Development and improvement of 3D digitizing systems provide for the ability to digitize a growing number of materials and geometrical forms of greater complexity. This paper presents the application of 3D digitizing system using close range photogrammetry on the upper jaw cast in plaster in order to obtain its 3D model. Because of the low visual characteristics of gypsum, such as color and texture, many questions arise about the possibility of applying this particular method to this type of physical models. In order to overcome bad visual properties of gypsum, this paper analyzes the possibility of the photogrammetry method application supported by the projected light texture which is based on patterns in the form of noise-obtained mathematically modeled functions. In order to determine the selected image for light texture which gives the better results, an experiment was designed and carried out. Only two images were tested. One image is selected based on previous research and the other one was generated by the Matlab function for uniformly distributed random numbers. For validation and a comparative analysis of the results, an object of 3D digitization was generated with and without projected light texture. CAD inspection was applied for the analysis of the obtained 3D digitizing results. 3D model obtained by approved professional optical 3D scanner as a reference was used. The results in this paper confirm better accuracy of 3D models obtained with the use of light textures, but this approach requires additional hardware and setup adjustment for images acquisition.
For many years, Poka-Yoke (PY) has been used as one of the means to overcome challenges that can affect errors and defects in process. It is a widely accepted concept-a way of thinking, which undoubtedly contributed to significant results in a struggle against the occurrence of errors in various work processes. However, although PY seems to be well understood in theory, there are a large number of scientific papers and books that still seek to clarify and redefine PY, in order to finally implement its application at full capacity. Many authors, as it seems, want to emphasize inconsistencies in current theoretical and practical experiences. This claim is supported by the fact that over 50 similar and different PY definitions have been found in literature. It seems that most researchers do not sufficiently perceive generally accepted attitudes in the field of PY, as well as differences and inconsistencies in some of them. Due to a sense of confusion during the process design stage, an effort to predict locations of possible sources of error is a direct consequence of the diffuse knowledge in the field, which imposes the need to change that state. This paper summarizes the latest studies and definitions in the field of PY applications, in order to propose a comprehensive and generally acceptable definition of PY. In order to find what is common to the most important attitudes in the field of PY, a systematic literature review has been undertaken, with the goal to identify the areas of disagreement, to recognize any gaps that exist and outline personal experiences and attitudes in the field. The novel approach to the types of PY presented in this paper should provide a solid foundation for the creation and development of PY model and a systematic approach to the application of PY in production and service systems. Finally, some conclusions and prospective future research directions are presented. Highlights • Detailed systematic literature review on Poka-Yoke (PY) is presented. • More than 50 examples and case studies on PY are reviewed. • A novel approach to types of PY is proposed. • Examples of PY devices are created and discussed.
Continuation of research on solving the problem of estimation of CNC grinding process parameters of multi-layer ceramics is presented in the paper. Heuristic analysis of the process was used to define the attributes of influence on the grinding process and the research model was set. For the problem of prediction-estimation of the grinding process parameters the following networks were used in experimental work: Modular Neural Network (MNN), Radial Basis Function Neural Network (RBFNN), General Regression Neural Network (GRNN) and Self-Organizing Map Neural Network (SOMNN). The experimental work, based on real data from the technological process was performed for the purpose of training and testing various architectures and algorithms of neural networks. In the architectures design process different rules of learning and transfer functions and other attributes were used. RMS error was used as a criterion for value evaluation and comparison of the realised neural networks and was compared with previous results obtained by Back-Propagation Neural Network (BPNN). In the validation phase the best results were obtained by Back-Propagation Neural
Reviewed and verified in this paper is a system which integrates functions of fixture design and optimization. The system was developed for machining of plastic parts. Due to specific characteristics of plastic parts, the system allows optimization of location of fixture elements for clamping and locating, using minimum deformation of plastic parts as the goal function. The paper present the basic steps of the methodology applied, reviews specific segments of the system, and illustrates its applicability on a study case featuring operations of drilling and milling of ABS parts.
U disertaciji se prikazuje razvoj sistema za projektovanje i optimizaciju konstrukcije pribora za mašinsku obradu. Analizirani su različiti prilazi u projektovanu pribora. Prikazana je koncepcija i funkcionisanje razvijenog sistema. Validacija sistema je izvršena na konkternim radnim predmetima za operacije obrade bušenja i glodanja. Na kraju su dati odgovarajući zaključci i mogući pravci budućih istraživanja. Datum prihvatanja teme, DP:
U radu su prezentovani rezultati merenja statičkog koeficijenta trenja kontaknih parova od drveta. Istraživanja su sprovedena na tribometru koji funkcioniše po principu kose ravni. Dobijene srednje vrednosti statičkog koeficijenta trenja za kontaktne parove od drveta se kreću u rasponu od 0,42 do 0,63. Veće vrednosti statičkog koeficijenta trenja su dobijene za kontaktne parove od drveta koje karakteriše veća tvrdoća i veći modul elastičnosti, i obrnuto.
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