In energy, petrochemical, and storage tank industries, safety is not a target, it is a non-negotiable requirement. Every equipment that enters a refinery, tank terminal or a petrochemical plant must operate without creating ignition risk. This requirement becomes significantly more critical when operations involve explosive atmospheres such as hydrocarbon vapors, flammable gases or volatile residues inside storage tanks.

At AIS Field, our mission is to bring digital technologies, mainly robotics, safely into these hazardous environments. With ATEX-certified, in-service inspection robots like our RUVI OilDiver, we enable clients to carry out inspection and asset integrity tasks without shutdown and decommissioning, without degassing and without exposing personnel to confined-space risks. This leads to significant cost savings for our customers.

To understand how and why this is possible, this article provides an overview of explosive atmospheres, ATEX certification, hazardous area classifications in refineries and storage tanks, and how AIS Field meets and exceeds these standards.

What is an explosive atmosphere?

An explosive atmosphere exists when a mixture of flammable substances (gas, vapor or dust) and air is present in conditions where a single ignition source can trigger a combustion event. In industrial facilities, especially refineries and petroleum storage tanks, these atmospheres can occur near fuel handling areas, inside or above storage tanks, during transfer operations, inside process units, around leakages, inside floating roof drain sumps etc. Explosiveness is describes by the ignition triangle:

1. Fuel (vapor, gas, dust)
2. Oxygen (air)
3. Ignition source (electrical spark, heat, static discharge, mechanical friction)

When all three are present, an ignition can occur. ATEX standards aim to eliminate at least one element these through rigorous design, testing and certification of all equipment operating in these conditions.

What is ATEX Certification and its Role?

ATEX derives its name from “ATmosphères EXplosibles”. ATEX, IECEx and NFPA/NEC standards form the global framework for ensuring equipment safety in explosive atmospheres. ATEX (EU) and IECEx (international) share nearly identical technical foundations, both based on IEC 60079, and they certify that equipment will not become an ignition source in areas with flammable gases, vapors or dust. ATEX is a legal requirement within the European Union, while IECEx is a voluntary but widely respected global conformity system used across many regions. In the United States, hazardous locations are regulated under NEC/CEC Class & Division standards. Although the frameworks differ in structure [Zones (ATEX/IECEx) vs. Classes & Divisions (NEC)] all three aim to classify hazardous areas and verify that equipment is engineered with explosion-proof and intrinsically safe protection methods. For companies operating internationally, understanding these systems is crucial, as each imposes rigorous design, testing, documentation and marking requirements to ensure safe operation of electrical and mechanical equipment in explosive atmospheres.

ATEX consists of two EU directives:

• ATEX 2014/34/EU (Equipment Directive) – Defines requirements for equipment used in explosive atmospheres
• ATEX 1999/92/EC (Workplace Directive) – Defines safety obligations for employers operating such workplaces

For a piece of equipment to be ATEX-certified, it must be engineered to prevent ignition through mechanisms such as:

• Flame or explosion proof enclosure (d-type): The enclosure withstands an internal explosion without rupturing.
• Increased safety (e-type): No arcs, sparks or dangerous temperatures allowed during normal operation.
• Intrinsic safety (i-type): Limits electrical energy and temperature so ignition cannot occur.
• Pressurization and purging (p-type): Positive pressure inside enclosure prevents entry of explosive gas, generally includes purging cycles with an inert gas before energizing.
• Encapsulation (m-type): Components are fully embedded in resin to prevent contact with explosive atmosphere.
• Oil immersion (o-type): Potential ignition parts are immersed in oil, preventing contact.
• Powder/sand filling (q-type): Components are surrounded by powder to prevent ignition.
• Non-sparking (n-type): Equipment designed to avoid arcs, sparks or hot surfaces under normal operation. Limited to Zone 2 only.
• Dust enclosure (t-type): For dust atmospheres, preventing dust ingress and limits surface temperatures.
• Non-electrical equipment protection (h-type): For mechanical equipment, including constructional safety, control of ignition sources and liquid immersion.

In robotics, implementing ATEX compliance becomes significantly more complex. Unlike static equipment, robotic systems move, use multiple motors and actuators, require sensor payloads, consume varying levels of electrical power, operate with dynamic loads, handle data acquisition, communication and real-time control.

Hazardous Area Classification: ATEX Zones Explained

ATEX divides hazardous areas into Zones based on the likelihood of an explosive atmosphere being present.

Gas/Vapor Zones (G):

• Zone 0: Explosive atmosphere is continuously present or present for long periods
• Zone 1: Likely to occur during normal operation
• Zone 2: Not likely during normal operation, or only for short durations

Dust Zones (D):

• Zone 20: Continuous presence of combustible dust
• Zone 21: Likely presence during normal operation
• Zone 22: Unlikely but possible presence, only for short duration

For hydrocarbon industries, gas zones are most relevant. Equipment that operates inside or near these zones must comply with specific ATEX categories. Zone 0 is category 1 (very high protection), Zone 1 is category 2 (high protection) and Zone 2 is Category 3 (normal protection. The closer to the source of hydrocarbons, the stricter the certification.

ATEX Zones in Refineries and Storage Tanks

Refineries contain a wide range of units and assets with high risk of vapor release. Common ATEX-classified areas include process units, crude distillation, vacuum distillation, hydrocracker, reformers, FCC units, alkylation units etc. These units often include Zone 1 classifications due to continuous or frequent hydrocarbon vapor presence. For example in tank farm areas: storage tank perimeters, floating roof seals, vents, breathing systems and drain sumps often include Zone 0/1 classifications. Understanding these classifications is essential for planning inspections, robotic deployment and maintenance work.

Storage tanks hold large volumes of crude oil, naphtha, gasoline, diesel, jet fuel and other flammable liquids. They present unique hazardous area conditions. Inside the tank, above liquid level is continuous vapor presence and it is classified as Zone 0. Manhole areas are typically classified as Zone 1 and roof and shell areas are generally Zone 2. These may slightly change depending on the tank and terminal design.

Given these classifications, any robot entering a storage tank (i.e. submerged in product) must be certified. This is exactly where RUVI OilDiver stands out.

AIS Field’s ATEX Capabilities

At AIS Field, with over 20 years experience working in refinery and explosive environments, and 10 years of experience in designing ATEX-compliant systems, we specialize in designing inspection robots that operate safely inside explosive or high-risk environments. Our engineering approach integrates a combination of protection systems. These capabilities allow us to develop and use robots suitable for in-service refinery and above ground storage tank operations, something only a few companies globally can deliver.

