Operations & Maintenance

In the ever-evolving landscape of asset management, reliability analytics has become a cornerstone for informed decision-making. Today, asset owners and operators use reliability analytics to inform themselves about the state of their operational assets. As we navigate the Plan-Do-Check-Act (PDCA) cycle, it's crucial to understand where these analytics fit and how they can drive meaningful improvements in asset performance, cost and risk. 

The PDCA Cycle and Reliability Analytics

Reliability analytics are typically applied in the "Act" phase of the PDCA cycle. This is where we leverage existing data sources to provide a comprehensive context of an asset's condition. By mapping analytics to this phase, we can make more specific predictions and decide how to respond to anomalies, address underperforming assets and determine the best course of action for continued operations. 

Types of Reliability Analytics 

1. Prognostics: How Long Do We Have? 

Prognostics and health management (PHM) is an emerging community of practice.  "Prognostics and systems health management (PHM) is an enabling discipline that uses sensors to assess the health of systems, diagnoses anomalous behavior, and predicts the remaining useful performance over the life of the asset"¹  Prognostics and the community of practice around it, offer some proven and clearly defined ways to apply data science and artificial intelligence. 

2. Statistical Analysis: When Will Failure Happen Next? 

Using mathematical distributions like Weibull and Crow-AMSAA, we can estimate when known failure events might occur within a certain range of uncertainty. This information is particularly useful for assessing risk and defining probability of failure modes.  It is also a key step when preparing for reliability-centered maintenance (RCM) studies and understanding trends in failure modes over time.   

3. Growth Analysis: How It Is Designed to Perform 

Growth analysis, typically conducted by asset designers, involves the improvement of prototypes using a range of mathematical models and testing. This process helps establish baseline performance expectations and identify potential weaknesses before an asset enters service. Having protections that are consistent with how the asset was designed to operate is an important practice, because the intrinsic reliability of an asset is rooted in its design and installation. 

The Role of Digital Twins and Smart Digital Reality  

The market becomes saturated with solutions for predictive analytics.  While it is great to have options, having too many to choose from can be unmotivating.  The Hexagon Smart Digital RealityTM is the continuity of data objects – a digital thread – from conceptualization to design, construction and operation. It embraces the view that the design and installation processes significantly impact an asset's future reliability. By selecting reliability analytics that are aligned to the design of the asset lifecycle, we can set the stage for improved long-term performance. 

Making Informed Decisions  

Asset management professionals play a vital role in decision-making.  When done well, asset management processes should continually compound the organization’s collective understanding of its assets and improve the quality of decisions made at the strategic level.  Reliability analytics support critical decisions throughout an asset's lifecycle, including: 

1. Asset strategies that successfully contain known failure modes 

2. Having a process in place to react to reliability events 

3. Addressing underperforming assets and evaluating improvement options 

4. Deciding whether to continue operating an asset based on the phase of its lifecycle 

The Path Forward  

While the allure of advanced analytics and machine learning is undeniable, it is essential to maintain a comprehensive approach to asset management. By combining innovative technology with proven reliability engineering principles, we can create a more robust and effective asset management strategy.

At Hexagon, we understand the importance of tailoring reliability analytics to your specific needs. Our process helps you determine which types of analytics will serve you best, leveraging the power of our Smart Digital Reality to generate valuable insights from existing asset data.