CHEESE BOWL PROCESS ANALYSIS USING PARTIAL MINIMUM SQUARES METHOD

Abstract

Introduction:
Process yield is an important parameter in cheese production, it depends of operating conditions, for that reason improvement alternatives can be established if the interaction among the involved variables are known.
Objective:
To establish the functional relation among cheese yield and operation parameters using Partial Minimum Squares method.
Materials and Methods:
Cluster Analysis was used to determine the interrelations among cheese yield and sixteen process variables, thus Principal Component and Partial Minimum Squares methods were applied to establish quantitative relationships between the same parameters using Statgraphics Centurion XV statistical program.
Results and Discussion:
In e multivariate analysis, a mathematical model with a high statistical signification was obtained for yields respect milk mass, and alternatives in operating conditions were evaluated using simulation methods. As result of process simulation with nonstandardized variables function a yield of 12.02% could be reach in this process.
Conclusions:
A regression model by Partial Minimum Square has a Predictive Quadratic Error of 5.00x10-4, indicating its possibility of use in this step simulation. It can be achieve an additional economic effect of 1600.00 CUP for each production, working under the best operation conditions.