RUVI OilDiver is our flagship in-service tank floor inspection robot, designed for fuel and chemical storage tanks. RUVI OilDiver is ATEX Zone 0 certified, fully capable of operating in storage tank environments mentioned above.

The products we inspected with RUVI OilDiver so far:

• Gasoline (with and without high benzene)
• Methanol
• Naphtha (both heavy and regular)
• Kerosene
• Jet fuel
• Diesel
• Lubricants

For new petrochemical or chemical products, we perform submergence tests in our workshop to ensure compatibility. For example, RUVI OilDiver system can be used in Xylene storage tanks.

Thanks to this approach, our clients receive safer inspections, shorter downtimes, reduced gas freeing and degassing activities and better compliance with API 653, API 575, EEMUA 159 and EEMUA 247 standards.

Contact us if you would like to see our certifications and to get more information about our engineering approach.

Why ATEX Matters for In-service Robotic Inspection

• Robotic inspection drastically reduces the need for human entry into hazardous zones.
• Avoiding conventional maintenance and shutdown can save millions per tank.
• In-service robots operate without disrupting operations.
• Regulatory compliance is key, for many industrial facilities ATEX certification is a must.
• From the perspective of environmental responsibility: by applying ATEX certified systems, unnecessary hydrocarbon emissions also prevented.

AIS Field ATEX certified RUVI OilDiver system helps facilities achieve all of these outcomes simultaneously.

AIS Field: Leading the Future of ATEX-Safe Robotics

As energy infrastructure becomes more complex, the demand for safer, more reliable robotic inspection will only increase. Explosive atmospheres and ATEX classification are not just regulatory topics, they directly shape how industrial facilities manage risk. As robotics becomes the new standard for in-service and confined-space inspections, the ability to safely operate within ATEX zones becomes a major differentiator.

As AIS Field, we have built our systems around this requirement. Through engineering, strict safety principles and real-world deployment experience, our robots offer unmatched capability in hazardous environments. RUVI OilDiver and our broader family of robotic inspection tools enable refineries and tank terminals to turn the most challenging inspection tasks into safe, predictable and non-intrusive operations. If your facility is seeking safer, faster, and ATEX-compatible inspection solutions, AIS Field is here to support you, with proven systems trusted across multiple continents.

Understanding ATEX Certification and Explosive Atmospheres in Refineries and Storage Tanks: How AIS Field Ensures Safe and Reliable In-Service Robotics yazısı ilk önce AIS Field üzerinde ortaya çıktı.

As one can imagine, partial inspection coverage introduces new challenges in data interpretation and risk evaluation. That is where EEMUA Publication 247 (2025 Edition): Statistical Analysis of In-Service Tank Floor Inspections comes in. The recently published EEMUA standard offers a comprehensive statistical framework for planning and evaluating partial-coverage robotic tank floor inspections. This was a significant and timely development for the robotic storage tank inspection industry.

At AIS Field, we provide oil tank inspections using our ATEX Zone 0 certified robotic system, RUVI OilDiver. Leveraging our experience and expertise, and building on the EEMUA 247 standard, we have developed a proprietary software tool that automates both the planning and statistical evaluation processes described in the publication. Additionally, following partial coverage inspections, evaluating the remaining life of the tank requires Extreme Value Analysis (EVA), as outlined in the API 575 standard. We have also developed a tool that automatically performs EVA following our tank inspections. In this article, we will introduce the key features of our software and the value it brings to tank operators, inspection providers and integrity engineers.

Understanding EEMUA 247

As mentioned, due to the nature of online robotic inspections, 100% of floor coverage is not always possible. EEMUA 247 provides detailed guidance on the optimum coverage and statistical analysis of in-service tank floor inspections using robotic tools. It categorizes inspections into three main types based on the presence and detectability of corrosion.

• Type A: Where no significant wall loss is expected.
• Type B: Where measurable wall loss is anticipated and statistical extrapolation is required.
• Type C: Where wall loss may be severe but isolated (requiring tailored justification).

The standard emphasizes the importance of:

• Corrosion risk assessment (CRA)
• Determination of corrosion density and spatial homogeneity
• Minimum inspection coverage calculations based on detection threshold and corrosion depth
• Use of Extreme Value Analysis (EVA), particularly Gumbel or Generalized Extreme Value (GEV) distributions, to predict the probability of critical wall loss in uninspected areas.

About Our EEMUA 247-Based Software Tool

Our RUVI OilDiver Analytics Software Tool transforms the EEMUA 247 methodology into an intuitive, interactive platform for inspection planning and evaluation. Key capabilities include:

1. Coverage Calculation
2. Distribution Fitting and EVA Module
3. CRA Support and Density Classification
4. Automated Reporting and Visualization

You can see both our coverage calculator and EVA analysis interfaces in the screenshots above.

Why This Matters

In-service robotic inspections, by nature, cannot achieve 100% floor coverage, especially in large diameter tanks with numerous internal obstacles. Our approach, built on the EEMUA 247 and API 575 standards, enables asset owners to overcome this limitation by applying robust statistical analysis to make confident integrity decisions, even when only a portion of the floor is inspected.

In simpler terms, depending on the tank’s geometry and inspection history, we use the EEMUA 247 guidelines to calculate the minimum inspection coverage required for reliable integrity decisions. Once our robot covers that targeted portion, we perform Extreme Value Analysis (EVA) to accurately assess the tank’s remaining life and overall integrity condition. While RUVI OilDiver operates inside the tank, our inspection team also conducts a full API 653 inspection, allowing us to deliver a complete inspection package to our customers. This combined approach adds significant value to our clients’ operations.

By aligning fully with EEMUA 247, the tool ensures consistency, traceability and defensibility of the inspection strategy. Therse are critical elements in regulatory compliance and internal risk management processes.

Conclusion

Robotic inspection technology has advanced rapidly, but the real power lies in planning the inspection and interpreting the data correctly. By codifying the principles of EEMUA 247 and API 575 into our internal procedures and also a software solution, we provide tank operators and service providers with the analytical edge they need to make data-driven integrity decisions.

To learn more about our solutions, feel free to get in touch with our team.

Enhancing Integrity Management through EEMUA 247-Based Robotic Inspection Analytics yazısı ilk önce AIS Field üzerinde ortaya çıktı.

