An experimental design approach using TOPSIS method for the selection of computer-integrated manufacturing technologies

The selection of Computer-Integrated Manufacturing (CIM) technologies becomes more complex as the decision makers in the manufacturing organization have to assess a wide range of alternatives based on a set of attributes. Although, a lot of Multi-Attribute Decision-Making (MADM) methods are available to deal with selection applications, this paper aims to explore the applicability of an integrated TOPSIS and DoE method to solve different CIM selection problems in real-time industrial applications. Four CIM selection problems, which include selection of (a) an industrial robot, (b) a rapid prototyping process, (c) a CNC machine tool and (d) plant layout design, are considered in this paper. TOPSIS method and Design of Experiment (DoE) are used together to identify critical selection attributes and their interactions of all these cases by fitting a polynomial to the experimental data in a multiple linear regression analysis. This mathematical model development process involves TOPSIS experiments with the model. The regression meta-model greatly reduced the cost, time and amount of the calculation step in application the TOPSIS model. Application results were validated and shown that they provide good approximations to four decision making problem's results in the literature.

► This paper presents the use of a meta-model to solve a MADM problem.
► The meta-model is a multiple regression model which is constructed using combined DoE and TOPSIS.
► It is different from the conventional MADM approaches.
► When the meta-model is constructed, it can easily facilitate the alternative evaluation process.