Rawal, Aditi ORCID: 0000-0001-6546-8577 , Mason, Peter, Stoyanov, Stoyan ORCID: 0000-0001-6091-1226 , Bailey, Chris and Huber, Jurgen (2024) A prognostic and health management approach using colour fade to determine the condition of silk in a museum display environment. Journal of the Institute of Conservation. pp. 1-20. ISSN 1945-5224 (Print), 1945-5232 (Online) (doi:https://doi.org/10.1080/19455224.2024.2347202)

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Abstract

Silk is highly susceptible to fade, often resulting in colour loss to the fabric even when displayed in controlled museum environments. This study applies the engineering-inspired Prognostics and Health Management (PHM) approach to assess the remaining useful life (RUL) of silk fabric in a museum environment, focussing on predicting colour fade as an indicator of degradation. A novel mathematical model is developed to forecast cumulative colour fade of silk upholstery exhibited at the Great Gallery in The Wallace Collection, London. Unlike traditional accelerated aging methods, this model utilises naturally aged samples to estimate the rate of colour change over time. The main contribution of this work lies in the methodology and computational framework for model development using environmental data and conditions of silk in the museum environment. The proposed PHM methodology allows for continuous modifications of the colour fade model to improve accuracy by deploying new data from different silk collections and environments. The article demonstrates a model-based approach for informed decision making in museums regarding display and storage of silk upholstery.

Item Type:	Article
Uncontrolled Keywords:	silk colour fade; modelling; prognostics and health management; remaining useful life; non-invasive and non-destructive methodology
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Related URLs:	Publisher
Last Modified:	06 Jun 2024 09:57
URI:	http://gala.gre.ac.uk/id/eprint/38521

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