1. A method for predicting temperature and additive concentration variables in an electrolytic smelting bath process, said variables being regulated together to provide in combination, optimal improvement in the physico-chemical properties of said bath and to lower the temperature of said bath, said optimal combination resulting in a lowering of the melting temperature of said bath at any given time, comprising: measuring process variables of each pot used in an electrolytic process of forming a pure metal; sending said process variables to a central database; receiving said process variables in said central database that was generated in each of said pots and receiving therein historical measurements; representing respective pots as quality predictive modeling tasks based on said historical measurements; grouping predictive modeling tasks for said temperature and said additive in said pots according to heterogeneous relatedness of the production equipment, said grouping step being included, for each pot in which a metal ore is simultaneously being processed, grouping said predictive modeling tasks for all of the respective pots, each said pot of the multiple pots being treated as a group of one or more predictive modeling tasks; partitioning said process variables into two sets comprising generating a prediction model that accommodates said grouping of said pots predictive modeling tasks from said grouping step and said partitioned process variables from said partitioning step; predicting a temperature and or a concentration of said additive in individual pots based on said prediction model generated in the generating step; sending predicted values of temperature and/or additive concentration obtained from each pot to an advanced process controller and the central database; measuring an actual number value of the temperature and/or additive concentration in at least one of said pots; sending said actual number value of the said temperature and/or said additive concentration in at least one of said pots to an advanced process controller and a virtual machine; updating said virtual machine with said actual number value of the temperature and/or additive concentration in at least one of said pots; determining a feedback control by said advanced process controller: and processing, by increasing or decreasing said temperature and/or said additive concentration by the production equipment in accordance with the feedback control, wherein the receiving, representing, grouping, partitioning, generating, and predicting steps are executed by a virtual machine implemented on a computer.