Using Industrial DataOps can help asset-heavy organizations create digital twins, which in turn can help organizations move APM into new areas, including the performance and sustainability aspects of their operations.
The way companies use asset performance management (APM) is in transition. Once used primarily for asset maintenance and reliability, APM is now also applied to address performance and durability issues. APM’s expanded role brings additional benefits. But to be successful, organizations often need to adopt more sophisticated approaches, especially those based on digital twins.
Tellingly enough, it’s the plural of “twins”, which means that instead of using one digital twin for a physical asset, there should be a set of digital twins that represent various interrelated elements that have an impact on the overall performance and sustainability of the organization.
And therein lies the challenge that many organizations face when trying to climb the APM ladder. Many systems and the data they produce or use are siloed. This makes it difficult to ensure that every group, every business area, and every digital twin has the data it needs. Enter DataOps, a data management practice focused on improving communication, integration, and automation of data flows between data managers and data consumers within an organization.
Not your father’s APM
Gartner defines APM as an approach that “encompasses the capabilities of capturing, integrating, visualizing, and analyzing data tied together for the explicit purpose of improving the reliability and availability of physical assets.”
And for years, APM has helped organizations improve the performance and availability of specific assets. It has played a vital role in asset-heavy industries including manufacturing, utilities, power generation, automotive, and more.
But there is a new realization that simply implementing APM software and digitizing existing processes is unlikely to improve core operations and deliver the bottom line results executives (and investors) want. require). According to Deloitte, “this appears to reveal a pervasive and narrow view of APM that may miss the link between asset performance, broader maintenance, operations improvements and safety.”
See also: “Googling” your industrial data: correcting research for SMEs
One of the reasons tunnel vision persists is that for many companies, maintenance, operations, security, and compliance organizations operate in silos. And worse, they may even have conflicting goals and motivations.
But this attitude is changing. According to a study by independent research firm Verdantix (and commissioned by Aspentech), “Industrial manufacturers’ priorities are changing. While minimizing asset downtime and maximizing production and quality remain important, sustainability and operational initiatives are becoming complex elements of a company’s strategic objectives. Increasingly, they rely on asset performance management (APM) software to meet the challenges of volatile market demands and supply chain disruptions and optimize overall asset performance.
Adopting this form of APM can help organizations:
- Reduce maintenance costs to improve efficiency and performance.
- Achieve their sustainability and digital transformation goals.
- Meet the challenges associated with the increasing complexity of failures and risks.
As Deloitte notes, “Perhaps the most transformative aspect of this new form of APM is how it can connect enterprise systems, from enterprise resource planning (ERP) to security and quality, including inventory management”.
So what’s stopping organizations from moving to this more holistic form of APM? Many enterprises cannot connect APM to other technologies and data in their enterprise-wide digital networks to unlock its full value.
See also: Digital Twins and IT/OT Convergence Drive the Industrial Internet
The Need for DataOps and Digital Twins
Two key technologies that can help are DataOps and Digital Twins.
DataOps
Let’s start with DataOps. For modern APM to succeed, organizations need to focus on data transparency across the organization. They need data to flow through the organization so that optimal decisions can be made.
It’s a perfect fit for DataOps. According to Gartner, DataOps should use technology to automate the design, deployment, and management of data delivery with appropriate levels of governance, and it uses metadata to improve the usability and value of data in a dynamic environment.
It’s a good starting point. More is needed for advanced APM use cases. Specifically, what is needed is what some call Industrial DataOps, which is about breaking down silos and maximizing the wide availability and usability of data generated in asset-heavy industries.
The convergence of data and analytics has made industrial DataOps an operational necessity. But data requires context if it is to be widely used by different groups and functional areas within and across an organization. To help in this area, a proper DataOps solution should automate data processes and create a central, contextualized source of truth.
Digital twins
APM is based on digital twin technology. They serve the data in a way that matches the business decisions that need to be made. For advanced APM applications, organizations need multiple digital twins because the type and nature of decisions for each aspect of operations are different.
Specifically, what many are realizing is that a single digital twin cannot do everything necessary. Industrial companies need multiple digital twins and an efficient way to populate all of the different types of digital twins with data in a scalable way. Industrial DataOps can provide the data backbone for creating and managing such digital twins.
One last word
Using Industrial DataOps helps asset-heavy organizations create digital twins. This, in turn, can help organizations apply APM in innovative ways to do more than just fix maintenance issues and move into other areas, including the performance and sustainability aspects of their operations.
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