Inspection robots are specialized robotic systems designed to carry out examinations and monitoring tasks in challenging, hazardous or inaccessible environments, often referred to as “field” conditions. Equipped with advanced sensors, inspection robots efficiently collect data to evaluate the condition of critical industrial assets. Such robotic systems are increasingly utilized across various industries, including manufacturing, construction, energy and infrastructure maintenance. At AIS Field, we specialize in developing and deploying mobile robotic solutions specifically tailored for asset inspection in the energy, oil and gas sectors.

What are the benefits?

The deployment of inspection robots in industrial facilities offers numerous benefits, mainly in economic, technical, health and safety (HSE) and environmental dimensions.

Firstly, traditional inspection methods typically involve human intervention, which often leads to substantial operational downtime. Human inspections tend to be slower, less consistent, and prone to error compared to robotic systems. Furthermore, many assets must be taken offline to enable human entry. For example, storage tanks must be emptied, cleaned and inspected manually, a process that can last several months and incur significant costs. Inspection robots, however, can operate efficiently in confined spaces, under liquid or at elevated heights, significantly reducing downtime and associated expenses.

Secondly, even when human access is possible, data collection capabilities are considerably limited. Inspection robots, on the other hand, can continuously collect and transmit real-time data from multiple sensors, offering comprehensive coverage that human inspectors simply cannot match. This robust and detailed data collection is invaluable for implementing advanced Risk-Based Inspection (RBI) strategies, process optimization and machine learning applications, ultimately enhancing asset integrity management.

Health and safety considerations provide another compelling argument for robotic inspections. By eliminating the need for human entry into confined spaces or performing work at dangerous heights, inspection robots significantly improve worker safety. Thanks to ongoing advancements in digital technology, inspections can now be carried out autonomously or via remote control, allowing human personnel to focus on more critical and less hazardous tasks, ensuring their safe return home to their families.

Lastly, there are many environmental benefits linked to inspection robots. Preventing downtime reduces emissions and waste generated from traditional inspection processes. For instance, taking a storage tank offline requires venting, resulting in harmful emissions, and the disposal of sludge at the tank bottom poses environmental hazards. Robotic systems can either delay or entirely prevent these procedures, significantly mitigating their environmental impact.

How AIS Field can help you?

At AIS Field, we provide specialized robotic inspection services tailored to address the unique needs and challenges of our clients. By integrating cutting-edge digital technologies with practical industry demands, our goal is to deliver innovative, high-value solutions. We are committed to enhancing the technical, economic, social and environmental aspects of real-world challenges through continuous innovation in robotic inspections. Check our robotic systems from the following link: AIS Field Services.

Inspection Robots yazısı ilk önce AIS Field üzerinde ortaya çıktı.

While it is widely known and accepted that inspection and maintenance are crucial aspects of asset management, Data Quality is observed to be a somewhat neglected part of these procedures. In the absence of Quality Data, effectiveness of inspection and maintenance may be significantly reduced. Inspection results are reached by processing obtained data and where and when maintenance is to be conducted is based on such results. Thus, if the data is shaky, the whole practice of asset management is affected.

Low quality data, even when it may be used to ensure compliance, does more harm than good. Low quality data may cause inspection to be ineffectual, since false results may incorrectly predict failure when asset is healthy or vice versa. Thus, low quality data can endanger asset integrity, cause OHS and/or environmental risks and incur unnecessary costs on the asset owner. Low quality data may be caused by various factors such as faulty or obsolete equipment, inexperienced operators or difficult conditions.

Getting quality data is ensured by working with quality equipment, experienced personnel and using cutting edge methods utilizing the latest technology. AIS Field’s main purpose is obtaining high quality and abundant data for industrial assets in a quick and safe manner. In this post, we go over the important aspects of the concepts of Data Quality and Quality Data and how AIS Field can help you in obtaining high quality data.

What is Quality Data?

Quality data can be defined as information that is accurate, reliable, consistent, and fit for its intended use. It is critical for making informed decisions. Quality Data can be defined as having several qualities.

First of all, it is accurate. Accuracy means being reflective of real-life condition. No data can be 100% accurate, but it should be as accurate as possible. Quality Data has as little deviation as possible and thus it is gathered with the method that is proven to be the most accurate.

Secondly, Quality Data is complete, in the sense that it contains all the data points necessary. Even the most accurate data is not Quality Data if it lacks information on some of the most important points.

Thirdly, it is consistent and repeatable. If a measurement is not repeatable, ie. it changes from measurement to measurement, it cannot be deemed reliable.

Fourthly, it should be timely. In operating conditions, using old data may be very costly. These are the most crucial qualities of Quality Data.

The Importance of Data Quality

Industrial asset management includes maintenance and upkeep procedures and lifecycle management. Neither of these can be efficient in the absence of Quality Data. Maintenance activities, such as preventive, predictive, and corrective maintenance, depend on Quality Data to assess the condition of assets, predict failures, and schedule repairs.

Without accurate and timely data on asset performance, maintenance teams cannot identify early signs of failure and conduct predictive maintenance. Predictive maintenance itself is based on the availability of Quality Data. If data is not available or Data Quality is low, false negatives or false positives may occur, leading to either unexpected failure or unnecessary maintenance, both of which are unwanted outcomes. If data is known to be reliable, asset lifecycle can be more easily managed, and maintenance schedules may be more accurately set. That way, assets can be kept in operation in the safest and least costly manner for the longest time.

The Cost of Poor Data Quality

Nowadays, the importance of data collection in industrial asset management is well understood. Periodic NDT is also regulated by the authorities and thus mandatory. However, not every data is created equal. NDT data on the assets are based on the quality of the equipment as well as the experience and skill of the NDT operator. When data collected does not have the features needed to be deemed Quality Data, it is poor quality data. Poor quality data can still be useful and may even be mostly correct enough, however, the most important feature of poor quality data is that it is not reliable.

Poor quality data may cause false positives for defects, in the sense that data indicates non-existent defects. This phenomenon may lead to unnecessary maintenance to be conducted, meaning costs and downtime. On the other hand and maybe even worse, poor quality data may fail to detect an existing defect (false negative). When that happens, maintenance can be skipped when it is indeed needed, leading to unexpected failure. Most of the time asset owners are aware that data quality is low, thus they do not fully depend on inspection data and conduct more maintenance than indicated by the data. The extra cost of these extra maintenance sessions adds up to a great number during an asset’s lifetime. 

How to Gather Quality Data?

