Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension

Diego Rodriguez-Obando (), Javier Rosero-García () and Esteban Rosero
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Diego Rodriguez-Obando: EM&D Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, Colombia
Javier Rosero-García: EM&D Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, Colombia
Esteban Rosero: Industrial Control Research Group, School of Electrical and Electronic Engineering, Faculty of Engineering, Universidad del Valle, Cali 760032, Colombia

Mathematics, 2024, vol. 12, issue 22, 1-22

Abstract: Several sugar mills operate as waste-to-energy plants. The shredder is the initial high-energy machine in the production chain and prepares sugarcane. Its hammers, essential spare parts, require continuous replacement. Then, the search for intelligent strategies to extend the lifetime of these hammers is fundamental. This paper presents (a) a dynamic data-driven model for estimating the deterioration and predicting remaining life of the sugarcane shredder hammers during operation, for which the real data of the entering sugarcane flow and the power required to prepare the sugarcane are analyzed, and (b) a management architecture intended for online decision-making assistance to extend the hammers’ life by making a trade-off between the desired lifetime, along with a nominal shredder work satisfaction criterion. The deterioration model is validated with real data achieving an accuracy of 84.41%. The remaining life prognostic is within a confidence zone calculated from the historical sugarcane flow, with a probability close to 99%, fitting a lognormal probability distribution. A numerical example is also provided to illustrate a closed loop control, where the proposed architecture is used to extend the useful life of the hammers during operation, adjusting the incoming sugarcane flow while maintaining the nominal work satisfaction of the shredder.

Keywords: data-driven method; deterioration model; extension of lifetime; maintenance; management of lifetime; prognostics and health management (PHM); reliability; reliability adaptive system (RAS); RUL prognostics; sugarcane shredder (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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