Productivity improvement generated from systematically scheduling a brewhouse.
Guidelines for implementing brewhouse automation projects are presented. Aspects to be considered for a network model to optimise capacity, energy use and quality are: (1) capacity of utilisation and production floor, (2) costs per unit, (3) decisions manipulating costs and capacity, (4) constraints of equipment, (5) constraints of sale volume target, (6) quality parameters and constraints. Brewhouse examples of static and dynamic decision techniques are discussed. Static techniques fall into the linear programming transportation algarithm category, whereas the dynamic operator assistance techniques are based on dynamic programming.
Keywords : automatic brewhouse economics efficiency production programming