Дисертації з теми "Hybrid Injection Molding"
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Shelesh-Nezhad, Karim. "Developing a hybrid expert system program to aid in the design of plastic injection molding process." Thesis, Queensland University of Technology, 1997. https://eprints.qut.edu.au/36048/7/36048_Digitised_Thesis.pdf.
Повний текст джерелаNugay, Isik Isil. "POLYURETHANES in RIGID and FLEXIBLE ELECTRONICSNOVEL HYBRID PROCESSING TECHNIQUES and REAL-TIME MONITORING OF MATERIAL PROPERTIES." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1406633847.
Повний текст джерелаRohne, Clemens, Michael Schreiter, Jens Sumpf, Klaus Nendel, and Lothar Kroll. "Hybrid Conveyor Chains – Calculation, Design and Manufacturing." Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-231781.
Повний текст джерелаIn der folgenden Abhandlung wird die Entwicklung einer Multiflex-Kette in Hybridbauweise erläutert. Mit dieser neuartigen Kettenvariante soll eine Steifigkeits- und Festigkeitssteigerung gegenüber den konventionellen Kunststoffgleitketten erzielt werden. Als Ausgangsbasis für die Entwicklung der hybriden Förderkette dient eine zweiteilig ausgeführte Multiflex-Kette mit der Teilung von 33,5 mm und einer Baubreite von 83 mm. Die hybride Förderkette soll in bestehende Layouts von Kettenförderern integriert werden können. Unter Beachtung konstruktiver, fertigungstechnischer und betrieblicher Aspekte wird die lasttragende Struktur der einzelnen Kettenglieder im Metalldruckgussprozess gefertigt und anschließend mit einem, für Multiflex-Ketten üblichen Kunststoff im Spritzgießprozess ummantelt. Die Evaluierung der Steifigkeits- bzw. Festigkeitssteigerung erfolgt im Rahmen umfangreicher Versuchsreihen
Ghoreishi, Rima, and Fatmehsari Mehdi Ehsani. "Mechanical and Thermal Characterizations of Biobased Thermoset Resins from Soybean Oil Reinforced with Natural Fiber Using Vacuum Injection Moulding Technique." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20223.
Повний текст джерелаVastesson, Alexander. "Thiol-ene and Thiol-ene-epoxy Based Polymers for Biomedical Microdevices." Doctoral thesis, KTH, Mikro- och nanosystemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215110.
Повний текст джерелаQC 20171003
Imaddahen, Amine. "Étude expérimentale multi-échelle et modélisation hybride prédictive du comportement, de l'endommagement et de la durée de vie en fatigue d’un matériau composite polypropylène / fibres de verre." Thesis, Paris, HESAM, 2020. http://www.theses.fr/2020HESAE063.
Повний текст джерелаThe main objective of this work, is to provide a numerical tool, capable of predicting the damage and fatigue life of thermoplastic matrix composites materials and structures. To do this, a multi-scale experimental study of the PPGF40 material (polypropylene loaded with 40% by mass of glass fiber) is carried out. A qualitative, but also a quantitative analysis of the various damage mechanisms occurring during mechanical loading was carried out through in-situ three-points SEM bending tests, interrupted fatigue tests and observations of fracture faces in monotonic and cyclic loading. In the light of these tests, we concluded that the decohesion of the fiber-matrix interface, and the propagation of cracks through the interfaces, appears to be, the predominant damage phenomenon leading to the fracture of the material and that, regardless of the orientation of the fibers and the loading mode. The proposed hybrid approach is based on a micromechanical / phenomenological model taking into account the damage at the fiber / matrix interface and the plasticity of the matrix. To do this, a local statistical criterion of damage at the fiber-matrix interface is introduced into a Mori and Tanaka model, and the linearization of the plastic behavior of the matrix is done step by step, using the mean field approach with a secant formulation. The micromechanical model used then, makes it possible to predict the behavior of the material under monotonic loading, and in particular the first stiffness loss during the fatigue. Analysis of the experimental results shows that the latter is directly related to the fatigue life of the material. Thus, a predictive methodology of the fatigue life is proposed and validated for various microstructural configurations. A fatigue failure criterion is proposed according to the number of cycles
Wang, Chih-hao, and 王志豪. "Research on Hybrid Optical Elements by Vibratile Injection Compression Molding." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/77563941492623190496.
