engleski

Functional data analysis and its application in production processes

Modern manufacturing facilities are with no exception equipped with measurement devices that are able to produce high-resolution discrete data for relevant production parameters. Data measured that way can be described by smooth functions having the derivatives of desired order. Each such function is considered as a data in functional data analysis (FDA) method. FDA is an extension of traditional methods for data analysis to data that can be identified as functions. The objective of this work is to describe the possibility of solving inverse problems in production processes by FDA. In this work algebraic and differential equations are introduced through mathematical models describing the behaviour of some production parameters in the hot rolling process of aluminium strip. The results of the computer simulation show that FDA methodology can be successfully applied in modelling of production systems and in solving problems of parameter estimation in dynamic mathematical models.

Functional data analysis; Mathematical modelling; Algebraic and differential equation; Production processes

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