【Smart Manufacturing 2.0 series】

1.   Smart factories have arrived

Nowadays, the strategical importance of smart factories is undeniable, as early adopters have reported operating more efficiently and driving more to the bottom line. In the United States alone, 86 percent of manufacturers believe that smart factories will be the main driver of competition by 2025. Furthermore, 83 percent believe that smart factories will transform the way products are made.

Research consistently reveals improvement in cost, throughput, quality, safety, and revenue growth through the deployment of smart factory technologies that combine capabilities in industrial internet of things (IIoT), cloud and edge computing, artificial intelligence (AI) and vision systems among others.

Deloitte conducted more than 40 qualitative interviews with a global array of manufacturing leaders, staff, and professional services providers with hands-on experience of smart factory transformations across diverse industries. Drawing from those interviews and building on Deloitte’s in-depth, collaborative study with the Manufacturers Alliance for Productivity and Innovation (MAPI), which investigates the state of smart factory deployment across the United States, and our initial 2017 smart factories study, this report offers insight into lessons that can be drawn from leaders’ experiences with smart factory transformations.

We’ve divided our findings into two sections: firstly, positioning smart factory initiatives for value: lessons in smart factory transformations from those who have done it.  Secondly, turning lessons into outcomes: realizing the value of smart factory transformations.
 

2.   Positioning smart factory initiatives for value

So, how will companies discover underlying change management themes from smart factory initiatives? Leaders need to consider the following four points:

• Human-centered design based on real user needs
• Top-down, bottom-up approach
• Diverse teams with a broad variety of skill sets
• Ongoing support and learning
   

Regarding to the "smart factory-specific" themes: how to integrate information technology (IT) and operations technology (OT) in the smart factory?

• Connectivity as critical
• Managing the reality of multiple devices
• Bridging the IT/OT divide

3.   Turing lessons into outcomes: Realizing the value of smart factory transformation

How can companies move from lessons learned from smart factory transformations toward outcomes, and the ways smart factory capabilities make processes and organizations better? There are multiple opportunities to recognize value: from illuminating data and bridging the smart factory to the broader DSN(digital supply network) , to driving improved versions of current processes, to layering advanced technology for operational excellence, to scaling beyond the four walls of the facility to the broader ecosystem.

Therefore, we need to leverage always-on connectivity to drive greater value to realize smart factory transformations. In order to achieve this objective, we need to illuminate the hidden factory; leverage current systems in new processes to achieve operational excellence; harness AI and other advanced tools to get to the next level; scale smart factory functions throughout networks, ecosystems and DSNs (digital supply networks).

4.   Applying lessons to scale up

Though there may be no single approach to smart factory deployment, lessons can be learned from each approach that can lead to significant value. These range from people-centric experiences such as change management, putting humans at the center of capabilities, and managing skill diversity, to broader operational and technological considerations such as the criticality of connectivity in often-challenging environments, the diversity of assets, and the need to bridge the IT/OT divide.

Finally, all these insights can come together to drive a vision for a successful smart factory future, informed by the wisdom of experience and the impact it can lead to. Powered by data from throughout the connected factory, leaders can create new processes to optimize operations and leverage technologies such as AI to make sense of data and anticipate, sense, and respond to shifts in the environment. After piloting and testing these capabilities in discrete locations, organizations can start small, learn, and adapt—and then scale their solutions more broadly. Scaling beyond the four walls to other facilities throughout the network or ecosystem can allow value to be recognized exponentially.