Повний текст джерела國立臺灣科技大學
機械工程系
98
This research is to develop Vibratile Injection Compression Molding (V-ICM) and integrate the Varithermo Mold Temperature (VMT) technology for increasing the Groove Filling Ratio (GFR) and reduce aspheric form errors of hybrid optical elements. PMMA and COP 480R have been used to investigate the difference in processing, and to understand the residual stress, chromatic aberration (CA) and the Modulation Transfer Function (MTF) graph for comparison. Groove filling ratio (GFR), aspheric form error and the distribution of residual stress have been studied and discussed. Results have shown that the V-ICM can enhance the GFR effectively. In addition, the fixed mold temperature and different trigger time points affect the GFR significantly under the same aspheric form errors. The GFR can achieve nearly 98.09% and aspheric form error is about 7.26μm with high mold temperature in the COP 480R processing with V-ICM and VMT technology. The results of this study can effectively enhance the accuracy of multi-scale hybrid optical elements. In the future, this technology can apply to produce the high accuracy and also have the aspheric form with different multi-scale sizes, or freeform optical elements.
Lee, Feng-Chi, and 李豐吉. "Research on Multi-Scale Hybrid Optical Elements by Injection Molding." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/60630087523422359384.
Повний текст джерела國立臺灣科技大學
機械工程系
97
This research is to develop and integrate the in-mold micro compression (IMMC) and varithermo mold temperature (VMT) method in injection molding process for investigating the multi-scale hybrid optical elements including the aspheric form error (Rt) and the replication or groove filling ratio (GFR) of Fresnel diffraction structure. The data acquisition system is used to integrate these two processes. In the IMMC method, piezoelectric actuator and pressure sensor are used to test with different percentages of peak filling pressure. The VMT method is to switch on the compression air to achieve quick mold cooling after sensing the packing phase signal from the injection molding machine. It is to investigate the effect of different cooling setting temperature (CST) on the quality of molded parts. The Rt can be achieved as 1.29 μm when the mold temperature is set as 100 ℃ in the traditional injection molding. Then experimental results show that the Rt can be achieved as 3.32 μm and the GFR as 96.95% when the mold temperature is set as 120 ℃, the CST of varithermo mold temperature as 80 ℃, and the IMMC method with trigger point as 50% of peak filling pressure. Further research focuses on the replication of hybrid lens array optical elements with micro structures to increase the optical performances.
Lin, Shian-Ming, та 林先明. "Research on μ-Injection Compression Molding of Hybrid Optical Elements". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/54326041383935224691.
Повний текст джерела國立臺灣科技大學
機械工程系
96
This research conducted a novel micro injection compression molding (μ-ICM) process for fabrication of hybrid optical elements (HOEs). The micro compression motion is triggered by the percentage of peak filling pressure obtained by the data acquisition (DAQ) system. Experiments were implemented with different percentages of peak fill pressure, and the relationship between the trigger time and transfer ratio of the groove (TRG) were investigated. The Moldflow MPI software (Moldflow Co., USA) is used to simulate the filling and packing stages of HOEs. Comparison of short shot is preceded by simulation and experimentation. Results show that (1) the HOEs are fabricated successfully by the μ-ICM with a closed-loop pressure control, (2) the comparison of short shot is similar in simulation and experiment, (3) the TRG has been achieved as 99% when the trigger pressure is 15% of peak filling pressure with mold temperature 90°C and melt temperature 250°C, (4) the comparison of different mold insert materials show that the STAVAX with electroless plated Nickel (ELNi ) has better TRG than that of the oxygen-free copper (OFC) due to higher hardness of ELNi. Further research focuses on the μ-ICM of optical elements with micro structures to increase the optical performances.
Chen, Pi-Kai, and 陳必凱. "Research on Closed-Loop Micro Injection Compression Molding of Hybrid Optical Elements." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/43370630576400291339.
Повний текст джерела國立臺灣科技大學
自動化及控制研究所
98
This research is to develop a novel Closed-Loop micro injection compression molding (CLMICM) process for fabricating the multi-scale hybrid optical elements with Fresnel diffraction structure. The research adopts the LabVIEW and PC-Based control system to construct a controller developing platform. In this Study performance analysis, controller design, simulation, and system application have been completed and tested on this platform. The cavity pressure controller uses a mold-based PI controller for closed-loop control scheme. Experimental results have demonstrated the feasibility of the proposed system. Results show that the HOEs can be fabricated successfully by the CLMICM. The cavity pressure response is similar as show in simulation and experiment. Moreover, the groove filling ratio (GFR) has been achieved as 98.27% by CLMICM with mold temperature 100°C. Further research focuses on the CLMICM for optical elements with micro structures and aspheric surface to increase the optical performances.
