 3D prints a specialty fuel nozzle they developed. One of the biggest advantages of 3D printing is that it stores production information on an easily accessible data file. If the worst were to happen and production shut down in one facility, it could be kickstarted in another location with the file as input.


Robots moved beyond the caged giants seen in automotive manufacturing. While large robots still perform welding, gluing, and fastening operations from cages so they don’t inadvertently harm their human coworkers, today's robots are collaborative (cobots) working alongside humans. A vision-guided cobot, The Hulk, helps with order fulfillment at the Johnson & Johnson facility in Jacksonville, Florida. It helps humans by lifting heavy loads. Robots can also be used for visual inspection of goods and pick-and-place operations leaving humans to attend to less repetitive tasks.

Augmented Reality

Parts break. When they do and experts are not available onsite, augmented reality (AR) helps workers access remote help. The expert can remotely overlay a model of the broken part against the real-life equivalent and guide the worker with fixes in real time. This saves precious downtime. AR can also help with worker training. A worker who needs to run a machine but has no prior training can pull up a mobile device located at the station and run through an AR-driven process to complete a self-guided tutorial. This is particularly useful in training new hires.

Working Alone—or in Tandem

While the list of technologies driving smart factories might be long, companies can choose which ones to implement first, depending on the key performance indicators they want to realize first.

Almost all manufacturers can integrate these technologies into their practices and realize efficiencies.

KPIs that measure adaptability to change might include shortening change-over times (to accommodate production of new, in-demand items) and productivity increase.

The lesson here is that almost all manufacturers, no matter where they are on the path to digital maturity, can integrate these technologies into their practices and realize efficiencies. Many technologies depend on others, however, so it sometimes becomes difficult to implement just one in isolation. For example, effective predictive maintenance needs both IIoT and cloud technology to forecast machine failure. 

Another lighthouse facility, Haier air-conditioning in China, uses an interactive platform where customers can design and order custom products. A performance monitor allows the product to be closely evaluated so the company can detect problems. Customer service calls retrieve performance data from a particular unit so problems are resolved faster. Customer-centric manufacturing allowing for customization at scale is another advantage of smart manufacturing.

What's Next?

To adapt to new realities, many manufacturers could be managing non-essential staff offline and rotating necessary workers in staggered shifts to adhere to strict CDC protocols.

Digitizing data and understanding how to integrate new technologies with existing legacy systems is the next step. Sharing data intelligence can deliver efficiencies in inventory management and make for a more resilient supply chain.

One of the biggest advantages of Industry 4.0 is that it gives manufacturers the ability to adapt to change faster. For example, Hytera easily reassigned one of its production lines to manufacture disposable face masks, a product outside of its usual wheelhouse. A system that could react to real-time data from changing markets facilitated the pivot.

Prior to COVID-19 economic challenges, Industry 4.0 was expected to create nearly $3.7 trillion in value by 2025. Manufacturers looking to keep production moving despite the pandemic might find that they can learn and implement many lessons from smart manufacturing. Weaving these technologies gradually into the fabric of processes can increase adaptability now—and build a more resilient future.

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