Industrial plants, especially offshore units, are vast, interconnected systems made up of thousands of physical components that must operate in sync to guarantee safety and reliable production. From piping supports, valves, and flanges to walkways, structural beams, electrical brackets, and the piping networks that run across the asset, each element plays a specific role in maintaining operational stability.
Yet the sheer scale and diversity of these elements create a core challenge: how to manage them all with accuracy, consistency, and agility. This is where the real issue emerges, an overwhelming volume of structural components paired with limited visibility into their actual condition.
In facilities with 10, 15, or even 20 years of operation, maintenance teams must constantly monitor a staggering number of components spread across decks, modules, and confined spaces. On a typical FPSO, the number of items with DROPS (Dropped Objects Prevention Scheme) potential can easily exceed 7,000 components. Many are small, from clamps and pipe brackets to secondary supports, yet each one has the potential to become a critical failure point if deteriorated.
Traditional inspection workflows struggle with this volume. Visual inspections often lack object-level granularity. Spreadsheets become outdated quickly. And most importantly, there is no reliable way to correlate the condition of thousands of elements into a clear, actionable picture of structural risk.
This lack of consolidated visibility is what allows hidden degradation to turn into serious incidents, especially when it comes to the risk of DROPS.
When Corrosion Becomes a High-Energy Threat
Corrosion is a natural and continuous process in offshore and onshore industrial settings, particularly in environments with high salinity, temperature variation, and constant mechanical stress. Over time, corrosion thins structures, weakens bolted connections, and compromises clamps, supports, and secondary fixtures.
What begins as surface rust can escalate into:
- metal loss and perforation,
- reduced load-bearing capacity,
- detachment of components, and unexpected structural failures that lead to dropped objects.
This is where the danger intensifies. Even a small corroded element, a 1 kg bracket, a 500 g clamp, or a loose bolt, when dropped from 5, 10, or 15 meters, becomes a high-energy projectile capable of causing severe injury, major asset damage, and process interruption.
And in aging assets, the number of components susceptible to this type of degradation increases dramatically
Managing DROPS Risk Requires More Than Inspections
Many industrial plants still rely on periodic inspections and corrective maintenance, but effective DROPS prevention requires far more. It demands clear visibility of individual structural elements, the ability to correlate corrosion severity with real dropped-object potential, and a system that prioritizes the most critical fall risks. Above all, it requires a precise view of where intervention is needed first, before degradation escalates into a serious incident.
Most plants don’t have the tools to connect these dots. As a result, teams are forced to react to issues instead of proactively preventing them. This is precisely the gap that Vidya’s technology fills.
Vidya’s DROPS Application: Turning Integrity Data into Action
Vidya’s DROPS Application is part of the Vidya Asset Integrity Suite, a set of integrated applications designed to digitize the entire integrity management cycle.
The suite is built on the combination of Digital Twin technology, spatial computing, contextualized integrity data, and AI-driven analytics, transforming fragmented workflows into structured, actionable intelligence.
Within this suite, the DROPS Application specifically addresses Dropped Objects Prevention, but it does so by leveraging the same integrity foundation used across corrosion, structural, and fabric integrity management.
A Digital Foundation for DROPS Analysis
The DROPS workflow begins with the construction of a Digital Twin populated with engineering data such as weight and fixation height, representing the asset’s structure, layout, and condition.
This digital model is then extended through contextualized reality capture, creating a unified digital representation that combines engineering information with the actual physical condition of the facility. High-resolution visual data is collected across decks, modules, and confined areas, achieving image coverage of more than 90% of the asset, and providing comprehensive visibility of components that may represent dropped-object hazards.
This approach creates an extension of reality, where every relevant element is not only positioned in the Digital Twin, but also visually documented in its real operating context. As a result, potential DROPS-related components can be identified, classified, and contextualized based on key physical and operational attributes.
