Vice President Network and Edge Group, General Manager Federal & Industrial Solutions at Intel Corporation.
Working at Intel, I have the unique opportunity to meet with manufacturing leaders from a wide variety of industries, and they all ask the same question: Will a smart manufacturing operation work for my company?
Thirty years ago, I started working at a chemical factory using basic PC infrastructure for planning and management. Today, when I walk onto Intel’s lights-out autonomous semiconductor fabrication factory floor, I see mainly maintenance personnel, and the technicians running the operations utilize a remote operation center (ROC) to oversee production. Although it’s the norm at Intel, many other manufacturing companies are not experiencing the same level of transformation.
There are lots of discussions about what is possible to make a dramatic transformation like ours, but only a few documented case studies to support the “buzz.” I would like to share what is possible with a couple of examples where the “buzz” is alive and working.
One of our ecosystem partners is a human-machine interface system manufacturer that built a smart factory in Italy. They use real-time, autonomous human resource scheduling, resource planning and order updates. Not only have they created an environment for their own use, but they have also allowed other industrial equipment providers to test on the 5G network and prepare products for deployment and use on the production floor.
What makes their automated manufacturing strategy unique is that it is built on solutions based upon industry standards with open architectures. Rather than being dictated to use an integrated, proprietary application set, an open architecture has allowed them to “plug and play” and configure using the best currently available applications. In turn, this has lowered maintenance costs, increased productivity and taken advantage of new business opportunities now and for future changes.
Let me share another manufacturing sector example.
One of our manufacturing customers is using machine vision (MV) to automate quality assurance processes. This technology is enabling the real-time detection of flaws that are not visible to the human eye. Utilizing artificial intelligence (AI) and an open platform, they can actuate robotics based on real-time inference and thus adjust the robot upon defect detection. This solution enabled our customer to reduce production rework, material waste and scrap.
Taking their success a step further, this customer collected videos of their overall operations for further analysis. The availability and transparency of the collected data enabled the employees supporting the factory to create process improvements in their operations, improvements that were not thought possible before.
Here’s an example from the oil and gas (O&G) sector.
Our customer announced that it had brought together five Industry leaders in the OT and IT world to collaborate and deliver on a computing platform, which will be deployed as part of a field trial at a production facility. This initial field trial will utilize more than 2,000 I/O and is scheduled for commissioning in 2023.
This announcement shows that the control industry’s transition to an open, software-defined approach is well underway. It’s worth noting that although our customer is driving this initiative, it is not an industry-specific or custom-designed solution only for O&G. Rather, it’s applicable to all industries and open automation projects.
Another example is the significant momentum we see in the utilities sector.
We’re seeing customers’ grid modernization virtual protection relay and substation virtualization efforts enhancing reliability, safety, security, remote management and edge analytics while significantly reducing capital expenditures and overall operating and maintenance costs.
Since the early 1980s, Intel has worked to transform our manufacturing by investing in automation and digitalization to accelerate production time, ramp capacity with high product quality and be more agile and resilient. The best practice we discovered during this journey was that a smart manufacturing strategy is much more than enabling technology—it is about transforming and digitizing data and its use, processes, decisions, business models and ultimately our people.
Ensuring buy-in within an organization can be mitigated by selecting the right “first project.” A smart manufacturing strategy needs to start with comprehending the challenges that must be addressed and carefully choosing the focus with an eye toward the expected business value. Next, consider a project where reliable data can be used to provide insights that can be turned into actions that alleviate these critical pain points.
I want to finish this article with a couple of points.
The journey to Industry 4.0 shows no sign of slowing, and smart manufacturing continues to be a massive opportunity for organizations to optimize efficiency. Technologies like AI, MV, machine learning, robotics, analytics and 5G open a vast number of application opportunities to lower maintenance costs, reduce rework, improve quality control and more, especially when built on open architecture standards.
The level of automation that we have been talking about is not happening by accident. Industry leaders are driving that level of automation by extensive collaboration, focusing on critical intercept points and driving definitions of technology and standards. When we have transparency of information, updated or new processes and data-driven decision-making ability, we can then drive new business models and outcomes.
We are in the fourth industrial revolution, and I cannot wait to see what we do as an industry.