Colin McMahon is a senior market research analyst working with PTC’s Corporate Marketing team, helping to provide actionable insights, challenging perspectives, and thought leadership on trends, technologies, and markets. Colin has been working professionally as a research analyst for many years, and he enjoys examining and evaluating just how large the overall impact of digital transformation technologies will be. He has a passion for augmented reality and virtual reality initiatives and believes that understanding the connected ecosystem of people and technology is key to a company fully realizing its potential in the 21st century.
LiveWorx 2023 covered many topics under the giant umbrella of digital transformation. Smart factories, a subset of smart manufacturing, may not have headlined any particular keynote speech, but remained a focus on numerous panels, breakout sessions, and show floor demos.
For those curious, a smart factory refers to taking the traditional factory concept and enhancing it interconnectivity; network-enabled machines working together, providing data and analytics to authorized users and enabling higher levels of productivity. Conversations on smart factories revolved around a common theme: How to effectively deploy and scale the idea of a fully connected and augmented work environment full of diverse hardware applications and numerous employees with different skill sets and focus areas.
This blog takes excerpts from attended LiveWorx panels and combines them into a helpful list of five ways you can start to scale your smart factory from pilot concept to full-fledged operation.
People are the most important element to effective scalability
One of the core messages across panels I attended on smart factories centered on the essential importance of people. The truth that, as of now, employees are at the core of successfully scaling smart factories beyond the pilot stage and into mass adoption. Without a committed, educated workforce, organizations can invest a lot of money into new technology without seeing the full reward for their efforts. It begins with knowing when and where to scale smart factory efforts.
Organizations that just started a pilot program within the last three months, for instance, likely should not have managers calling for the process to be replicated and scaled to regional or global levels. The right mindset around smart factory usage is a curious but measured one: an employee should be able to see the value, but understands that pilot stages exist for a reason and wants to ensure all hiccups and significant barriers have been overcome before taking the initiative further. Education is paramount – not just around specific technology but its implications.
A recent study on digital transformation strategies among different employee groups found numerous disconnects between the executive and frontline level. One of the key insights was to scale properly, all employees must see and understand the long-term potential of smart factories and why the initiative is worth the investment.
Managing business process variability
Every factory is unique, if only in small ways. One facility might have specialized equipment, for example, only used in certain operations. Organizations looking to scale…should not focus on these differentiators first. Instead, prioritize applying smart factory platforms on the most common hardware. Once the solution has been optimized, spreading it from location to location should be easier and make a more immediate, significant impact. It makes much more sense to improve a machine that is 30% of your operational inventory than one that only makes up 2% of total hardware platforms.
Controlling and corralling the immense variability found in factories can be daunting, so we recommend using a sustainability and efficiency mindset. Think practically: What is the smallest amount of work that your organization can do that will yield the largest difference? Most manufacturers worry about financial resources and want to control costs, and this strategy helps ensure that your eye remains on the bottom line. Too often executives can ask for something flashy over something effective. Push back when necessary and focus the sizable investments into core, common business processes found throughout multiple factory locations.
Making sense of technology complexity
Data may be the new oil, but it’s useless without a rig to properly process and refine it into something usable. Many manufacturers already have incredible amounts of data that are either siloed or completely inaccessible. Before a successful smart factory can be replicated, organizations need to ensure they can successfully access, integrate, and translate legacy data (from both IT and OT) into new systems. A common data standard works wonders on this front. It’s one of the reasons our Kepware solution has proven so popular. It is much easier to troubleshoot a problem when you know exactly where all the data is coming from.
Data standardization helps align different teams and different technologies on a common, easily accessible platform, improving transparency and security throughout the facilities. With greater insight into their work, frontline operators and technicians can more easily understand where to focus their efforts, where additional work needs to be done, and which aspects of their success can be counted on to be repeatable.
Once a coherent and dependable data stream has been established, it becomes much easier not only to replicate it/bring more machinery into the system, but new digital transformation initiatives like digital twin—and even industrial metaverse concepts—become possible. It all starts with making sense of technology complexity and seeing disparate parts as one whole ecosystem of operational and information data with a shared purpose: improving factory performance.
Using cloud and edge computing where applicable
When cloud computing first debuted in the manufacturing space, many thought it might be a miracle: Take all your computing and process it somewhere else. The potential is limitless, right? Well, great in theory, but often limited in practice. The bandwidth demands of cloud can prove costly and sometimes the system goes down. If the cloud is offline for even an hour or two, that can lead to a lot of lost productivity.
As a result, many manufacturers are now realigning their priorities. Yes, cloud computing and SaaS platforms still bring significant value to the table, but they should not be a one-stop-shop for all processing and analytics. Edge computing, or data processing near the point of creation, is a terrific way to lessen the cost of cloud while keeping its benefits, and also safeguarding against the hazards of unexpected downtime or (worst-case scenario) a denial of service cyberattack.
The cloud at the edge for manufacturing enables customers to scale as needed, use rapid deployment and innovation, allows for subscription-based pricing models, provides storage, backup, and disaster recovery, and provides reliability and uptime for SLAs. It also enhances the capability for machine learning (AI) programs to provide enhanced data insights more quickly and consistently.
Understanding the security implications of operational technology
Lastly, and this has been alluded to throughout this article, smart factories need to scale securely. There is no magic easy button to ensure your factory is 100% safe from cybercrime and, at first glance, it may sound like a smart factory might increase the likelihood of data breach. After all, connecting OT and IT into a common system makes it easier to bring the whole system down…right?
Yes and no. It’s true, smart factories are vulnerable to cyberattacks, especially without the proper safety and transparency systems in place. Yet these software solutions tend to be newer and inherently more secure than legacy solutions (many of which were created at a time when the cyber landscape was very different). By upgrading and integrating data into a common platform, manufacturers have a level of oversight into factory operations that was not possible before. Successful smart factories can detect, isolate, and reduce the fallout of cyberattacks far more quickly than their legacy counterparts – thus improving protection overall.
But this improvement doesn’t happen in a vacuum. In fact, all of these suggestions tie directly back to the first point: It all begins with people. Despite their name, smart factories still consistently yield to human intelligence and oversight. They are only as strong as the people behind them. When looking to scale your smart factory programs, make sure you’re not overlooking any of these foundational steps. Each brings an important aspect of growth forward, and together they provide a stable path toward acceleration and improved efficiency.
LiveWorx On Demand
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