One of the important aspects contributing to the competitiveness and success of a manufacturer is the efficient management for timely order delivery. After production orders are scheduled, there arises the need of a support tool to aid in the analysis with the available information, and to support managerial decision making which ultimately aims at on-time delivery. One way in which companies can meet due-dates of orders that are in jeopardy of being late, is to schedule overtime. This research presents a method used for 1) predict the completion times of scheduled jobs; and 2) optimizing overtime allocation when delays are foreseen. Mathematical mixed-integer linear program models are developed to represent the above problems for a tandem production line with single machine work stages. Non-operational downtime occurrences are considered in the production horizons which can be varied by work stage. Buffer areas (queues) are also included in the production system. These MILP models are solved using commercial optimizer ILOG-OPL studio. Using VBA script with OPL, a friendly interface is built in MS Excel for ease in user manipulation. The interface can also be used in production test to hypothetical “what if” questions. The models are verified using simulation. Runtime evaluation is also preformed to determine the capabilities and limitations of the models