As mentioned before, Quality Data requires quality operation. Ensuring data accuracy is only made possible by using the method proper for the operation. In addition to that, the device should be functioning correctly, should be correctly calibrated and should be used properly.

Ensuring data completeness is another aspect of gathering quality data. For a dataset to be complete, data gathering should have been made from many different locations. Sometimes these locations require working at heights or working in confined spaces.

In short, data completeness can be costly and sometimes dangerous. It requires more man-hours and additional equipment. Consistency and repeatability in data is another issue that can be overcome by experienced operators and good inspection practices. However, human operators are not machines; thus, they will always have a certain level of inconsistency. As we will see in the next section, AIS Field’s robotic solutions make all these significantly easier to achieve and ensure quality data.

How AIS Field can Help You?

AIS Field’s RUVI Oildiver and RUVI Wallker robots are automated robotic solutions for gathering data safely, quickly and accurately from industrial assets. When applicable, robotic NDT has numerous benefits over traditional NDT practices. Robots are configured to reach the accuracy needed for the NDT operation that is to be conducted.

Our robots provide fully repeatable and consistent data, which is impossible for human operators. In addition, robotic NDT gathers tens of thousands time more data than that is possible for human operators. This data can be gathered without any safety precautions, any scaffolding, or, in the case of RUVI Oildiver, even in-service. To ensure Data Quality and obtain Quality Data, robotic NDT is the next step forward.

Robotic NDT data is not presented as specific points, but a full mapping of the inspected asset. That way, robotic NDT provides reliable and thorough data and makes it possible to base efficient maintenance planning upon it. 

The Importance of Data Quality for Asset Management yazısı ilk önce AIS Field üzerinde ortaya çıktı.

Traditionally, monitoring the condition of storage tanks involved periodic manual inspections, which could be time-consuming, error-prone, and limited in scope. Manual inspections involve tank drainage and significant downtime. Moreover, traditional paper-based reports do not present a full picture of the tank condition.

In addition to that, these paper-based reports contain hundreds of pages of results, which often makes them quite time-inefficient for the asset owner to analyze in detail. Moreover, since every periodic inspection results in a new report, and tank farms often contains dozens if not hundreds of tanks, not to mention other types of assets, handling reports may become overwhelming.

In today’s world, digital transformation has become a key driver of innovation and efficiency across various industries. And thanks to digital transformation, messy paper-based results can be digitally transformed into soft data. And AIS Field works to ensure your storage tank inspection and maintenance procedures are digitally transformed. In addition to helping in the gathering of Quality Data with its robotic solutions, AIS Field’s advanced software solutions help in transforming conventional bookkeeping into digital bookkeeping. Unlike paper-based data, processing software-based data is incredibly easy.

For example, for any given tank, time based inspection data can be quickly obtained from the software and then processed via analytical tools to make possible efficient predictive maintenance. In this post, we briefly go over some of the many benefits of digital transformation in storage tanks. We also demonstrate how AIS Field helps you in achieving digital transformation and making use of its benefits.

What is Digital Transformation?

Digital Transformation is the process of integrating digital technologies into areas of a business or organization, fundamentally changing how it operates. Digital Transformation in heavy industrial asset management has the potential to decrease costs, increase efficiency, ensure safer operation, mitigate environmental risks and reduce downtime. For industrial asset management such as storage tank management, there are various ways in which digitalization can be utilized to increase efficiency and safety.

For example, with smart sensors, around-the-clock monitoring of parameters such as temperature and pressure is possible. Many data analytics and AI tools may be utilized to make possible predictive maintenance and lifecycle
management. Moreover, maybe one of the most promising and crucial methods of digital transformation is Digital Twin software, which provides a virtual representation or simulation of a physical asset. Digital twins provide a baseline upon which all the other digital and AI technologies can be built. AIS Field has developed its own Digital Twin software to present its robotic NDT reports.

Avoid Potential Failures With Digital Transformation

Digital transformation practices have many benefits in preventing failures before they even occur. Digital Twin software we provide with our NDT reports helps customers in multiple ways.

Firstly, thanks to Digital Twin integrated reports, customers can, instead of going through hundreds of pages of reports, see all the results in one software screen and navigate in a point and click fashion.

Secondly, Digital Twin software makes possible indefinite storage of all the old data without using any physical space. Not only does this prevent any data from ever being lost and makes finding data significantly easier, but it also makes processing time-based data incredibly easy.

As mentioned, Digital Twin software can be easily integrated with any data processing method including machine learning models. Digital transformation with Digital Twin software saves data collection and safeguarding from being a personal endeavor and transforms it into a corporation-level procedure. Change in personnel will have no effect on the integrity of data since any authorized personnel can easily reach data and understand where and when each data point in the Digital Twin software belongs. That way, predictive maintenance is made much simpler and easier to achieve thanks to plentiful Quality Data being available to everyone.

How to Digitalize Tank Maintenance Process?

Digital Twin software provides the baseline for safer and more optimized storage tank maintenance. Once robust tank inspection data is obtained and Digital Twin is constructed, a full mapping of all the critical zones will be available. Thanks to the visual interface, the problematic areas can be easily seen. The abundance of data and the ease of integrating analytical methods will make predictive maintenance much simpler to carry out.

Digital Twin software will accompany the tank all through its service life. Every inspection and maintenance, no matter how minor, will be saved into the software. That way, a very large amount of data will be available for the planning team. Different types of data from different points of asset life can be processed via a large variety of methods to make possible efficient lifecycle management.

How AIS Field can Help You?

First step of digital transformation is data collection. Any digital analytical method will need high quality data. In fact, one of the most important advantages of digital analytical methods is that they can handle big data. However, even the creation of big data requires advanced methods.

For example, it is well-known fact that human operators cannot physically collect which would make asset mapping possible. On the other hands, robots, thanks to their automated movement and high-performance sensors, are able to obtain tens of thousands of data points from asset surface.

That way, mapping is possible. AIS Field’s RUVI Oildiver and RUVI Wallker robots are able to map large surfaces very quickly and collect robust, accurate and plentiful data. AIS Field provides the tools to present and analyze these data as well. To present these large amounts of data in a user friendly way and store it indefinitely, we utilize our Digital Twin software. To analyze this data and reach predictive maintenance results, we utilize advanced data analytics, including cutting-edge machine learning models.

The Importance of Digital Transformation for Storage Tanks yazısı ilk önce AIS Field üzerinde ortaya çıktı.

