Good Data/Bad Data for FFS Assessments

Introduction

Collecting inspection data is often the most expensive part of performing a fitness-for-service (FFS) assessment on a piece of damaged equipment. This article explores some common pitfalls in gathering inspection data using real-world examples and examines a case study where a small amount of additional targeted data gathering resulted in a significant improvement in the FFS results for a vessel.

Data Requirements for FFS

API 579-1/ASME FFS-1, Fitness-For-Service (API 579) presents the FFS assessment procedure as an eight-step process. In this article, we’ll focus on Step 3: Data Requirements, which can be broken down into a few different areas.

Equipment Details

The first step in gathering data is determining if you have adequate information on the equipment or piping system to perform an assessment. Do you have original equipment design data such as the original code of construction, component dimensions, materials of construction, design conditions, joint efficiencies, status of stress relief, etc.? Ideally, all this information is easy to locate in the equipment file, but if there are gaps, it may be necessary to fill them.

Maintenance, repair, and alteration data, as well as inspection histories and current and past process conditions and operating data, are all valuable to an FFS assessment.

Damage Characterization

It’s difficult to choose an inspection technique if you don’t know what kind of damage you’re looking for! For example, the techniques to inspect for volumetric damage vs. cracking or creep will be completely different. Industry guidance documents like API RP 571 Damage Mechanisms Affecting Fixed Equipment in the Refining Industry and WRC Bulletin 584 Overview of API 579-1/ASME FFS-1 With an Emphasis on Data and Inspection Requirements, combined with knowledgeable staff and experts can help ensure that the inspection techniques match the expected damage and that damage mechanisms of interest aren’t neglected.

To complicate matters further, some technologies like ultrasonic examination (UT) can be implemented in a wide variety of techniques that can identify some damage types but miss others. Let’s assume that all the background work has been completed to determine that the damage of interest is volumetric loss, and it has been decided that straight-beam UT will be used to characterize it. How much data is needed, and how exactly should it be collected? Here are a few questions to consider:

• Will a single-point thickness reading suffice?
• Should we collect a few readings at various locations?
• Should we lay out a grid? If so, what spacing?
• Should we collect the data manually or use automated UT?

While there aren’t always easy answers to these questions, doing some proactive FFS work can be very instructive. Getting your FFS analyst involved early can help direct data collection and save time and money. Even something as simple as calculating a minimum required thickness (t_min) for a component before completing inspections can add a lot of value by helping inspectors in the field make decisions based on preliminary results. For example, if a vessel has a design corrosion allowance (CA) of 0.063 inches, but some proactive work indicates that a particular nozzle neck actually has significantly more margin between the nominal thickness and t_min, an inspector could make a quick call in the field based on that proactive work, to not collect any additional data even though spot readings may indicate that the original 0.063 inches of CA has been exhausted.