Multivariate Key Performance Indicator of Baking Process

Abstract

Energy efficiency is nowadays a subject deeply discussed in several fields, with a large potential in industry. Here proper process and energy management routines turns out to be essential to reduce the energy demand while keeping the control of the product quality. In this respect the bread baking, one of the pillar of food related industry, is an energy intensive process irrespective to the adopted oven technology or to the primary energy nature. Baking is the fundamental step of the bread production process and it entails a number of complex chemical and physical phenomena, critical to the final physical properties of bread, i.e. crust colour, crumb texture and taste. A careful balance throughout all the steps of the “manufacturing” cycle is vital to ensure the processes synchronization, in order to produce a consistent and satisfactory loaf of bread. A proper energy management of this process needs to consider such features to ensure a high quality product. As such process monitoring can not be conveniently described using customary specific energy metric (correlating the energy demand to the amount of processed material) or full three-dimensional (3D) physic-based modeling as in computational fluid dynamics (CFD).In this paper, the energy analysis of the system is carried out with a methodology rooted in the family of non parametric approaches. The aim of the study is to identify key performance indicators (KPIs) able to assess the effectiveness of the energy “use” along the baking process. Specifically, the identification of KPIs is carried out using Principal Component Analysis (PCA) of the available datasets.