Speaker
Description
The safe lifecycle management of conventional ammunition is a continuing challenge for defense organizations due to aging effects, variable storage conditions, incomplete historical records, and the need to maintain both operational readiness and safety assurance. In this context, non-destructive diagnostic data can provide a practical basis for more transparent and evidence-based lifecycle decisions. This paper presents a condition-based and risk-oriented approach for lifecycle safety management of conventional ammunition using non-destructive diagnostic data as the primary source of technical evidence. The proposed concept integrates condition monitoring, interpretation of degradation-related indicators, and structured risk evaluation into a unified decision-support logic applicable across storage, inspection, handling, maintenance, and disposal planning stages.
The approach is designed to support the identification of early warning signs associated with physical degradation, to reduce uncertainty in technical assessment, and to improve prioritization of safety-related actions under limited inspection resources. Diagnostic observations are translated into condition indicators and further mapped to risk-informed management categories that can support continued storage, intensified surveillance, handling restrictions, maintenance planning, or withdrawal from service. Particular attention is given to the consistency, traceability, and practical deployability of the proposed assessment workflow in real stockpile management environments.
The main contribution of the paper is the formulation of a transferable framework that connects non-destructive technical evidence with lifecycle safety decisions in a structured and auditable manner. The proposed approach does not rely on invasive examination procedures and is therefore suitable for applications where safety constraints, resource limitations, and operational continuity must be considered simultaneously. The paper argues that embedding non-destructive diagnostics within a condition-based risk management framework can improve stockpile safety, strengthen decision transparency, and support more rational lifecycle planning for conventional ammunition.