In today’s world, customers expect product variety. However, non-uniform products complicate the manufacturing processes significantly. In this study, we solved the cellular manufacturing system design and the technology selection problems simultaneously while taking the changing market dynamics into consideration. Cellular manufacturing system design problem aims the identification of existing part families and machine groups, while the technology selection decision determines the appropriate technology for the facility. In order to integrate the market characteristics in our model, we proposed a new cost function. Further, we modified a well known similarity measure in order to handle the operational capability of available technology. This new coefficient is employed at the identification of part families. The technology selection decision is based on the individual properties of parts, namely the production volume, variability of the demand, and the design stability of the part. Integration of the product variety at the design stage leads us to the use of flexible machining systems and dedicated manufacturing systems at the same facility. In the thesis, our hybrid technology approach is presented via a multi-objective mathematical model. A filtered-beam based local search heuristic is proposed to solve the problem efficiently