Papers by Keyword: PIM

Abstract: This study proposes an intelligent optimization system based on the Taguchi method, back-propagation neural network (BPNN), multilayer perceptron (MLP) and modified PSO-GA to find optimal process parameters in plastic injection molding (PIM). Firstly, the Taguchi method is used to determine the initial combination of parameter settings by calculating the signal-to-noise (S/N) ratios from the experimental data. Significant factors are determined using analysis of variance (ANOVA). The S/N ratio predictors (BPNN_S/N) and quality predictors (BPNN_Q) are constructed using BPNN with the experimental data. In addition, a modified PSO-GA algorithm in conjunction with MLP is used to find initial weights of BPNN and to reduce the training time of BPNN. In the first stage optimization, the S/N ratio predictors are coupled with GA to reduce the variations of the manufacturing process. In the second stage optimization, The combination of S/N ratio predictors and quality predictors with modified PSO-GA is empoyed to search for the optimal parameters. Finally, three confirmation experiments are performed to assess the effectiveness of these approaches. The experimental results show that the proposed system can create the best performance, and optimal process parameter settings which not only enhance the stability in the whole injection molding process but also effectively improve the PIM product quality. Furthermore, experiences of the novel hybrid optimization system can be transferred into the intelligent PIM machines for the coming up internet of things (IoT) and big data environment.

Abstract: This study proposes an optimization system to find out the optimal process parameters of plastic injection molding (PIM). The system is divided into two phases. In the first phase, the Taguchi method and analysis of variance (ANOVA) are employed to perform the experimental work, calculate the signal-to-noise (S/N) ratio, and determine the initial process parameters. In the second phase, the back-propagation neural network (BPNN) is employed to construct an S/N ratio predictor. The S/N ratio predictor and genetic algorithms (GA) are integrated to search for the optimal parameter combination. The purpose of this stage is to reduce the process variance and promote product quality. Experimental results show that the proposed optimization system can not only satisfy the quality specification, but also improve stability of the PIM process.

Abstract: This study proposes the research method to examine through experiment the mechanical properties of final products based on the size and sintering temperature of powder particle during STS630 powder based metal injection molding and heat treatment processing condition after the sintering. The feedstock for the injection was manufactured based on STS630 powder with the diameter of 7.0±1.0μm and 8.0±1.0μm and the sintering was carried at 2 temperature conditions of 1300°C and 1355°C after the injection and debinding process. Heat treatment conditions of sample after the sintering were divided into 2 types thus final samples of total 8 cases were manufactured. Then, the 5 types of mechanical properties test were conducted. Optimal processing conditions for MIM molding and heat treatment of STS630 powder could be established based on it.

Abstract: Main low-PIM crafts were summarized, such as material requirements of major devices and special requirements of electroplating process. The setting up technologies of a PIMI testing system was discussed, for example reducing the number of connectors, isolators being used to prevent active IM and requirements of subsystem and receiver being given. Based on those crafts and technologies, a PIMI testing system was setting up with a design goal of 3rd residual PIM being-165dBc@2x43dBm. It achieved the goal with-165dBc through actual measuring after calibration.

Abstract: In this study, a micro patterned substrate was manufactured by micro powder injection molding (μPIM). As a mold for forming the micro patterned substrate, a metal mold having a linewidth of 100 um was fabricated by micro photo etching process. The specimen prepared through such a process had a sound shape at a shrinkage rate of 16.7% with respect to the mold. To verify industrial applicability of the micro patterned substrate, a micro-fluidic device was fabricated using a smooth flow of fluid therethrough. These results indicated that the micro powder injection molding is useful for micro-fluidics.

Abstract: An exhaustive design to the micro-architecture of SIMD core based on PIM technology is made; meanwhile the system architecture is implemented completely by applying Verilog hardware description language, and is simulated by the simulation software Xilinx ISE, the verification of the functional correctness is obtained as well via the simulation waveform. As the result, it can be concluded that the bandwidth and the delay of data accessing can be increased and reduced respectively by making full use of PIM technology, and then the performance of the entire system can be greatly improved accordingly.

Abstract: Austenitic Stainless Steel Has a FCC Structure at Room Temperature and the Temperature Range of the Austenite Phase Depends upon its Composition. 316L SS Is Widely Used in Medical, Marine, Industrial, Sporting and Aerospace Applications due to its Excellent Combination of Mechanical Properties and Corrosion Resistance. this Study Presents the Defects Observed during Optimization of the Processing Parameters for the Fabrication of Powder Injection Molding (PIM) of 316L SS Parts. in this Study, Five Formulations of Feedstock Containing 60-71vol% of Metal Powder Were Prepared Using a Wax-Based Binder. Green Samples Were Injection-Moulded, Followed by Binder Removal by Solvent and Thermal Means. Paraffin Wax (major Binder) Was Extracted at Various Temperatures in Order to Determine the Solvent Extraction Temperature. the Thermal De-Binding Was Performed Successfully at a Temperature of 450°C by Varying the Heating Rate from 1°C/min -10°C/min. SEM Results Showed Complete Removal of the Plastic Binder. Test Samples Were Sintered at Various Temperatures and Atmospheres. the Defects Observed during Solvent Extraction Were Swelling, Cracks and, at the Thermal De-Binding Step, Collection of Binder, Swelling and Holes. Sintered Samples Showed a Loss of Dimensional Control. these Types of Defect Were Considered to Be due to Inappropriate Heating Rates, Temperature and Dwell Time at each Process Step.

Abstract: The purpose of present study was to increase productivity and to reduce the polution of dust for making of endmill by conventional method such as grinding process. The micro scale endmill manufactured by powder injection molding, the molding (green part) was debinded and sintered. After that decreasing the porosities of the parts sintered, HIP process was adapted. After HIP process the relative density was shown more than 99% of the tools sintered. Finally, the micro cutting experiment using manufactured tool by PIM and HIP were implemented for verifying the feasibility of the tool. The ware of zirconia micro tool was observed very small, but the concentricity is less than the conventional tool made by grinding process. This type of tool is adequate to use in rough milling.

Abstract: To enable rapid response to the needs of MES reconfiguration, we introduce a component -based MES reconfiguration approach based on PIM. In this approach we get feature values by extending PIM, and use them to query reusable components that are needed to perform MES reconfiguration. By this means we can ensure system flexibility, on the other hand ensure the quality of the reconstructed system from the abstraction level of models.