Cloud computing in the industrial sector is exploding as costs shrink, security is enhanced, and decision-makers recognize the tremendous value, particularly when applied to sustainability efforts. Here we discuss trends in this space with Dustin Johnson, Seeq CTO, who heralds a “new generation of efficiency and sustainability.”
Smart Industry: How are cloud-based technologies enabling manufacturers to achieve sustainability objectives?
Dustin: Cloud-based technologies are enabling manufacturers to achieve sustainability by providing three key factors: collaboration, interconnectivity and analytics capabilities. First, the ability to capture knowledge and share it across personnel teams, plants and the globe via a common cloud-based platform has led many organizations to discover that insights and best practices from one area can be applied to several others.
Next, interconnecting databases with cloud-based technologies has enabled many organizations to reduce unplanned downtime, emissions, and operational inefficiencies, while simultaneously increasing yield, reliability, and asset service life.
Lastly, you can’t improve what you aren’t measuring. Cloud-based advanced analytics solutions play a critical role in accessing, cleansing, computing and reporting on sustainability KPIs. The ability to visualize data from various sources makes it increasingly straightforward to communicate actual performance metrics in a timely manner.
Smart Industry: What's exciting in the world of on-prem technology / alternatives to traditional approaches here?
Dustin: A very exciting trend in the world of on-prem technology is the migration of technology from other markets into the industrial space, especially when it comes to data-analytics capabilities that empower existing employees. For example, what used to take hours or days to accomplish via the legacy "extract, transform and load" (ETL) pattern can now be accomplished—even on-prem—in seconds with live interconnections between analytics solutions and data-storage systems.
Live connections to manufacturing data, whether time-series or context data, enables not only always-up-to-date insights, but also curiosity, exploration and collaboration through live and interactive charts and graphs, compared to the static presentations of the old model.
The trend of breaking down barriers between process and business data through greater interconnections will empower a new generation of efficiency and sustainability, enabled by the insights achieved through analytics software marrying the two together.
Smart Industry: What differentiates these types of tools?
Dustin: The shear amount of data being captured has led to unprecedented opportunity to discover insights. It has become increasingly clear that these insights are most accessible when curious individuals have access to digital solutions that present data in an approachable manner, tailored to the needs of their industries. The industry is beginning to realize many projects that previously required several months and significant investment can be accomplished in much shorter timeframes, with minimal investment in modern software tools.
Smart Industry: How do you define "elasticity" in regard to cloud computing? Why is this important?
Dustin: Elasticity simply means that a software solution will grow along with the needs of a business. Our customers have driven us to mature our calculation engine, (the basis of our analytics capability) into a microservices-based cluster architecture that can dynamically scale from one compute node up to many dozens to meet ever-increasing user needs.
Elasticity’s main challenges are feasibility and complexity. Feasibility is a challenge because most software was not designed with scaling in mind, and retrofits or redesigns are prone to failure. Complexity is a challenge due to the maintenance and operations burdens that come along with administering clusters instead of individual servers or VMs. Complexity is the driving force behind the rise of software-as-a-service, where support, administration and reliability are provided as part of the product offering. This approach empowers vendors to develop specialized tooling to manage their deployments.
Smart Industry: Is the concept of advanced analytics changing as we mature in this space? As we get better with data analytics, does "advanced" evolve?
Dustin: Absolutely! When Seeq first started nearly ten years ago, most individuals working with time-series data did so via occasional exports to Excel. Now, these analysts expect an analytics package built specifically for industrial spaces with live connections to plant historians, and excitement is turning toward guided machine learning, monitoring and performance at scale.