Abstract

The research describes the effort to develop a predictive model for coating degradation and substrate corrosion on Army assets. The model incorporates the learning from field surveys of over 15,000 assets and 250,000 components; coating performance in standardized testing; and observations of coating condition as-applied to fielded items. The model outputs would provide a basis to (1) support a Commodity Manager to determine repaint intervals, optimizing expenditures and (2) develop new products / processes (impacting coating performance) increasing life of an asset protective coating system.

Introduction

Coating degradation on Army ground systems represents a significant maintenance cost and effort. The objective of this proposed work is to develop a predictive model for coating degradation and subsequent substrate corrosion on Army ground assets. Provided with a better understanding of the root causes, steps can be taken to reduce corrosion impacts on Army materiel.

Coating and corrosion condition on Army ground equipment is related to Stages of Corrosion (SoC) (Figure 1). These ratings are outlined in TB 43-0213 "Corrosion Prevention and Control for Army Ground Equipment." Data concerning materiel condition is gathered as part of standardized inspections and the results of the inspections are a basis for recommended remedial preservation action.

In general, Stage 1 corrosion conditions can be controlled by the application of Corrosion Inhibiting Compounds (CIC). Stage 2 and 3 corrosion can require both CICs and surface preparation / paint application. Stage 4 corrosion requires part repair / replacement in addition to recoating. Maintenance decisions for specific pieces of equipment are based on consideration of the occurrence of these various stages of corrosion on that gear.

The present effort seeks to develop a model explaining primary contributors to a recommended repair of CICs (only), CICs/spot paint [hereafter referred to as spot paint], or complete repaint [hereafter repaint]. The modeling effort seeks to combine a series of data to create the explanation. Primary sources of performance data include:

• Army Research Laboratory (ARL) data concerning the performance of Army standard chemical agent resistant coating (CARC) systems. This includes knowledge of the development of the original and current CARC systems, laboratory and field exposures of test samples, demonstration projects at various Logistics Readiness Centers (LRCs) and depots and monitoring of field demonstration assets.

• Field inspection data from the Army TACOM-sponsored ground vehicle survey efforts. This program began in 2015 and to date has inspected over 15,000 assets, identified over 250,000 parts having corrosion and coating damage, and contains over more than 400,000 photographs of corrosion and coating damage on parts.

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