DETERMINATION OF THE ROUGHNESS IMPRINT COEFFICIENT IN COLD ROLLING WITH CONSIDERATION OF THE RELATIVE WORK ROLL SERVICE LIFE AND THE INFLUENCE OF DIFFERENT ROLLING EMULSIONS

Abstract

This article examines the topical issue of quantitatively assessing the formation of the surface micro-relief of steel strip during cold rolling on continuous tandem mills. It has been established that the key factors determining the roughness of the finished rolled product are the surface condition of the work rolls in the final stand and the tribological conditions determined by the type of rolling emulsion. Since experimental control of intermediate roughness under industrial conditions is limited, the authors propose a universal approach to assessing the roughness imprint coefficient Kprint. The research methodology is based on the introduction of the relative roll operating time parameter L, which allows data to be standardised across campaigns of varying durations. A comparative analysis was carried out of five types of rolling emulsions: the base ‘Universal-1TS-M’ and four imported equivalents (Lubro, Quakerol, Rollub, Trenoil). For the base process, reference linear relationships were established between roll wear and changes in strip roughness. The scientific novelty of the work lies in defining Kprint not as a static quantity, but as a dynamic function of the relative service life of the rolls. Three calculation methods were compared: the arithmetic mean, the instantaneous integral, and the ratio of integrals of functions (‘energy’ measure). The results showed that integral methods provide a smoother estimate, levelling out local inhomogeneities, although they yield values 15–30% lower than discrete measurements. The ranking of emulsions by their ability to imprint roughness proved to be identical for all methods, confirming the reliability of the proposed models. The obtained functional dependencies can be integrated into mathematical models of lubricant film formation to optimise rolling conditions and improve metal surface quality.