Prescriptive Maintenance

Unlocking Hidden Industrial Data Value

In today’s asset-intensive industries, data fuels operational excellence, efficiency, innovation and sustainability. From the shop floor to the boardroom, organizations are increasingly recognizing the critical role of industrial data management in driving value creation.


 

Balancing IT and OT Strategies

Chief Digital Officers (CDOs) and other C-level executives across the industrial sector are working to achieve a delicate balance between IT (informational technologies) and OT (operational technologies) strategies while tasked with navigating the business transformation inherent in industrial digitalization initiatives. The business imperatives can be grouped into three distinct categories: holistic risk management in volatile and uncertain markets, margin improvement in challenging environments and sustainability goals in conjunction with profitability and productivity targets. The question quickly becomes which of these are IT and which of these are OT imperatives? Many customers are struggling with defining the problem comprehensively and identifying the right combination of talent, technology and process to address the problem.

One thing customers agree with is that data is integral to their industrial digital transformation initiatives; where they differ is the level of maturity they have achieved in managing that data and deriving business value from it. Often an organization will build data lakes in which data from disparate sources is aggregated. These data lakes are capturing data at an accelerating rate and rely on a highly-skilled workforce to put that data to good use. At the same time, these skilled personnel are difficult to cultivate, and the issue is further exacerbated by a rapidly-evolving workforce. The data lake that previously had so much potential becomes a data swamp with less visibility and more complexity than you started with.


 

Liberate Your Industrial Data

Today’s leading companies are making better, faster business decisions using data-driven information. How? By unlocking the hidden value of industrial data using AspenTech Inmation™, which connects people, machinery, plants, logistics and applications so that they can better communicate and collaborate using existing data.

To connect these different strands of information, a unified, flexible, high-performance system is needed to provide corporate-wide, real-time, information flow. AspenTech Inmation does all of this and more, securely streaming data and then contextualizing and transforming it for use from plant maintenance to the executive suite.

AspenTech Inmation is a real-time, scalable solution with enterprise historian capabilities. It leverages heterogeneous data without disrupting production systems so users have access to actionable information for better business decisions. Providing connectivity to operational data from multiple data sources, it enables decision-makers across the plant and around the world to have access to actionable information any time, any place and on any device they choose.


 

The Evolution of Industrial Data Processing

Industrial data processing encompasses the collection, storage and analysis of data for the connected enterprise. As technology advances, so does our ability to harness data for actionable insights:

  • Data Collection and Integration. At the heart of effective data management lies robust data collection. Organizations must seamlessly gather data from various sources, including sensors, equipment and production processes. The AspenTech DataWorks product suite provides solutions like Aspen InfoPlus.21®, which collects, merges, stores and retrieves large volumes of time-series data. This data integration ensures a holistic view of operations, enabling informed decision-making.
  • Asset Modeling and Visualization. Understanding assets is crucial for optimizing performance. AspenTech Inmation offers a centralized data management system. By creating asset models, organizations gain insights into asset health, utilization and maintenance requirements. Visualizations enhance understanding, allowing stakeholders to identify patterns and anomalies.
  • Archiving and Accessibility. Data retention and accessibility are vital. AspenTech solutions enable efficient archiving, ensuring historical data availability for compliance, troubleshooting and predictive data analytics for utilities and other industries. Whether it’s process data, maintenance logs or performance metrics, having a reliable archive is essential.
  • Analytics and Decision Support. Raw data becomes valuable when transformed into actionable insights. AspenTech DataWorks facilitates advanced analytics, including predictive maintenance, anomaly detection and optimization. These insights empower operators, engineers and executives to make informed decisions, improving overall efficiency.

 

One Solution. Zero Compromise.

Industrial data management isn’t just about numbers; it’s about unlocking insights that transform businesses. AspenTech DataWorks embodies the vision of data-driven value creation and empowers capital intensive industries to thrive in an ever-evolving landscape. As a comprehensive solution, from data ingestion to visualization, it covers the entire data lifecycle. So, whether you’re on the shop floor or in the boardroom, embrace the power of data—it’s your compass to success.


 

FAQs

What is industrial data management?

Industrial data management is about unlocking insights from your data that transform business. AspenTech DataWorks embodies the vision of data-driven value creation and empowers asset-intensive industries to thrive in an ever-evolving landscape. As a comprehensive solution, from data ingestion to visualization, it covers the entire data lifecycle.

Why is industrial data collection important?

At the heart of effective data management lies robust data collection. Organizations must seamlessly gather data from various sources, including sensors, equipment and production processes. Aspen InfoPlus.21 collects, merges, stores and retrieves large volumes of time-series data. This data integration ensures a holistic view of operations, enabling informed decision-making.