An Intelligent decision support system for machine tool selection

Official URL: http://risc01.sabanciuniv.edu/record=b1123082 (Table of Contents)

The selection of appropriate machines and equipments is one of the most critical decisions in the design and development of a successful production environment. Considering the detailed specifications related to the functional requirements, productivity, quality, flexibility, cost, etc., and the number of available alternative machine tools in the market, the selection procedure can be quite complicated and time consuming. In this thesis, a user-friendly decision support system called Intelligent Machine Tool Selection is developed for machine tool selection. The software guides decision-maker in selecting available machines via effective algorithms: Analytic Hierarchy Process (AHP). It has some special features which may not be included in other decision support systems. The user does not need to have detailed technical knowledge as he is guided by simple questions throughout the selection process. The user first determines the relevant criteria to be considered (such as productivity, flexibility, etc.) and then makes a pair-wise comparison of each criterion to the others. There are many sub-criteria such as machine power, spindle speed, tool magazine capacity, etc. which are used to determine the scores for each criterion. If desired, some important requirements for an application, such as power and force, can be determined using process models which are also integrated to the software. The software can store the relevant new information associated with the user so that it can be made available to facilitate the successive decision-making processes. After a list of machines with their specifications is retrieved from the database based upon the user specified requirements, the selected criteria are considered in the AHP process. The application of the system is presented through several examples. Furthermore, sensitivity analysis is used to determine the most critical criterion and the most critical measure of performance. Cost analysis is carried out for the purchasing decision of a selected machine tool and its additional options. Reliability and precision analysis guide decision-maker selection of suitable machines.