Liou, Pen-Hsi, and 劉朋熹. "An optimization system for plastic injection molding process parameters using hybrid algorithms." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/12119435650441651849.
Повний текст джерела中華大學
科技管理博士學位學程
102
The plastic injection molding (PIM) industry offers a variety of products to satisfy diverse consumer needs. Nowadays, the parameter settings for the PIM industry are based on engineers’ experiences and design of experiments (DOE). However, it takes a large amount of time, manpower, and cost to figure out an appropriate combination of process parameters since parameter settings that could have a great impact on products are numerous and there are deep nonlinear relationships between the parameters. This study proposes a system with optimal parameters for the PIM industry in order to solve those problems. Two models are taken along with the research work and each model is a two-stage multiple-objective optimization based on hybrid algorithms. The research starts with the Taguchi method employed for experiment and data analysis. Besides, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are used to obtain a combination of parameter settings that is the most significant one in the process. The first model is an optimization based on regression model using hybrid algorithms. With the experimental data gained from the Taguchi’s experiment, a quality regression model (quality predictor) and an S/N ratio regression model (S/N ratio predictor) are created. The first stage is to optimize the multiple-objective S/N ratio. The S/N ratio predictor is associated with genetic algorithm (GA), simulated annealing (SA), and particle swarm optimization (PSO) for universal search to acquire the process parameters and to maximize the S/N ratio of each quality characteristics. This stage intends to minimize the variance in process. The second stage is to optimize the multiple-objective quality. The hybrid algorithms (SA-PSO, GA-PSO, PSO-GA) are associated with the S/N ratio predictor and the quality predictor for universal search. The process parameters gained from the first stage is set for the initial values. The hybrid algorithms are then used to find the optimal parameter settings that tally best with the quality standard and make it most stable in process. The second model is an optimization based on back-propagation neural network (BPNN) using hybrid algorithms. The data gained from the Taguchi experiment are applied to train in BPNN so as to generate an S/N ratio predictor and quality predictor. The first stage is to optimize the S/N ratio. The S/N ratio predictor then works together with GA for universal search to acquire the process parameters and to maximize the S/N ratio of the quality responses. This stage intends to minimize the variance in process. As for the second stage, process optimization of the multiple-objective quality is investigated. Hybrid GA-PSO is associated with the S/N ratio predictor and the quality predictor for universal search. The process parameters gained from the first stage is set for the initial values. The Hybrid GA-PSO is then used to find the optimal parameter settings that tally best with the quality standard and make it most stable in process. The confirmation results show that the second model can create the best performance. The best process parameter settings which not only enhance the stability in the whole injection molding process but also meet the length specification, reduce the parts’ warpage and effectively improve the PIM product quality.
Chen, Szu-Ting, and 陳思婷. "Study on Progressive Injection Compression Molding for Hybrid Prism with Sub-wavelength Micro Structures." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/92056688307271984954.
Повний текст джерела國立臺灣科技大學
機械工程系
101
This research is to design a progressive injection compression molding (PICM) for hybrid prism with micro structures to obtain better surface uniformity for improving optical quality. The compression stroke is based on the different part thickness of prism and the mold cavity pressure has been observed by two sets of pressure sensor modules to acquire the relationship of pressure and compression effects. In this research, three kinds of molding process including injection molding (IM), injection compression molding (ICM) and progressive injection compression molding (PICM) have been investigated to discuss the parameters of injection velocity, mold temperature, and compression time based on performance of non-uniformity (NU) and sub-wavelength micro structures (SWMS) of filling ratio (SFR) by experimental design. The SWMS is replicated by a silicon mold insert with nano or sub-micro structures of porous anodic alumina (PAA). Residual stress has been measured by photoelastic instrument and discussed. Experimental results show that the PICM could effectively improve the incident surface uniformity 46.34% as compared with IM process and also improve the SFR from 82% to 92%, The contact angle incident surfaces of prism by IM and PICM increased from 83.3゚to 118.7 ゚, as increased by 42.50%. The hybrid prism with best SFR can improve the illumination 80.8 % as compared with prism without sub-microstructure. Further study can apply on injection molding of the hybrid thickness of prism aspheric elements.
Chen, Te-Ning, and 陳德寧. "Optimization of the Plastic Injection Molding Process Using Taguchi method, RSM, and Hybrid GA-PSO." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/t637s2.
