Ultrasound Tomography for Spatially Resolved Melt Temperature Measurements in Injection Moulding Processes

For many years, injection molding is adopted as the most suitable manufacturing process in the production of complex plastic components. It is very difficult to boost the product's quality stability to attain a higher forming speed and higher automation in the injection moulding process because the process often disrupted by numerous inevitable deviations. The settings for different process parameters and machine parameters have quite a major influence on the overall product quality and its performance of the injection moulding process, which shows the final product quality as output responses. Identifying the perfect process parameter settings so that numerous responses may be optimized at almost the same time is becoming a significant research challenge these days. Smart manufacturing is at the heart of the new industrial revolution, and it will continue to be the primary means of transforming and upgrading the manufacturing industry in the upcoming decades. Melt temperature, the temperature of mould, injection pressure, and velocity of molten polymer while injection, injection time, pressure of molten polymer while holding into the mold cavity, holding time of molten polymer, and cooling time are the variety of input process parameters.  While mechanical characteristics, flaws such as warpage, volumetric or dimensional shrinkage, sink mark on outer surface, residual stress, and surface finish/roughness are examples of responses. To study and optimize the molding process, researchers have used a wide range of methods. Mathematical modeling, simulation, design of experiments, Taguchi methodology, analysis of variance - ANOVA, response surface methodology - RSM, evolutionary algorithm (EA), artificial neural networks - ANN, genetic algorithms - GA, fuzzy logic, particle swarm optimization - PSO, are examples of these techniques. This paper presents a review of the numerous strategies that used till date for optimizing the key injection moulding parameters, as well as their benefits and challenges. In the review, it is discovered that a perfect injection molding process, which takes care of overall quality control is still being researched upon. The process parameters involved in injection molding, required response, and the methodologies used for optimization of overall injection molding process are discussed throughout this paper.

The simulation solutions of different plastic injection molding processes are as multifaceted as the field of injection molding itself. In this study, the simulation of a special injection molding process, which generates partially foamed integral components, was parameterized and performed. This partial and physical foaming is realized by a defined volume expansion of the mold cavity. Using the injection molding simulation software Moldex 3D, this so-called Pull and Foam process was digitally reconstructed and simulated. Since the Pull and Foam process is a special injection molding technique for producing foamed components, the validity of the simulation results was analyzed and evaluated. With the use of Moldex 3D, varied settings such as different bubble growth models and mesh topologies were set, parameterized, and then analyzed, to provide differentiated numerical calculation solutions. Actual manufactured components represent the experimental part of this study and are produced for reference. Different evaluation methods were used to quantify morphological quantities such as porosities, local densities, and cell distributions. These methods are based on two-dimensional and three-dimensional imaging techniques such as optical microscopy and X-ray microtomography (µ-CT). Thus, this structural characterization of the manufactured samples serves as the validation basis for the calculated results of the simulations. According to the illustrated results, the adequate selection of bubble growth models and especially mesh topologies must be considered for valid simulation of specific core-back techniques, such as the Pull and Foam injection molding process.

The application of Taguchi method to reduce warpage in an injection moulding process is studied. The objective of this paper is to analyze the effect of injection moulding parameters, i.e., injection time, packing time, melt temperature and mould temperature, on the warpage defect in dumbbell plastics part. Optical comparator horizontal type was used to measure the difference of warpage value on each part. L9 orthogonal array with 3 replications was done with 27 totals of specimens. The result collected was optimized using Taguchi method and percentage of contribution was calculated using analysis of variance (ANOVA). According to the analysis, it is found that the significant factors affected warpage are injection time (32.01%), packing time (29.73%), mould temperature (24.39%) and melt temperature (13.87%). The optimum parameters for minimizing the warpage were injection time (1s), packing time (5s), melt temperature (270 °C) and the mould temperature (21 °C). By using Taguchi method and ANOVA analysis, optimum parameters and the percentage of contribution of parameters can be obtained. Thus, it shows that design of experiment method is the good quality tools to get the best quality for production.

Mould temperature is one of the most important parameter in injection moulding process of thermoplastic polymers in particular semi crystalline polymers. There are a lots of methods of control mould temperature but it is not simple and easy to measure heat transfer precisely. Injection moulds have usually a large mass and this is equal also to large heat capacity of tools and its thermal inertia. Measuring temperature by using contact equipment causes a lot of mistakes, because that method is based on heat transfer between thermocouple and measured area of mould. Result of research of 3 different method of temperature control of mould surface were present in the publication. For this purpose a special experimental mould was made. Mould has eight independent cooling circuits which were connected to the thermo controller Wittmann with two circuits. The main aim of research was to determine the effect of normal process of injection moulding on temperature changing in different area of mould. Under the cavity 4 thermocouple were placed and connect to the recorder what gave a possibility of uploading data during injection process. For that research mould temperature was change in many different layouts. Data and sequences of changes in temperature collected during tests gave very interesting result for discussion. Furthermore use of differences in temperature profile of the mould causes different temperature profile recorded during injection moulding. Tests were made by using fallowing equipment: Krauss Maffei injection moulding machine KM65-C4 and thermo controller Wittmann TPplus2, Shini Rotameter, infrared camera TESTO-890 and thermocouple signal recorder with 4 thermocouples of diameter 1mm located in injection mould 3mm under cavity surface. Draft of experimental mould and thermocouple location were presented in the article, and results of research as a drafts and charts of temperature changing in different area of mould were included.

