Geometrically accurate and anatomically correct threedimensional geometric models of human bones or bone sections are essential for successful pre-operative planning in orthopedic surgery. For such purposes, 3D polygonal models of bones are usually created based on Computer Tomography (CT) or Magnetic Resonance Imaging (MRI) data. In cases where there is no CT or MRI scan, or part of bone is missing, such three-dimensional polygonal models are difficult to create. In these situations predictive bone models are commonly used. In this paper, the authors describe the developed a software system for creation of Human Bones Customized Polygonal models (HBCP) which is based on the use of the predictive parametric bone model. The software system enables creation of patient-specific polygonal models of bones, by using only a limited number of parameter values. Parameter values can be acquired from volumetric medical imaging methods (CT, MRI), or from two-dimensional imaging methods (i.e. Xray). This paper introduces the new approach to the process of creation of human bones geometrical models which are based on the anatomical landmark points. Testing of the HBCP for the cases of femur bone samples has shown that created bone and bone region models are characterized by a good level of anatomical and morphometric accuracy compared to the results presented in similar researches.

One of the most important challenges for every machining shopfloor, especially a small one, is to achieve the required productivity with minimal energy consumption and engaged power. The paper presents a way to determine the optimal combination of values of cutting parameters such as depth of cut, feed rate and cutting speed from the range of their recommended values, which are usually additionally limited by the real conditions of available machines and tools. The optimal combination is the one which ensures targeted productivity and maximum energy savings at the same time. As an example, a real practice case of external rough turning of an AISI 1045 steel workpiece is presented. The selection of the optimal combination of cutting parameter values is based on a model which is developed using in situ measurements of energy consumption and engaged power in an experiment that emulates the critical operation in terms of energy consumption. The results show that optimization of cutting parameter values that enables the minimum of total energy consumption while achieving target productivity, does not necessarily enable the maximum of energy savings for a given operation. In the example from real practice shown in the paper, this optimization approach can cause higher total energy consumption by as much as 15.9% compared to the combination of parameters that ensure maximum productivity.