Повний текст джерела中華大學
工業管理學系碩士班
101
In a rapidly changing world, the plastic injection molding (PIM) industry is trying to make the product various. At present, the parameter settings for plastic injection molding often rely on engineers’ experiences and design of experiments. However, since many different parameters could influence a finished product and a high level nonlinear relationship stands between each parameter, it takes a large number of manpower, devices, and other expenses to figure out a better combination of process parameters. This study proposes three optimization models of process parameters in plastic injection molding in order to solve those problems. Three optimal models are taken along with the research methodologies. In the first model, the Taguchi method is employed for experiment and data analysis in which the quality characteristics for the plastic injection product are length and warpage. Besides, the control factors for the process are melt temperature, injection velocity, packing pressure, packing time, and cooling time. Moreover, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are used to obtain a combination of parameter settings that is the most significant parameters in the process. In the second model, experimental data are set for the response surface methodology (RSM) to analyze and create a quality regression model (quality predictor). The quality predictor is associated with genetic algorithm (GA) to derive an optimal combination of process parameters that meets multiple-objective quality characteristics. The third model is a two-stage multiple-objective optimization. The first stage is to optimize the S/N ratio. The data gained from the Taguchi experiment are adopted to generate an S/N ratio predictor. The S/N ratio predictor then works together with GA for universal search to acquire the process parameters and to maximize the S/N ratio of the quality responses. This stage intends to decrease the variance in process to minimum. As for the second stage, process optimization is investigated. Hybrid GA-PSO is used with the quality predictor and the S/N ratio predictor for search. The process parameters gained from the first stage is set for the initial values to find the optimal parameter settings that tally best with the quality standard and make it most stable in process. The confirmation results show that two-stage optimization system turns out with the best performance. The approach not only enhances the stability in the whole injection molding process including the quality in length and warpage but also saves the cost and time spent from the mold design to manufacturing.
Yeh, Ching-Hsien, and 葉敬賢. "Research on Residual Stress and Optical Quality in Hybrid Optical Elements by Vibratile Injection Compression Molding Process." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/ke9whj.
Повний текст джерела國立臺灣科技大學
機械工程系
99
This research is to explore the formation model of the residual stress, molecular orientation during injection molding of hybrid optical lens and finally to study aspheric form error, groove filling rate(GFR) and residual stress on optical quality. The research methods discuss the forming of residual stress from gate to filling end by in-mold annealing. Further, the Raman intensity ratio is defined to discuss the molecular orientation on different injection velocity and thickness. It also discusses the factors of injection velocity, mold temperature and PZT vibration frequency to the effects of aspheric form error, GFR and residual stress by experiment design finally. Experimental results will be compared with those of simulation analysis. From experimental results, the residual stress reduces gradually once the time of holding temperature is getting longer by in-mold annealing. The molded parts near the mold wall can have higher molecular orientation with higher injection velocity.The molecular orientation reduces in this in-mold annealing experiment. The aspheric form error, GFR and residual stress are mainly affected by mold temperature. Finally, the optical quality is mostly affected by aspheric form error.
Kurniawan, Denni, and 丹尼Denni Kurniawan. "An Integrated Optimization System for Plastic Injection Molding Using Taguchi Method, BPNN, GA, and Hybrid PSO-GA." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/gh8fbp.
Повний текст джерела中華大學
科技管理博士學位學程
102
Applications of polymer material in injection molding application are growing very fast in last decades. Moreover, several advantages, such as short cycle time production, light weight of products, and high surface quality, make plastic injection molding (PIM) work as a solution for industries to survive in competitive world. Besides these advantages, PIM is a more complex process than it is previously thought. Inappropriate material selection, process parameters, part and mold designs can affect the quality of plastic products. Therefore, investigation to improve product quality still becomes an important issue to be conducted. A well-controlled parameter setting is one of the solutions to avoid or reduce defect in plastic products. Previously, process parameters in PIM relied on the technician's experience using trial-and-error approach. However, this approach is not effective and unsuitable for complex manufacturing processes. This study presents a two- stage optimization system to find optimal process parameters of multiple quality characteristics in the PIM process. The Taguchi method, back-propagation neural network (BPNN), genetic algorithms (GA), and combination of particle swarm optimization and genetic algorithms (PSO-GA) are used to find optimum parameter settings. Melt temperature, injection velocity, packing pressure, packing time, and cooling time are selected as initial process parameters. Length and warpage are employed as the product quality. The experimental work is conducted using the Taguchi orthogonal array. According to the result from the Taguchi experiment, S/N ratio is calculated to find the best combination settings for product quality. Then, analysis of variance (ANOVA) is used to determine significant factors of the control parameters. Moreover, the S/N ratio predictor and quality predictor are constructed using BPNN. In the first stage optimization, S/N ratio predictor and GA are used to reduce variance of quality characteristic. In the second stage optimization, the S/N ratio predictor and quality predictor with hybrid PSO-GA are used to find optimal parameter settings for quality characteristic and stability of the process. Finally, three confirmation experiments are conducted to assess the effectiveness of the proposed system. Experimental results show that the proposed system not only improves the quality of plastic parts, but also reduces variability of process effectively.