Avoiding operational failure in storage tanks is especially important due to the risk in case of failure being great. If a tank failure occurs, tank contents may leak into the environment, causing severe environmental pollution. In addition to that, since most tanks are used for holding volatile and/or toxic compounds there are high OHS risks in case of a leakage. Lastly, a tank failure means tank will be decommissioned for a significant amount of time, meaning lost profits.

Luckily, inspection and maintenance techniques have come a long way; thus, the possibility of a catastrophic tank failure is minimized. However, maintenance itself continues to incur risks and costs on asset owners. Tanks are huge pieces of equipment with very large interiors. If maintenance is needed in the interior, the massive amount of product inside should be moved elsewhere.

Traditional inspection methods do not provide an opportunity to gauge whether or not tank maintenance is necessary, without taking the tank out-of-service. On the other hand, AIS Field’s current portfolio helps asset owners to know precisely whether or not and where maintenance is necessary. In addition, thanks to the developments in computational methods, we are able to help the customers in performing predictive maintenance. That way, asset owners can plan ahead their maintenance, without wasting their precious time and resources with unnecessary out-of-service inspections and maintenance.

The Importance of Regular Inspections

Inspections have a close relationship with maintenance. For storage tanks, NDT inspections are used to determine if, when and where maintenance is required. Without scanning of the structure via NDT, it would be almost impossible to properly and efficiently carry out inspections in such vast structures.

Regular inspections ensure long-term safe operation for industrial assets. NDT has no detrimental effect on structural integrity, it is rapid, low-cost and reliable. For storage tanks, inspections such as ultrasonic thickness and weld inspections are performed routinely, and are mandatory for asset owners, as per API 653. In-service UT inspections of tank walls are possible in some cases; on the other hand, tank floor inspection with traditional methods is not possible due to the impossibility of human operators to collect data under such conditions.

This means, conventional methods dictate that tank is taken out-of-service if bottom is to be inspected. This creates the problem of impossibility of separating inspection schedules from maintenance schedules and avoiding unnecessary downtimes.

AIS Field’s RUVI Oildiver solves this problem. In addition, AIS Field’s RUVI Wallker can climb interior or exterior tank walls for thorough UT inspection. This not only brings reduction of OHS risks but also brings significant cost reduction since with this method it is now possible to inspect tank walls without scaffolding. 

What is the Ideal Regular Cleaning and Maintenance Schedule?

As is explained thus far, ideal interval for cleaning and maintenance for an asset owner is actually to never do cleaning and maintenance, since these incur great costs. This desire clashes with the difficulty of making sure of asset integrity. For storage tanks, since traditional methods cannot ensure integrity of tank bottom without emptying tanks for inspection, maintenance schedules are the same as inspection schedules, since once the tank is opened, it makes sense to do maintenance as well. As a rule of thumb, Inspection-maintenance interval is around 10 years; however, it can also be altered due to various factors. However, if reliable in-service inspection is possible, the ideal time of maintenance is exactly when a structural defect is detected and no sooner. 

It is not yet possible to perform in-service maintenance on a tank interior. However, if presence or lack of structural defects can be detected in-service, the need for maintenance can be shown to be non-existent. In other words, best case scenario is to do in-service inspections and postpone maintenance if the structure is found in a good condition and only start in-service repairs when it is not.

AIS Field’s solution, RUVI Oildiver, is precisely aimed at doing just that. Since our robotic inspection makes possible in-service scanning of tank bottom floor, asset owners can ensure safety and compliance without putting their tanks out-of-service.

Tips for Optimal Storage Tank Maintenance

Since typically there is limited time allocated for tank maintenance, rendering the maintenance as efficient as possible is paramount. The key concept in efficiency is resource allocation. Thus, the resources necessary for maintenance (manpower, equipment etc.) should be allocated to where they are the most needed. To do that, prior planning is essential.

However, for a successful planning procedure, quality data is a must. Quality data on the other hand can only be obtained via quality inspection. If abundant and accurate inspection data is available, the planner will be able to allocate available maintenance resources to where they are the most needed. Without quality data, maintenance procedure may run into problems, can be more costly or take more time. Examples of the lack of quality data can be given as too few data points, low repeatability, low accuracy, lack of data from critical areas etc.

How AIS Field can Help You?

To reach maintenance best practices, Ais Field can help you with obtaining quality data. Main aim of AIS Field’s robotic solutions are to provide our customers with quality inspection data.

First of all, AIS Field robots reach hard-to-reach or dangerous places without any OHS risks, thus we are able to provide data from everywhere.

Secondly, AIS Field robots are able to carry out full mapping of your asset with tens of thousands of data points, a feat simply impossible for human operators.

Thirdly, robotic inspection has a much higher repeatability compared to human operators.

All things considered, not only does AIS Field robotic solutions help you in reaching regularity in inspections with minimal cost and health hazards, they also provide high quality data to make maintenance planning mush more efficient.

Maintenance Best Practices for Storage Tanks yazısı ilk önce AIS Field üzerinde ortaya çıktı.

In actuality, RUVI Oildiver can be configured to reach to and get signal from even dead corners. However, the main issue for in-service inspections of the critical zone is the heavy sludge that is typically present in such locations. This sludge makes it difficult to conduct healthy thickness readings from the corners. On the other hand, corners are important locations that need to be inspected. In fact, due to the extra stress that occurs in these corners, they are classified by API 653 as “critical zones”. These critical zones in storage tank floors made it necessary for us to develop an additional solution for their inspection.

We believe in a holistic approach in robotic inspection. The ultimate goal is to inspect the whole tank robotically, minimizing human error, inspection time, environmental impact and OHS risks. Since our robots specialize in providing high quality solutions for specific industry pain points, different problems in industry are best challenged by different robots. If one robot has a limitation in its scope, this limitation can be remedied by another supplementary robot.

This is our approach to the critical zone inspection in storage tanks. While RUVI Oildiver inspects the general tank floor, the best quality for critical zone inspection can be obtained by a robot fully dedicated for this task. For the tanks in which critical zones are inaccessible by RUVI Oildiver, we have developed PAars Annular Ring Inspection Robot, designed specifically to inspect critical zones in storage tank floors. In this post, we aim to provide information about critical zone inspections and our robotic solution PAars.

Where is The Critical Zone in a Storage Tank?

