The search for increased productivity and cost reduction in machining can be interpreted as the desire to increase the material removal rate, MRR, and maximize the cutting tool utilization. The CNC process is complex and involves numerous limitations and parameters, ranging from tolerances to machinability. A well-managed preparation process creates the foundations for achieving a reduction in manufacturing errors and machining time. Along the preparation process of the NC-program, two different studies have been conducted and are presented in this thesis. One study examined the CAM programming preparation process from the Lean perspective. The other study includes an evaluation of how the cutting tools are used in terms of MRR and tool utilization.

The material removal rate is defined as the product of three variables, namely the cutting speed, the feed and the depth of cut, which all constitute the cutting data. Tool life is the amount of time that a cutting tool can be used and is mainly dependent on the same variables. Two different combinations of cutting data might provide the same MRR, however the tool life will be different. Thereby the difficulty is to select the cutting data to maximize both MRR and cutting tool utilization. A model for the analysis and efficient selection of cutting data for maximal MRR and maximal tool utilization has been developed and is presented. The presented model shortens the time dedicated to the optimized cutting data selection and the needed iterations along the program development.

The search for increased productivity and cost reduction in machining can be interpreted as desire to increase the Material Removal Rate, , and maximize the cutting tool utilization. The CNC process is complex and involves numerous constraints and parameters; ranging from tolerances to machinability. A well-managed preparation process creates the foundation for achieving a reduction in manufacturing errors and machining time. Along the preparation process of the NC-program, two different studies have been performed and are presented in this thesis. One study examined the CAM programming process from the Lean perspective. The other study includes an evaluation of how the cutting tools are used in terms of and tool utilization. Two distinct combinations of cutting data might provide the same . However, the tool life and machining cost can be different. Therefore, selection of appropriate cutting parameters that best meet all these objectives is challenging. An algorithm for analysis and efficient selection of cutting data for maximal , maximal tool utilization and minimal machining cost has been developed and is presented in this work. The presented algorithm shortens the time dedicated to the optimized cutting data selection and the needed iterations along the program development. Furthermore, the objectives that need to be considered during the estimation of the manufacturing processes sustainability have been identified. In addition, this thesis also includes a theoretical study to estimate energy use, CO2-footprint and water consumption during the manufacture of a workpiece, which can be invaluable for companies in their search for sustainability of their manufacturing processes.