With this contextual foundation in place, artificial intelligence is applied to analyze the captured visual data and diagnose corrosion conditions across the asset where it becomes possible to identify corrosion features, degradation patterns, and material loss, transforming visual evidence into structured integrity data.
This process enables a consistent and scalable assessment of degradation while preserving full traceability to the original images and asset context.
At this stage, the objective is not yet the DROPS risk calculation itself, but the creation of a reliable, visually grounded, and engineering-consistent integrity dataset, where corrosion findings can later be correlated with weight, height, structural role, and consequence attributes to support accurate DROPS risk analysis.
From Integrity Data to DROPS Risk Intelligence
Once Integrity data is consolidated, the DROPS Application builds on this foundation.
Rather than treating DROPS as a standalone checklist, Vidya applies a dedicated DROPS risk matrix that correlates integrity conditions with real-world dropped-object scenarios.
The system processes each mapped element through a specialized DROPS risk matrix, considering:
- Mass and estimated weight of the element
- Installation height and elevation
- Potential fall trajectory and projection
- Structural role and fixation type
- Observed degradation and integrity condition
- Structural classification (primary, secondary, or tertiary)
- Consequence attributes reflecting the potential impact in case of failure
This approach allows operators to clearly identify elements with an increased likelihood of detachment or failure.
The relationship between corrosion condition and DROPS potential is therefore critical, as corrosion severity, section loss, and degradation mechanisms directly affect dropped-object probability, rather than being addressed as separate integrity issues.
Field Data Collection via Mobile Application
Once the initial diagnosis is established through AI-based analysis and the DROPS risk matrix, inspection activities are strategically planned rather than executed in a reactive manner. Critical areas are identified, and optimized inspection routes are defined using heat maps, ensuring that field efforts are focused on elements with the highest DROPS potential.
Based on this risk-driven planning, qualified inspectors are deployed to the field using Vidya’s Mobile Application, which plays a central role in execution. In the field, inspectors navigate the asset through a 3D model of the asset, making it easier to locate components, understand their structural hierarchy, and assess conditions accurately.
During inspections, data is collected directly at the source, including:
- Visual inspections and condition ratings
- Photos linked to each specific element
- Observations of looseness, deformation, missing fasteners, or abnormal conditions
- Immediate tagging of potential dropped-object hazards and execution of corrective actions when required
All data is digitally captured and structured even in offline environments, with automatic synchronization once connectivity is restored. This ensures there is no loss of context between inspection, location, and structural hierarchy, while enabling instant reporting, full traceability, and immediate availability of data for DROPS risk reassessment and decision-making.
Risk Ranking and Visualization
The output of this process is a dynamic and continuously updated ranking of DROPS hazards, visualized directly within the Digital Twin and planned for execution through the platform’s workpacks.
This visual flow helps operators understand the order of operations, from inspection to decision-making, and reinforces the connection between integrity management and DROPS prevention.
Actionable Decision-Making
With risks ranked and contextualized, operators can:
- Prioritize interventions based on real DROPS exposure
- Focus maintenance resources on the most critical locations
- Track mitigation actions and reassess risk dynamically
- Maintain a clear audit trail from inspection to corrective action
- Have full visibility over thousands of elements
- Prioritized maintenance based on real severity, not assumptions
- Faster cycles of detection, intervention, and mitigation
- Consistent DROPS prevention across complex operations
- Compliance across Regulatory conditions
The Result
Vidya’s DROPS Application transforms integrity data into clear, prioritized, and actionable DROPS intelligence.
By integrating AI-driven corrosion diagnosis, Mobile field data collection, Digital Twin visualization, and AI-based risk correlation, the platform eliminates disconnected concepts and delivers a cohesive, end-to-end DROPS prevention workflow fully integrated within the Asset Integrity Suite.
Vidya transforms DROPS management into a continuous, closed-loop process, one that protects people, safeguards equipment, and strengthens operational reliability.
About the Author: Andre Andrade