Critical zones are defined as the lower corners of the storage tanks, 3 inches (7.6 cm) of inside edge of the shell. Critical zones are not only under the weight of the shell, but they are also prone to sludge build up. This area also contains the weld between tank shell and tank bottom. Due to these issues, critical zones are typically built with a higher thickness. The unique situation of the critical zones of storage tanks makes their inspection more crucial. Higher stress means higher probability of defects occurring and a general higher rate of loss of thickness. 

How to Inspect the Critical Zone?

In conventional tank inspections, since the tank is emptied and the bottom is cleaned prior to inspection, critical zones can be inspected just like the rest of the tank floor. However, in service robotic inspection of the storage tank bottom floors has a weak point for the critical zone inspection in storage tanks.

Our RUVI Oildiver robot has 32 UT probes, collecting comprehensive data from the tank floor. If the critical zone is relatively clean, ie. has low levels of sludge, RUVI Oildiver’s probes can be configured before operation to obtain critical zone data.

However, the critical zone is most of the time not clean and has significant sludge build-up. This makes it difficult for the robot to get near the critical zone for inspection and also makes it difficult to obtain accurate UT measurement data due to sludge interference. Due to this, we have presented our dedicated robot PAars to inspect the critical zone.

Does Inspection Report Quality Matter?

Above all else, inspection aims to collect accurate data. Accurate data can be used to gauge the estimated lifetimes of industrial assets, predict when, where and how failures are going to occur and prepare future maintenance roadmaps. Our robotic inspection solutions provide abundant, accurate, repeatable data very quickly.

However, just as important is a high quality report that is processed by expert personnel that provide valuable insights. In the age of big data that we live in, data processing is nearly as important data gathering. Another aspect of high quality reports is that they provide compliance. AIS Field’s in-service robotic inspection solutions for storage tanks, RUVI Oildiver and PAars Annular Inspection Robot, provide reports for storage tanks are fully compliant with the mandatory API 653 regulation. AIS Field’s NDT Level II and Level III experts prepare comprehensive reports from our robotically obtained data, to provide valuable insight to our customers as well as to ensure their compliance.

How AIS Field can Help You?

Our critical zone inspection robot, PAars Annular Ring Inspection Robot, is specifically designed to solve the issue of critical zone inspection is storage tanks. Unlike RUVI Oildiver, PAars does not need to dive the tank; it can inspect from the outside. It is an automated scanner attached to the tank shell wall.

PAars is equipped with the integration of ultrasonic phased array and 0-degree. Once attached to the tank bottom edge from the outside, PAars is able to detect plate defects from the tank interior, up to 1 meter away from the tank shell. It is able to characterize defects up to 40cm away from the shell. If we remember that the critical zone is defined as 7.62 cm away from the tank shell, it can be asserted that PAars provides a definitive solution for the critical zone inspections for storage tanks.

PAars service can be provided standalone, but it is typically offered as supplementary with our RUVI Oildiver to provide a full picture tank bottom inspection.

Storage Tank Floor Inspection – The Critical Zone in Storage Tanks yazısı ilk önce AIS Field üzerinde ortaya çıktı.

Optimizing maintenance process for storage tanks is crucial due to various reasons. Firstly, most maintenance processed are tightly regulated. If we take storage tanks for example, API-653 inspections are closely tied to tank age and are mandatory. Moreover, there are tight regulations on exactly how the maintenance is to be conducted.

Secondly, routine maintenance is one of the best ways to extend an asset’s maximum lifetime and ensure its operational integrity. Tanks are expensive pieces of equipment which are used for holding valuable commodities. Thus, optimizing their maintenance process will pay off in the long run. 

As competition grows in heavy industry, firms have found it lucrative to invest in cutting edge technologies which give them advantage over their rivals. Asset integrity is one of the most crucial fields for continuous, safe and profitable operation of an industrial facility. However, it cannot be said that it is getting the attention it deserves. Many facilities are reluctant to modernizing their routine inspection protocols.

Why Facilities are Reluctant to Modernizing Their Routine Inspection Protocols?

The main cause of concern is the vast amount of protocols already present in a plant. Heavy industrial facilities are more often than not quite large and complex, thus tinkering with already operational procedures can feel like a bad idea at first. Another concern is that heavy industry is a risky operation, thus operators have a tendency to err on the safer side and stick to older technologies. Lastly, new technologies are not always fully compliant with the regulations, which means that they cannot be implemented such regulation-heavy industries.

However, when it comes to adopting new technologies, a very well known fact is that early adopters get the lion’s share of the benefits and position themselves far ahead of their competitors. The longer companies hesitate, the more they risk being left behind in a rapidly evolving market.

Early adoption accelerates efficiency, boosts safety, and unlocks unprecedented levels of predictive insight. Those who take action first will thrive, while the ones who drag their feet will find themselves desperately playing catch-up, with increased price but decreased return. The market rewards bold moves, not hesitation. In this post, we go through why one should invest in the optimization of maintenance in storage tanks and how we can help you in alleviating your concerns.

The Importance of Modernizing Maintenance in Storage Tanks

When the time of maintenance comes, stressful days commence. Time is tight, costs are high and facility is losing money daily. In the case of storage tanks, there is possibly a very high opportunity cost of maintenance, since production in refineries is tied to available storage space.

Conventional inspection and maintenance all requires taking the tank out of service. This is because bottom is not reachable  while the tank is filled with toxic and explosive liquid. But fortunately, new technology brought in robotic NDT practices, which made it possible to reach the bottom while in-service. Our RUVI Oildiver robot, thanks to its ATEX Zone 0 certification, is able to do fully API-653 compliant tank bottom inspection.

Moreover, our RUVI Wallker robot is able to climb tanks’ outer walls for full thickness mapping. Thus, modernizing storage tank maintenance practices means the customer is able to develop more efficient, safe and low-cost maintenance procedures without any downtime.

Common Maintenance Challenges

Challenges in tank maintenance are well-known for those who are in the sector. One cannot just simply get into tank, the tank should be emptied at first. This alone is a huge problem since if there is no back-up tank, the production will suffer. However, even when this is not a problem, planning for it is also brings in a significant problem.

Afterwards, preparing a tank for this process is long and cumbersome. Degassing, cleaning and sludge reduction are mandatory practices as per regulation. The tank is also to be ventilated via ex-proof fans for several weeks. One thing to underline again is the presence of toxic and explosive solids, liquids and gases/vapors during this whole process. These cause significant environmental risks, OHS concerns and handling costs.

In short, not only is conventional inspection and maintenance impractical, it is also dangerous, dirty and takes a long time. Optimization of conventional maintenance processes is not an easy task, since there are many aspects of it that can go wrong, adding it unpredictability.

