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An interior design methodology to compensate for the shrinkage in the holes of artifacts fabricated with desktop 3D printers employing fused deposition modeling process is presented in this study. In the conventional way of compensating, the initial geometry is scaled according to the predictive and statistical models so that the critical dimensions will be more accurate when the part is cooled down. The proposed method employs a completely different paradigm. It constructs various interior structures to compensate for the shrinkage in the holes according to the geometric attributes of the artifacts. In other words, the method utilizes shrinkage as a tool to compensate for the shrinkage. Printed interior line segments, which are directly connected to the perimeter of the hole, simply pull the hole towards the inside of the artifact. In result, the dimensional accuracy of the hole is improved considerably. The measurements with a coordinate measuring machine and the numerical analysis revealed that the proposed design approach can decrease the dimensional error substantially compared to the conventional 3D printed parts. [ABSTRACT FROM AUTHOR]

Tool condition monitoring, mainly tool breakage detection for high-speed machining (HSM), is an important problem to solve; however, the techniques or types of sensors applied in other research projects present certain inconveniences. In order to improve tool breakage monitoring systems, a simple, effective, and fast method is presented herein. This method is based on the discrete wavelet transform (DWT) and statistical methodologies. The effectiveness of the method is based on the measurements of the feed-motor current signals using inexpensive sensors. It is well-known that during the cutting process, the motor current is related to the tool condition. The current consumption changes when the tool is broken as compared to when the tool is in normal cutting condition. This difference can be obtained from the waveform variances between the signals in order to ascertain the tool condition. The algorithms of this research project consist of obtaining compressed signals from the I feed-motor current signals applying the DWT. Then from these compressed signals, we detect the asymmetries between them. The arithmetic mean value is applied to asymmetries of consecutive machining lengths to reduce noise in the data having a mean value of a series of asymmetries; also, a normal cutting threshold is set up in order to make decisions regarding the tool conditions so as to detect tool breakage. Therefore, this research project shows a low-cost monitoring system that is simple to implement. [ABSTRACT FROM AUTHOR]

A cavity optimization method based on the principle of reverse deformation was prompted in this paper. In the reverse deformation method, the displacement which represents the nonlinear shrinkage was superposed on the initial profile of cavity and compensated the shrinkage of wax and alloy solidification. Moreover, an estimation algorithm was prompted to calculate the displacement based on reverse engineering, and its key technologies such as blade measurement, model registration, and statistical analysis of the displacement were investigated. Finally, a sample application was presented for demonstration in this paper. [ABSTRACT FROM AUTHOR]

A new approach is proposed using a support vector machine (SVM) to classify the feature of the cutting force signal for the prediction of tool breakage in face milling. The cutting force signal is compressed by averaging the cutting force signals per tooth to extract the feature of the cutting force signal due to tool breakage. With the SVM learning process, the output of SVM’s decision function can be utilized to identify a milling cutter with or without tool breakage. Experimental results are presented to verify the feasibility of this tool breakage prediction system in milling operations. [ABSTRACT FROM AUTHOR]

This paper presents a systematic methodology to analyze the shrinkage and warpage in an injection-molded part with a thin shell feature during the injection molding process. The systematic experimental design based on the response surface methodology (RSM) is applied to identify the effects of machining parameters on the performance of shrinkage and warpage. The experiment plan adopts the centered central composite design (CCD). The quadratic model of RSM associated sequential approximation optimization (SAO) method is used to find the optimum value of machining parameters. One real case study in the injection molding process of polycarbonate/acrylonitrile butadiene styrene (PC/ABS) cell phone shell has been performed to verify the proposed optimum procedure. The mold temperature ( M T), packing time ( P t), packing pressure ( P P) and cooling time ( C t) in the packing stage are considered as machining parameters. The results of analysis of variance (ANOVA) and conducting confirmation experiments demonstrate that the quadratic models of the shrinkage and warpage are fairly well fitted with the experimental values. The individual influences of all machining parameters on the shrinkage and warpage have been analyzed and predicted by the obtained mathematical models. For the manufacture of PC/ABS cell phone shell, the values of shrinkage and warpage present the reduction of 37.8 and 53.9%, respectively, using this optimal procedure. [ABSTRACT FROM AUTHOR]