Capital goods and their components have to be clearly identifiable along the entire value chain for the transparency of the market. This is necessary for the confidence in the component quality and the enforceability of accountability. Identification procedures must be counterfeit-proof for a reliable transparency. This allows trustworthy traceability and an enhanced quality protection. Identification procedures are only counterfeit-proof, if the identifiable features cannot be reproduced, even after the publication of the technical process for the identification. Therefore, an identification procedure called Batch-Fingerprint is investigated. The procedure considers stochastic characteristics related to the elemental composition of the component. The Energy-dispersive X-ray Spectroscopy (EDX) and Optical Emission Spectrometry (OES) are used to analyze these component properties. In this paper, the influencing factors to evaluate the Batch-Fingerprint are analyzed. The paper discusses the difference between material dependent, process dependent and measurement dependent influencing factors. The factors are analyzed regarding their influence on the elemental composition and the resulting evaluation of the fingerprint. With the knowledge of the important influencing factors for the evaluation, the elemental composition can be measured correctly. Thereby, a diagnostically conclusive fingerprint can be detected, which can be identified even in the final product. This provides quality protection for manufactures and customers. Manufacturers can thus be protected against unauthorized liability actions, since the origin of a capital part can be traced at any time within the lifecycle of the product. Customer can use the Batch-Fingerprint for unique identification of the capital goods. All customers involved in the value chain can test the originality and the quality of a supplied component to protect themselves against counterfeited components.
Cichos, D., & Aurich, J. C. (2017). Quality Protection of Capital Goods Based on Inherent Component Characteristics. In Procedia CIRP (Vol. 63, pp. 598–603). Elsevier B.V. https://doi.org/10.1016/j.procir.2017.03.345