Utilizing Technology to Overcome Challenges

In today’s world, robotics and AI are the names of the new revolution and cutting edge innovation is achieved in many sectors via integrating new developments there to that specific sector. Our team, well aware of all the short-comings of current conventional methods thanks to their vast field experience, have done just that. We utilize robotics and AI to decrease human errors, get procedures done faster, build more stream-lined inspection and maintenance operations and most importantly operate in places not possible for human operators thus minimizing the danger to human life.

Robots work with precision simply impossible for human operators, can collect hundreds of thousands time more data than human can, can safely climb to heights, can work in confined spaces, can dive into toxic and explosive fluids. Utilizing AI makes possible to analyze big data for predicting error mechanisms, making possible much more efficient maintenance practices. In the long run, putting together the vast amount of data collected by robots with the analyzing capabilities of the AI models, it will be made possible to build new and unprecedented inspection and maintenance protocols for storage tanks as well as other industrial assets.

Strategies for Optimizing Maintenance Process for Storage Tanks

Making the transformation to robotic extremely straightforward, the robotic inspection of storage tanks is much easier to manage than a conventional inspection. First of all, robotic inspection does not require thorough planning. Since the tank is not to be emptied, no back-up tank is needed. Tank content is left intact, so there is no need for ventilation or sludge management. There are also next to no emissions.

Robotic inspection can be decided only a couple days prior and is quickly finalized. If tank is found in good condition, fully API-653 compliant reports will be received without ever opening the tank. In case a tank requiring maintenance is detected, prior robotic inspection will have given thorough information on so that maintenance can be planned accurately and can be conducted quicker and more efficiently. Thanks to all these reasons, a robotic transformation for tank inspection and maintenance is extremely easy for and works wonders for optimizing maintenance processes for storage tanks.

How AIS Field can Help You?

As mentioned above, there are admittedly difficulties of attempting a robotic transformation for optimizing maintenance processes for storage tanks. To minimize the uncertainty, the company that is offering a robotic solution should be aware of the complexities present in heavy industrial processes.

The AIS Field team, with its vast field experience, is not only a robotic service provider but also is able to act as a consultant regarding the big picture of a plant. Working with such a seasoned team minimizes the risks of a robotic transformation while maximizing its benefits.

Our solutions are not cookie-cutter ones, but are tailor made on the field for real industrial conditions. Our robots are made to solve problems, and are designed to be fully compliant with regulations such as API-653. All our solutions are designed, manufactured and operated by us, thus they are fully optimizable to each customer. With its R&D capabilities, AIS Field is constantly developing new innovative solutions for pressing industrial problems.

Optimizing Maintenance Process for Storage Tanks yazısı ilk önce AIS Field üzerinde ortaya çıktı.

What is a Tank Inspection?

Inspection means careful examination and scrutiny. In an industrial context, inspection procedures are almost always guided by regulations. Industrial assets are not only expensive pieces of equipment, they also provide constant cash-flow; as long as they are in service. This is the main idea of inspection: to prevent future time lost. In that sense, inspection pays for itself. Being important industrial assets, storage tanks are inspected to ensure safe, uninterrupted and long operation.

Why is Tank Inspection Important?

Industrial tanks that store oil, oil derivatives or chemicals are expensive assets. A tank that is small to average in size costs at least several hundreds of dollar to build with most tanks that are currently operated on the field exceeding 1 million dollars in construction cost. To make the most this significant investment, tanks should stay operational at all times. Inspection is the only way to prevent unexpected leakages and ensure uninterrupted operation. Moreover, leakages in fuel and chemical tanks cause significant environmental hazards. This makes tank inspection crucial for green industry and zero emission.

How Often Should a Tank Be Inspected?

As per API-653 regulations guiding tank inspection, storage tanks require full inspection for thickness loss and corrosion every 10 years under normal conditions. Inspections can be carried out more often than that if the asset owner predicts a heightened risk.

How to Inspect a Tank?

Tank inspections are crucial for safety, reliability and longevity of industrial storage units but the method of inspection can make all the difference in efficiency. Traditional Non-Destructive Testing (NDT) methods like Visual Inspection (VT), Ultrasonic Testing (UT) and Magnetic Flux Leakage (MFL) have been the norm for years. But these methods require tanks to be completely emptied and taken out of service for several months which although effective introduces downtime and risks to environmental and safety factors.

Thanks to technology, robotic systems like the RUVI OilDiver offer an alternative. These systems can inspect the tank floor without emptying the tank so companies can stay in operation. In the next section we will look at traditional methods and the RUVI OilDiver, the benefits and the advancements in tank floor inspection.

Traditional Methods

Non-destructive Testing (NDT) is the industry standard since it makes possible to gather a significant amount of data without causing damage to the structure. Tank inspections are generally made via visual inspection (VT), Ultrasonic Testing (UT) and Magnetic Flux Leakage (MFL). These methods detect the damages that are present in the structure so that they can be fixed afterwards. Since it is impossible for these methods to inspect tank floor when the tank is full, traditional methods require the tank to be fully emptied and put out-of-service for several months, but this is considered as a decent trade-off since this procedure helps to prevent future unexpected failures. However, environmental and safety risks that arise from this process cannot be fully mitigated.

Ruvi OilDiver – A Robotic System Designed for Tank Floor Inspection

Recently, technological advancements made it possible to carry out tank floor NDT without emptying the tank. Our advanced system, RUVI OilDiver, is able to dive into a fuel tank that is full with explosive content, thanks to its Zone-0 ATEX certification. This makes possible UT and visual inspection of the tank floor, without taking the tank out-of-service for even one day.

Ultrasonic Thickness Measurement and Corrosion Mapping with RUVI OilDiver

RUVI Oildiver provides API-653 compliant reports. It can fully map the tank floor with both thickness and visual data, detecting exactly where and on which floor plate corrosion had occurred. Thanks to the highly accurate thickness data, asset owners can gauge if and where repairs are required. Data received from RUVI Oildiver inspections makes Risk Based Inspection (RBI) possible. Robotic Inspection can determine “good actor tanks” which do not and are unlikely to require repairs and maintenance. That way, inspection and maintenance budget can be diverted to “bad actor tanks” which need the most attention.  This is also crucial for insurance purposes since the data can be used to reduce uncertainty and decrease the insurance premiums.

