Understanding the current state of the asset and verifying its condition are traditionally handled by online and offline inspections in the oil, gas, and chemical industries. There are typically guidelines on how to inspect physical assets, including API 510 (for pressure vessels), API 570 (for pipes), API 653 (for storage tanks), and other international standards.
Data is produced by these inspections in the form of readings, checklist requirements, findings, and recommendations. Images and other specialized output, such as readings from cathodic protection anodes, hydrostatic output, or pressure tests of relief devices, are frequently included with the inspection results.
A Problem Statement and Solution
The majority of the results of inspections are kept on corporate file servers, in an Inspection Data Management System (IDMS) run by a third-party inspection and maintenance contractor, or in centralized databases created by commercially available software.
In each of these situations, crucial equipment information, inspection findings, and important recommendations are kept separate from the work management and enterprise asset management (EAM) solutions. The inspection, maintenance, and reliability managers are prevented from connecting the dots to prevent failures by this centralized approach.
What is the inspection data management system exactly?
The oil and gas industry and chemical processing use inspection data management systems (IDMS) to arrange inspection data for fixed equipment like pressure equipment relief devices, tankage, and piping. These programs can create and manage inspection tasks, gather and keep track of inspection outcomes, and, with proper management, produce trustworthy proactive inspection plans. Today, a lot of IDMS programs also offer Risk-Based Inspection (RBI) capabilities.
Limitations in the Inspection Data Management System (IDMS)
The management of inspection programs is a good use of inspection data management systems, but this is all they are capable of. This narrow focus results in gaps that either remain unfilled or necessitate the use of additional software, which furthers the siloing of data.
The following are some limitations of IDMS programs:
- They do not consider reliability or how each asset affects reliability across the board; they only include inspection data. As a result, it is impossible to truly optimize resources throughout your facility.
- Static data is used by IDMS programs. Since the system does not have live data connections for the assets, updating each asset involves time-consuming manual data entry and analysis.
- The IDMS programs use conservative inspection models. Time-based programs, for instance, are very cautious because they don’t consider risk when making decisions. Programs for Risk-Based Inspection employ conservative risk calculations that allow for further data agglomeration.
Relevant industries must use a variety of programs and tools to manage various aspects of their facilities because an IDMS’s capabilities are restricted to managing inspection programs. What, then, does the future of reliability data hold?
What Will Reliability Look Like in the Future?
In order to increase reliability and maintenance, complex manufacturing systems are constantly working to make smarter decisions more quickly. They must sort through millions of discrete pieces of data stored, for instance, in IDMS, Computerized Maintenance Management Systems (CMMS), and Asset Performance Management (APM) programs before making those decisions. But the fields of data collection, warehousing, modeling, and analytics are still making significant strides. With the help of these capabilities, we have the chance to advance reliability analysis and increase reliability while lowering total maintenance and inspection costs.
Through the use of quantitative reliability optimization, this advancement is made possible. Every data point is connected by the Quantitative Reliability Optimization (QRO) method, which also analyzes the data to create the most sophisticated and precise risk models to date. System-based strategies are then enabled, allowing you to prioritize actions across your entire facility in accordance with market conditions, availability objectives, and/or financial constraints.
All asset data can be connected with Quantitative Reliability Optimization (QRO) to see key performance indicators like availability, risk, and cost. In order to determine the best course of action for units, facilities, and enterprises as a whole, it can also be used to simulate various asset management plans.
- Based on short-, mid-, and long-term reliability goals, all maintenance expenditures are optimized in close to real time.
- Recognize the economic value of each inspection or maintenance procedure carried out.
- Recognize the economic worth of each data point that is currently being collected or may be collected in the future.
- modeling of possible outcomes in close to real time, including the effects of postponed turnarounds, adjustments in feedstock prices, or different capital projects.
- In the event of operating excursions based on reliability, make wise economic decisions.
The development of dependability The management systems we use for data must evolve. This evolution can be found in QRO, which makes it possible to analyze data in almost real time and model effects across numerous systems simultaneously. By combining your IDMS and other asset management systems into one system with QRO, you can improve your reliability and maintenance performance by making better, quicker, and more informed decisions.
Best Inspection Data Management System (IDMS) Softwares
- AsInt CORE Inspection for SAP (IDMS) – Required for Mechanical Integrity Inspections and Thickness Data Management
- SAP Asset Strategy and Performance Management (ASPM)–Optional for Risk and Reliability and Condition Assessments data
- AsInt Mobile CORE Inspection – Optional for data collection of Mechanical Integrity Inspections and Thickness Readings
