Business globalization, increased worldwide competition, decreased product lifecycles and continuous introduction of new technologies force companies to use new machine tools. Appropriate selection of a machine tool for a production system resultsin increased precision, productivity, flexibility, and manufacturing responsiveness.Meanwhile, machine tool selection is a multi-faceted manufacturing planning problem,typically involving a variety of conflicting goals. Thus, selecting the most suitablemachine from the increasing number of available machines is a difficult and demandingtask. In this thesis, a decision support system (DSS) is developed to aid in selection of machine tools for a production system. The DSS uses multi-criteria weighted averagemethod (MCWA) as the decision-making approach. MCWA method considers a set ofconflicting objectives such as productivity, flexibility, and adaptability that typically cannot be achieved simultaneously. Each machine tool is assigned a score according to itsproperties in relation to the machines in the database. These scores are then used to rankthe machines according to various criteria. A stepwise approach is used in the selectionprocess. The entire tool selection process is demonstrated with examples. Sensitivity analysis is used to determine the most critical criterion and the most critical measure ofperformance. Cost / benefit analysis is carried out involving the purchasing decision of aselected machine tool and its additional options
