Today’s factory floor is a time machine, where the newest equipment relies on technology that didn’t exist when the oldest equipment was built. Bridging those generational technology gaps to create an Internet of Things (IoT) ecosystem is a huge challenge for most manufacturers. But this integration is vital to optimizing productivity, maintenance and efficiency across the plant floor.
PTC has helped countless manufacturers overcome this legacy data integration challenge and create a holistic industrial IoT ecosystem. In this “Integrating Legacy Tools” blog series, we will be examining the milestones, potential pitfalls and strategies that leading manufacturers have used to ensure they’re on the right path towards effectively integrating legacy data with IoT initiatives.
Three Questions to Ask When Exploring How to Integrate Legacy Machines
Figuring out the first steps to integrating legacy data can be intimidating. Like with any complex project, its vital to take an honest look at your needs and ask some hard questions during the exploratory phase. Below are three questions that we’ve found to be helpful to manufacturers kicking off discussions of how to approach a legacy data integration.
Question 1: Aside from legacy-to-IoT connectivity, are my legacy machines working well?
The answer to this question will help determine if you pursue a full rip-and-replace approach, or focus more on upgrading tools through add-on sensors, IoT platforms or other third-party connectivity solutions. If your legacy machines are on their last legs, it might be worth replacing the most outdated assets. New machines ensure that you have the most up-to-date technology and its full benefits: improved performance, improved security and complete scalability for next-gen technologies, such as augmented reality.
However, if your machines are in great working order, a full rip-and-replace will likely hurt more than help. Most legacy tools were built to last and remain lynchpins of the manufacturing floor for decades. A full rip-and-replace involves numerous time sinks: sourcing new equipment, uninstalling current equipment, installing new equipment and ensuring appropriate vendor support, re-training employees and more. The time investment required by rip-and-replace is often prohibitive on its own—let alone the cost involved. This question will be easy for some, and more difficult for others—but a full awareness of your legacy machines’ current productivity and connectivity abilities will provide a baseline for all future analysis.
Question 2: How will my legacy machine data enablement scale to new IoT projects and stay ahead of customer and internal needs?
Conversations around legacy IoT enablement tend to focus on the immediate tasks at hand—just getting machines flowing data is challenging enough. But IoT is useless if it’s not scalable to future needs. After all, having inflexible technology is how this legacy connectivity became a problem in the first place!
Scalability reaches beyond the legacy connectivity solution itself and into IT and troubleshooting support, as well. Usually when legacy data is integrated into IoT, it opens up new ideas for additional data to monitor and additional use cases to pilot. How will your connectivity solution adapt? If you rely on legacy machine connectivity built internally, will those internal resources be able to continuously support future initiatives? Do your internal IT and Operations teams have the bandwidth to stay on top of data connectivity best practices (and implement them before your competition does?). Especially with the fast-pace of software security and ever-evolving viruses, in-house solutions can be high-cost, high-time and high-frustration.
External legacy connectivity solutions, such as IoT gateways and platforms, stay competitive by innovating, relying on market feedback and keeping ahead of users’ needs. Because they are focused exclusively on providing IoT connectivity to assets—including legacy machines—and nothing else, they can often create and sustain legacy connectivity to meet specific goals better than in-house solutions. When exploring different vendors, asking about road maps and how the vendor provides both long-term and short-term value can help highlight if you need their platform, or would be better off with an in-house controlled solution that is strategically developed—or maybe a combination of both. Are you better off relying on in-house knowledge, or would a third-party vendor’s road map (which is usually built to help anticipate market needs) provide better value? Such long-term planning can seem like an irrelevant question at this early stage, but don’t dismiss it with a “we’ll figure it out when we get there” answer.
Some manufacturers find it helpful to start small, with a jump-start project such as remote connectivity, or unique sensors on legacy machines, and see how they can make use of data before bringing a project large-scale. But that large-scale future should always be planned for in the early stages in order to capture full ROI and build high-value, low-cost IoT strategies.
Question 3: How can I optimize legacy equipment data across the whole enterprise?
Powerful data often grows to reach beyond the plant floor. Integrating legacy machines will make previously inaccessible data highly available. In turn, this new data will lead to new KPIs and data-based decisions from the plant floor to the C-Suite. Accessing data alone isn’t enough—how will all this new data be turned into information for stakeholders? And how can you provide a break-down based on roles to create a cohesive picture of operations for different stakeholders?
At its core, the industrial IoT connects the plant floor to the enterprise—enhancing visualization, data analysis and holistic insights so that operators can optimize critical processes and performance. An IoT platform that connects your legacy machines can stretch that data’s reach and enhance role-based visibility into operations for the entire enterprise. The impact on the enterprise as a whole depends on how the data is used, but integrating data from both legacy and modern machines has the potential to enhance decision-making at all levels of an organization.
Answers Leading to Actions
The process of integrating old machines and new can be intimidating. But taking measured, planned first steps and asking the right questions—and answering them honestly—will provide clarity and insight to guide you in the right direction.
Check back next week for the second post in this series, where we’ll look at how to use your answers to those three key questions as a guiding framework when choosing different legacy methodologies.
For more information, download the new “Merging Legacy Equipment with the Industrial Internet of Things: Three Approaches for Integrated Data” white paper.