API 653 – What is API 653 Standards for Tank Inspections

API 653 is an industry standard set by the American Petroleum Institute (API) for the inspection, repair, alteration and reconstruction of aboveground storage tanks for petroleum and other liquids. While the design and construction of these tanks are covered by API 650, API 653 is for the ongoing integrity of the tanks. It specifies inspection frequency, types of inspections and what to do if any defects are found. API 653 compliant inspections are mandatory for safe tank operation and is often required by national regulations in Turkey. It also emphasizes documentation so API 653 is a must have framework to ensure tanks are safe, reliable and in continuous service.

API 653 says in-service tanks must be inspected every 5 years. More detailed inspections including Non-Destructive Testing (NDT) of the tank floor for thickness and corrosion must be done every 10 years under normal conditions. In the past this would mean taking the tank out of service for a long period of time but with advanced robotic systems like the RUVI OilDiver you can do it without any downtime.

What is API 653?

American Petroleum Institute (API) 653 is a standard that guide inspection, repair, alteration, and reconstruction of aboveground storage tanks of petroleum products and other liquids. Note that initial tank design and construction is guided by API 650. API 653 stipulates the frequency and types of inspections required to ensure the integrity of storage tanks. In addition, if issues are identified, maintenance and repair of tanks are also to be made in accordance with API 653. API 653 also provides guidelines for documentation; thus, an API 653 compliant inspection and reporting is necessary for tank operation. Turkish regulations also cite API 653 and require API 653 compliant inspections.

How often is API 653 inspection?

Every five years, in-service inspections are to be carried out. Under normal conditions, every ten years, bottom-plate thickness NDT is required for above-ground tanks. As mentioned, these traditionally require lenghty out-of-service NDT operations. Not anymore, thanks to the RUVI OilDiver.

Tank Inspection – Everything You Need to Know About Tank Floor Inspection yazısı ilk önce AIS Field üzerinde ortaya çıktı.

NDT, being very widely used and depended on technology, is always quick to incorporate new technological advancements to improve its robustness. Two most exciting fields that have seen significant technological advancements recently are robotics and artificial intelligence (AI). As well as incorporating robotics into NDT with solutions such as RUVI Oildiver and RUVI Wallker, AIS Field also works to incorporate AI for better NDT analysis and reporting performance.

Traditional Methods vs. Robotic Methods

Traditional approaches have several shortcomings which are time-consuming analysis, high potential for human error, limited adaptability to dynamic environments and high dependency on skilled operators. Machine learning can enhance traditional NDT techniques by automating defect detection and minimizing human error, also cutting costs.

The advantages of Machine Learning in NDT are:

• Automation and Efficiency: Machine learning models, especially neural networks, can quickly process large volumes of Non-Destructive Testing data and provide rapid, accurate defect detection.
• Improved Accuracy: In most cases, machine learning makes possible better analysis than humans. In our article titled “Development and Comparison of RNN, LSTM and GRU Neural Network Models for Automated Eddy Current Inspection of Heat Exchanger Tubes Using Real World Industrial Data”, recently published and presented in BINDT 2024, the machine learning models developed (RNN, LSTM, GRU) achieved accuracy levels over 98%, outperforming traditional rule-based software and human inspection (with GRU achieving the highest accuracy of 99.26%).
• Cost Savings: Automating the inspection process reduces the need for manual analysis, thus lowering operational costs by saving time and reducing the need for highly specialized personnel.
• Reduced Human Error: By removing the need for subjective human analysis, machine learning can reduce inconsistencies in reporting and ensure a more standardized evaluation process.

Machine learning in NDT at its current state also faces some challenges and has some limitations which will be mitigated over time with advancing technology:

• Data Quality and Availability: Machine learning models require extensive and well-labeled datasets to perform effectively. Gathering and labeling real-world data (such as the 10 years of data used in the AIS Field study) can be resource-intensive​.
• Computational Demands: Training complex models such as deep learning architectures (RNN, LSTM, GRU) can require significant computational resources, both in terms of time and hardware (e.g., GPUs)​.
• Bias and Overfitting Risks: Without careful curation of training data, machine learning models may develop biases, leading to overfitting on specific types of defects or equipment.

Recent Developments and Case Studies

AIS Field R&D Department contributes to the scientific literature on the use of machine learning in NDT. In our recent study, machine learning models were used for the data analysis and reporting of eddy current testing (ECT) in heat exchanger tubes.

Real-world inspection data from 89 heat exchangers have been gathered. From the data, more than 100.000 potential defect areas have been extracted using advanced signal processing methods. For the machine learning study, three bidirectional neural network architectures have been used: Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTMs), and Gated Recurrent Units (GRUs). It has been determined that GRU is the most accurate model among the three with 0.9842 general accuracy, followed by LSTM (0.9770) and the least accurate was RNN (0.9689). The ranking stayed the same for both ferrous and non-ferrous models.

False positives exceeded false negatives, underlining the prioritization of safety by the machine learning models. It has been shown in the study that with GRU models it is possible to reach 98.55% defect detection for ferrous and 99.89% for non-ferrous tubes. These results show that machine learning models significantly outperform human experts as well as traditional rule-based software systems in both accuracy and speed.

The Future of Machine Learning in Non-Destructive Testing

Increased Integration with Robotics: Machine learning models will likely be integrated into robotic systems for autonomous inspection. One example of such a development is AIS Field’s efforts to make use of machine learning to localize robots and reduce the time needed for NDT data analysis in storage tanks​. This integration can reduce the need for human involvement in hazardous environments.

Predictive Maintenance: Machine learning could enable the transition from reactive to predictive maintenance, predicting when and where defects are likely to occur based on historical data and real-time analysis.

Enhanced Defect Characterization: Moving beyond detection, future advancements in machine learning could allow models to characterize the type, size, and severity of defects with greater precision, enabling more targeted maintenance strategies.

Machine learning offers significant advantages for NDT, from improved accuracy and cost savings to increased safety through automation. While there are challenges, particularly regarding data quality and computational demands, the potential for further advancements makes machine learning an essential tool for the future of NDT.

As industries continue to digitalize and automate, the role of machine learning in NDT is likely to grow, transforming how inspections are conducted and contributing to safer and more reliable industrial operations. Moving maintenance from reactive to predictive will do wonders for better workplace security and lessened environmental impact. In that sense, the future of NDT indubitably lies in the incorporation of robotics and AI.

Machine Learning in Non-Destructive Testing yazısı ilk önce AIS Field üzerinde ortaya çıktı.