Chen, X., Yee Cheong Lam, Michael K. C. Tam, and S. C. M. Yu. "Particle Migration of Quasi-Steady Flow in Concentrated Suspension for Powder Injection Molding." 2002. http://hdl.handle.net/1721.1/4035.
Повний текст джерелаSingapore-MIT Alliance (SMA)
Dai, Tsai-lun, and 戴采綸. "Research of Injection Compression Molding and Photoelasticity Compensator Method on Residual Stress and Optical Quality of Hybrid Prism." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/02982195926061773011.
Повний текст джерела國立臺灣科技大學
機械工程系
102
This study aims to design a Photoelastic Stress Image Analysis System (PSIAS) based on circular polarization theory, which includes two calibration and analysis methods of (I) PSIAS combined with a LWC Compensator Method or named as PSIAS_LWC_md and (II) Photoelastic Stress Analysis Software (PSAS) modified from previous study. Experimental verification has been performed by mechanical force compression on a benchmark Psm-1 disk for comparison of both methods with theoretical optical-stress coefficient method (C_md) from reference. The average stress error by PSIAS_LWC_md is 0.140MPa or 4.6%. Another results of PSAS is lesser than 0.312MPa or 10.3%. Then a PMMA disk by injection molding (IM) is used for estimating the stress-optical coefficients of test materials by PSIAS_LWC_md. Therefore a light-guide prism has been fabricated by IM and injection compression molding with thermal annealing (ICM-ANL) processes to investigate effects of parameters on prism’s residual stress, formability and optical quality. Result of the average residual stress of prism by ICM-ANL process is reduced 24.5% with that of IM process. Similarly, the minimum average non-uniformity (ANU) of prism by ICM-ANL process is 11?慆 or improved 74% and the illumination is promoted as 4% with that of IM process. Verification results of Raman intensity measurement have revealed that the molecular orientation of skin, shear and core layers in filling direction of prisms is much reduced for ICM-ANL process. Final test of hybrid prism with sub-wavelength structure, an Anodic Alumina Oxide (AAO) process is applied to fabricate six inch sub-wavelength structure (6”Al_SWS), and electroforming process is conducted to make 6”Ni_SWS of diameter 93nm and height 360nm. The sub-wavelength structures of hybrid prism are difficult to be demolded because the Ni_SWS of nano-columns are not totally vertically duplicated. Results of this study have been tested and verified for residual stress estimation of light-guide prism with different thickness by PSIAS_LWC_md. Future study can focus on applying the PSIAS_LWC_md and ICM-ANL technique as residual stress estimation on optical elements with different thickness and sub-wavelength structure.
Lo, Wen-Tuan, and 羅文端. "Design and Fabrication of a Self-Powered Wireless Sensing Module and Corresponding Temperature/Pressure-Hybrid Micro-Sensor for Injection-Molding Monitoring." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/74975270808652712896.
Повний текст джерела國立交通大學
機械工程系所
102
Recently, energy-harvester-powered (i.e., self-powered) wireless sensors network for environmental, medical, mechanical, and civil structural monitoring applications are rapidly developed. In this thesis, an energy-harvester-powered (i.e., self-powered) wireless sensing module for injection-molding monitoring is reported. Thermoelectric generators connected in series are used to harness a thermal energy from the injection-molding process and subsequently convert the thermal energy to the electrical output. The electrical output is consequently modulated/rectified to power a customized wireless temperature-sensing module which consists of wireless RF components, central controlling unit, RTD temperature sensor (embedded inside a mold cavity to detect the process temperature of injection-molding), and corresponding circuits. Due to this, a self-powered wireless temperature sensing module for injection-molding monitoring is achieved. The experimental results show the module successfully monitors the process temperature of the injection-molding. In addition, a smart MEMS temperature/pressure-hybrid sensor is fabricated and integrated with the module toward an intelligent injection-molding monitoring module. The testing results indicate the intelligent module is capable of sensing the temperature and pressure in the injection-molding process.
Sardashti, Amirpouyan. "Wheat Straw-Clay-Polypropylene Hybrid Composites." Thesis, 2009. http://hdl.handle.net/10012/4712.
Повний текст джерела