Introduction 

Asset Integrity Management (AIM) is essential for maintaining the safety, reliability, and performance of industrial facilities by identifying, assessing, and mitigating risks that could affect structural integrity and operations. A core element of AIM is the systematic process of inspections, testing, and monitoring, which helps evaluate the condition of assets over time. One key aspect of an effective inspection program is the identification of appropriate Condition Monitoring Locations (CMLs) — specific parts of equipment or infrastructure where inspections and data collection are performed.  

With the sheer volume of CMLs that may exist across large industrial facilities, each associated with different monitoring activities, managing this data can become a complex and challenging task. AsInt’s AIS Application on SAP Business Technology Platform (BTP) solves this problem by centralizing all CMLs and their historical data, alleviating the load on traditional ERP systems and ensuring easy access to critical information. This centralized system not only supports optimized asset performance but also helps extend the life of critical assets. Through AsInt’s Asset Inspection and CMLs applications, teams can capture inspection readings and analyze historical data, empowering more informed decision-making and more effective asset management. 

Challenges in Asset Inspection 

Industries across the globe face a set of common challenges when conducting asset inspections. Understanding these hurdles is crucial in recognizing the value of a robust inspection management system. Key challenges include: 

• Inconsistent Inspection Processes: One of the most significant barriers to effective asset inspections is the lack of standardized inspection checklists. Without standardized procedures, inspections are often left to the discretion of individual inspectors, which can lead to variations in the quality and consistency of the data collected. This inconsistency makes it difficult to compare inspection results over time and across different assets, leading to potentially inaccurate assessments and delayed corrective actions.  

• Data Overload and Disorganization: Asset inspections generate large volumes of data that must be efficiently captured, stored, and analyzed. With disparate systems or manual processes in place, retrieving this data can be a slow and cumbersome task. This disorganization can lead to gaps in asset knowledge, and delay in identifying critical issues, ultimately putting the organization at risk of costly failures or downtime. 

• Lag in Corrective Actions: The gap between identifying asset issues during inspections and implementing corrective actions is often a major bottleneck in many industries. This disjointed process can involve multiple stakeholders and numerous manual steps, causing delays in decision-making and response times. As a result, issues are often not addressed in a timely manner, leading to a decline in asset integrity and increased operational risks. 

How AsInt’s Solutions Address These Challenges 

• Configurability: AsInt’s Asset Inspection application offers configurable options, allowing users to create personalized inspection templates. These templates can include checklists for visual inspections and provide a unified space for recording thickness data with inspection details. The CML template on the other hand provides a space to add multiple CMLs to a single equipment. 

• Seamless Data Synchronization: AsInt’s Integrity Management applications, including Asset Strategy Development, Asset Inspection, and Condition Monitoring Locations (CMLs), are seamlessly connected ensuring automatic data flow into the system. This eliminates the need to re-enter the same information for different analyses, saving time and reducing the risk of errors. 

• Storage and Accessibility of Data: All inspection history is stored efficiently and can be easily accessed through the Asset Inspection & CMLs application. Any thickness data entered into the inspection application is automatically synced to the CML application, where it can be retrieved collectively. Additionally, this data can be extracted for further analysis. The CML application also offers graphical representations of the condition of each monitored location, providing a clear and visual overview of asset health. 

• Attachments for Comprehensive Documentation: Attach related documents, links, and additional visual evidence of the condition of the inspected equipment, structures, or components. Adding attachments enhances the  documentation, aids in prioritizing issues, and strengthens support for the recommendations provided. 

• Automated Critical Calculations: The CML application automatically calculates and displays key values such as minimum thickness, short-term corrosion rate, long-term corrosion rate, half-life, and retirement date, making them easily accessible for equipment assessment. 

• Notification Generation: Inspection findings can be directly converted into notifications and work orders, which can be assigned to the responsible person. The status of these tasks – whether outstanding, released, or completed – can be tracked for efficient follow-up.  

• Roles: Roles can be assigned based on the approval workflow, guaranteeing that everyone involved in the decision-making process is informed of the inspection outcomes. 

Conclusion 

As industrial facilities face growing challenges in maintaining the integrity of their assets, having a robust and streamlined inspection and asset management system is crucial. AsInt’s Inspection and CML applications provide a powerful solution to these challenges by offering configurable templates, seamless data synchronization, efficient storage and retrieval, and automated critical calculations. These features ensure that asset inspections are conducted consistently, data is easily accessible, and corrective actions are efficiently implemented. By leveraging AsInt’s solutions, companies can improve their asset management processes, extend the lifespan of critical equipment, and enhance overall operational performance.