Weld strength is crucial to the operation of critical assets like submarines. Defective welds can result in costly repairs, restricted performance, or even catastrophic failures. Naval crews rely on submarines to keep them safe during missions – making vessel quality of the utmost importance.
It’s standard practice in manufacturing for naval submarines and other critical high-value assets to be inspected before going into service to maximize safety, integrity, and reliability. Traditionally, manual UT and radiographic weld testing (RT), often called X-ray inspection, are used to analyze the thousands of welds of newly constructed submarines.
The radiographic weld testing process is similar to medical X-rays of the human body. However, this method requires that other simultaneous construction operations come to a halt during RT inspection to keep workers safe from radiation exposure. Due to the sheer size and scale of submarines, this process can be highly disruptive, time-consuming, and resource-intensive.
Furthermore, the data, analysis, and monitoring capabilities are severely limited for manual UT and RT reporting. The data interpretation is subject to the inspector’s judgment and skill level, and the readings may not be digitized, making it difficult to validate or reference over time.
With physical, printed reports, the data isn’t dynamic for ongoing condition based monitoring and analysis. Typically, once the documents are reviewed, they get stored away in disparate filing locations, making Subject Matter Expertise review, sign-off, and future auditing very difficult. These hurdles within the construction process exacerbate current workforce constraints and delays in construction and maintenance schedules.
In this blog, we introduce steps to modernize the construction processes of critical assets by leveraging robot-powered inspections and deep data insights from software workflows.
Establish a Baseline with Advanced Robotic Technologies
Mark Twain once said, “The secret of getting ahead is getting started.” For industrial asset management, the best way to get a proactive start is by establishing an accurate baseline to form a solid foundation of asset health knowledge.
It’s impossible to accurately forecast, make confident decisions, and develop an effective maintenance plan once an asset is in service when you don’t know where you are starting. Inevitably, you will likely waste time and resources on plans that don’t solve the real problems, either executing redundant, unnecessary maintenance activities or increasing the risk of unexpected failures while in service.
Instead, start by establishing an accurate baseline to understand the condition of the asset and ensure no weld defects are present before it goes into service. This verifies that welds meet or exceed the acceptance criteria and helps to identify issues before they become a problem, going from a reactive maintenance approach to a predictive one. Inspection methods have drastically evolved from traditional manual and X-ray techniques. Now, there are more efficient, safer, and faster methods that provide better visibility into accurate weld health through advanced robotics.
Rapid Auto Weld (RAW) inspection technology is powered by phased array robots that are designed to cover weld seams and heat-affected zones (HAZ) to identify weldment defects, such as lack of fusion (LOF), porosity, slag, inclusions, and cracking. RAW inspection robots continuously collect thousands of readings per linear foot for full-coverage data capture that eliminates blind spots. Specialized encoders track the robot’s location as it scans the weld seam, allowing for repeatable and reproducible inspections in the future.
RAW inspections provide a complete picture of weld health to inform confident decisions and mitigate risks. In addition to improved accuracy, this method is also up to 50x faster than conventional methods, drastically increasing the speed of manufacturing processes.
Leverage High-Fidelity Data for Actionable Decision Making
The high-resolution data captured during the RAW inspection then gets processed and analyzed through an advanced data engine system. This analysis feeds into a software platform to present the data in impactful, intuitive visualizations.
Digitized models of the asset in the platform make it easy to quickly identify specific areas of concern for precision repairs and monitoring. The platform annotates the levels of damage on the model to inform immediate and longer-term repair plans, pinpointing the recordable and rejectable damage points as defined by weld code and standards.
Severely cracked or damaged areas can be re-welded prior to service. Areas with less severe damage can be flagged and monitored over time. By comparing the baseline data with subsequent inspection data, operators can see how problem areas are progressing to inform and prioritize maintenance plans or alter service conditions.
With an accurate picture of weld conditions, operators can ensure that submarines meet or exceed quality standards before being deployed. Faulty welds are identified early in the construction process, eliminating unnecessary risks. This ensures issues are proactively addressed so the asset operates safely while in service.
Not only is quality ensured from the very beginning, but crews become armed with predictive insights. The analytic tools help to proactively plan while maximizing resources and workforces once the submarine is in service. This depth of understanding at the forefront pays dividends by reducing unexpected issues and maintenance cycles in the future.
A Strong Foundation Supports Future Success
It’s important to note that there is a direct correlation between data quality and successful optimization. A software platform is only valuable if it is populated with high-fidelity data. Sparse or subjective data leaves significant vulnerabilities. It’s critical to implement an end-to-end solution that leverages best-in-class inspection technologies, like RAW inspection robots, to power its analytics platform.
Starting with an accurate baseline yields results. Advanced technologies are making construction processes faster while improving asset quality – prior to even going into service. A data-rich understanding of weld conditions helps establish predictive maintenance plans and improves in-service maintenance cycles for optimal reliability, safety, and integrity – today and in the long term.