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dc.contributor.authorSpuzic, S.
dc.contributor.authorNarayanan, R.
dc.contributor.authorKovacic, Z.
dc.contributor.authorArachchige, D-H.
dc.contributor.authorAbhary, K.
dc.date.accessioned2017-05-11T03:15:06Z
dc.date.available2017-05-11T03:15:06Z
dc.date.issued2016
dc.identifier.citationSpuzic, S., Narayanan, R., Kovacic, Z., Arachchige, D.-H., & Abhary, K. (2016). Roll pass design optimization. The International Journal of Advanced Manufacturing Technology, 1–7. Retrieved from http://link.springer.com/article/10.1007/s00170-016-9424-4en_US
dc.identifier.urihttp://hdl.handle.net/11072/1891
dc.description.abstractHot rolling is among the most widely used manufacturing techniques. However, rolling mills are major resource consumers; thus, urgent rationalisation is required in the relevant industrial systems. Roll pass design (RPD) is a principal factor that determines process efficiency, product quality and resource consumption. Therefore, it is important to optimise RPD including the selection of roll materials. New avenues for optimising RPD are to be found by extracting knowledge buried in the vast repository of industrial records. The extracted statistical functions are then used for the non-linear optimisation of RPD parameters. The design of a leading oval groove for rolling a wire rod is presented as an example, along with a discussion of the general mathematical aspects. The presented case analysis shows how regression analysis and the probability density function (PDF) are used to define principal dimensions—height and width—for the leading oval groove. These two dimensions are inferred following the logic of probabilistic design, and are based on an understanding of the trend in groove contour changes, which occur due to surface wear during rolling campaigns.en_US
dc.language.isoenen_US
dc.subjectRoll pass designen_US
dc.titleRoll pass design optimizationen_US
dc.typeArticleen_US


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