A major change is coming, one that will be felt from the factory floor to the boardroom. Along with the shift from global outsourcing models to regionalized supply chains, the next milestone for manufacturers is the adoption of intelligent automation solutions that enable greater flexibility, resiliency, and higher ROI.
Automating factories has historically been complex and time-consuming, often done on a project basis and in a bespoke manner for an individual production line or facility. Automation goals typically centered around driving up production volume and driving down labor costs. Automated lines were essentially “fixed,” with limited ability to modify once in place. In periods of stable demand, companies were willing to make these tradeoffs.
Today, being the high volume producer is no longer enough. Companies who embrace “software-defined automation” can more easily reprogram a line, adjust production output as market conditions shift, even replicate operations from one factory to another. They can reduce the downtime and start-up costs that are often prohibitive when considering a capacity expansion. Advances in automation also make it possible to build multiple SKUs on a single line, employing software-based instruction sets that can be selected and run by line operators right on the factory floor.
This type of programmability — coupled with modular hardware and adaptive robotics — allows manufacturers to maximize use (and reuse) of their production lines. It protects their investment in automation while driving up the resiliency of their operations. It’s a win-win for companies working to stay competitive in an ever-changing macro environment.
Greg Ratcliff - Chief Innovation Officer at Vertiv
I’m going to cheat a bit and name two that share a common technology foundation. The first is the virtualization of manufacturing automation through digital twins that enable process optimization, predictive maintenance and other analytic models that can significantly reduce equipment downtime.
Simultaneously, machine-level intelligence will become more centralized. Instead of distributing intelligence across every piece of automation in the factory, it’s going to be more effective and scalable to centralize some of that intelligence at the factory level, supported by cloud computing. This will allow manufacturers to really unlock the value of AI.
The technology foundation for these two developments is an edge computing layer that sits between sensors and system-level intelligence and the cloud. IoT is already driving a surge in edge computing in manufacturing, but we are still very early in this evolution.
Manufacturing environments will require more sophisticated computing, communications, and infrastructure systems to support automation’s processing, continuity, and latency requirements. What we’re seeing across all edge applications is the need for purpose-built micro data centers tailored to the application that enable fast technology deployment and simplified management. In manufacturing, these micro data centers may need to be located on the factory floor, requiring a higher level of environmental and power protection than is necessary in some other edge applications.
Fully integrated and enclosed micro data centers can enable IT operation in harsh environments and will become increasingly important in supporting the evolution of factory automation.
Stephan Pottel - Manufacturing Specialist EMEA at Zebra Technologies
The next big milestone in factory automation is the challenge of combining the workforce and technology in an efficient and ergonomic way — let's call it orchestration.
It's about orchestrating workflows, human labor and intelligence with technologies like autonomous mobile robots to take on the sorts of tasks people don't want or need to do, machine vision systems that automate compliance and quality control processes with advanced cameras and software and radio-frequency identification (RFID) to track inventory. These sorts of technologies leverage and augment human skill and empower frontline workers.
Ergonomics plays a key role in this process of orchestration, with things like mobile computers and wearable scanners that provide real-time insight at the edge and create a more natural and comfortable way of working that seamlessly connects workers, assets, data, and workflows.
These technologies will help orchestrate the right balance between augmenting frontline workers and automation of workflows.
Hans Thalbauer - Managing Director, Supply Chain and Manufacturing Industries at Google Cloud
The next big milestone in factory automation will be when artificial intelligence is fully utilized on the factory floor. While utilizing AI in factories is not new, deploying it at scale is a challenge and making it more accessible will help businesses rise to this challenge. AI is most commonly used for predictive maintenance on the factory floor, with tools like Google Cloud’s Visual Inspection AI automatically detecting product defects throughout the assembly process.
Right now we are finding that a lot of U.S. factories are using older technologies because manufacturing operators don’t believe AI is mature enough. At Google Cloud, we are working closely with manufacturers to educate them on how AI can help make their businesses more efficient and sustainable. AI can help deliver significant and quick ROI to businesses by reducing inspections costs, rework and scrap materials. And by reducing scrap materials, businesses can reduce waste materials and in turn make a factory more sustainable.
Ande Hazard - VP of Manufacturing Solutions at AT&T Business
Advanced manufacturing facilities are using Industry 4.0 technologies, like AI-driven automation and IoT, throughout their production process to improve overall efficiencies. By gaining visibility into operations through automation and predictive analytics, manufacturers are able to develop effective revenue growth opportunities, while ensuring a more efficient, safe work environment. The structural advantages of these Industry 4.0 platforms enable manufacturers to meet the rapid change in customer demand, while minimizing downtime and avoiding production disruption. However, achieving factory automation using IoT generates a tremendous amount of data, involving many interconnected technologies and endpoints — requiring manufacturers to have a higher level of reliable and secure computing power to process it.
The transition to 5G networks — bringing fast speed, low latency, and mass connectivity — will supercharge the changes already happening in manufacturing with automation, while opening new areas for innovation. 5G will ultimately provide the power and consistency needed for intelligent Industry 4.0 infrastructure, creating a secure foundation to efficiently move data out of corporate silos, keep it safely within the walls of the facility, and use it to make smarter business decisions.
While the intersection of digital transformation and automation is changing the face of the factory, we’ve only scratched the surface of the revolutionary changes coming to manufacturing. We believe the heart of Industry 4.0 is next-generation networks and connectivity, so the challenge for factories now is that they need networks that can keep pace with developing Industry 4.0 technologies as they migrate to 5G.
Tim Householder - Manufacturing Industry Adviser at World Wide Technology
The word “automation” in the manufacturing industry, and many industrial sectors, invokes images of robots performing functions along a production line, quality testing, continuous motion of products, and autonomous vehicles moving through a plant or distribution center.
While these are examples of physical automation, one of the next major milestones for automation will be creating value for the business from the data that is utilized from these processes, equipment/devices, and networks that make it all possible. Data will provide value differently to varying stakeholders within an organization, but the challenge will be the success realized from the ability to extract data from the environment and processes and then normalize, transform, and visualize it — all while informing other processes within the operations leveraging technologies like artificial intelligence and machine learning.
The business outcome to this milestone is a connected environment that provides a holistic view of processes, tools, and efficiencies. Additionally, the understanding and value from the data allows for more informed decision-making across areas of the business including supply chain and logistics, production scheduling, manufacturing, and procurement. This then sets the foundation for delivering next-generation solutions such as co-bots (human and bot workstreams) and digital twins. The immediate need to develop a vision and strategy to achieve both physical and data automation is driving the industry to seek a more sophisticated labor force and modern, secure manufacturing facilities.
Written by: Kevin McAllister, Research Editor, for Protocol.