Injection molding (IM) is considered the foremost process for mass-producing plastic products. One of the biggest challenges facing injection molders today is to determine the proper settings for the IM process variables. Selecting the proper settings for an IM process is crucial because the behavior of the polymeric material during shaping is highly influenced by the process variables. Consequently, the process variables govern the quality of the part produced. The difficulty of optimizing an IM process is that the performance measures (PMs), such as surface quality or cycle time, that characterize the adequacy of part, process, or machine to intended purposes, usually show conflicting behavior. Therefore, a compromise must be found between all of the PMs of interest. In the past, we have shown a method comprised of Computer Aided Engineering, Artificial Neural Networks, and Data Envelopment Analysis (DEA) that can be used to find the best compromises between several performance measures. The analyses presented in this paper are geared to make informed decisions on the compromises of several performance measures. These analyses also allow for the identification of robust variable settings that might help to define a starting point for negotiation between multiple decision makers. Future work will include adding information about the variability of PMs on the DEA analysis and the determination of process windows with efficiency considerations. This paper discusses the application of this method to IM and how to exploit the results to determine robust process and design settings.

The development of the Gas-assisted-Reaction Injection Moulding (G-RIM) technique has been the subject of research activities at IKV for some years. To understand and explain the process phenomena observed in the Gas-assisted-Reaction Injection Moulding (G-RIM) technique, the reaction kinetics and rheological material behaviour needs to be examined. This is the subject of ongoing research activities at IKV. In this paper investigations on the rheokinetic and rheological material behaviour of a slow-reacting compact PU system are presented and mathematically described. The investigations have shown that the model developed for describing the reaction kinetics and the temperature and viscosity field reproduces the material behaviour under the real process conditions with a good degree of accuracy.

When hybrid moulds are used for the production of injection moulds, mostly the mould designer and/or plastic processor ignore the implementation of multiple mould materials and its effect on the polymer processing and material characteristics. This effect of mould material selection for injection moulds is underestimated. When one selects a mould material with poor or good thermal behaviour, it results in slower or faster cooling down of the polymer with positive or negative influence on the rheology of the injected polymer. To analyse the effect of mould material on the rheology of polymers, a hybrid micro injection mould of a spiral flow part was designed in which the flow length has been analysed for several injection moulding parameters and mould materials. Both mould and polymer analyses resulted in a better understanding of the rheology during the injection moulding process of hybrid moulds. It also resulted in a better understanding of the needed mould design strategy for multiple material moulds related to rheology, specially for micro injection moulding. Conventionally, micro moulds use techniques such as inductive heating to optimise the rheology. The research has proven that appropriate mould material selection can eliminate the need of mould heating during the injection process.

Clamping force is needed during injection molding process to keep the injection mold closed. It is a crucial parameter that must be considered during the process of plastic part development, because high clamping forces can be achieved with stronger (and more expensive) injection molding machine. It is economically wise to use processing parameters that can allow manufacturing of parts with smaller machines. The clamping force is a variable strictly related to pressure present in the cavity of the injection mold. In this study two parameters that strongly influence injection pressure (plastic flow rate and volume-to-pressure switch-over point) were examined with numerical simulations performed in Autodesk Moldflow Insight software and validated with a experiment. According to obtained outcome the increase of melt flow speed results with significant (but linear) increase of injection pressure and for investigated part the switchover point has significant impact above 98%. The nonlinear behavior of clamping force during injection phase was observed because of the energy dissipation on polymer flow. The experiment validated the direction of changes whereas the differences in comparison to simulations were observed because of the limitations of measurement systems that were present in injection molding machine.

This paper presents the experimental results regarding acoustic emission signals measured during the injection moulding of those standard test specimens commonly used for examining the shrinkage behaviour of various thermoplastic materials. The acoustic emission was measured on a new injection mould and injection mould with the visible cracks on the cavity's surface. Two resonant 150 kHz piezoelectric AE sensors were attached to tool steel inserts via AE waveguides. The results of acoustic emission testing on the crack defected tool steel insert revealed higher acoustic emission activity compared with that captured on the brand new engraving insert under same processing conditions. Specimens produced with a new and defected tool were scanned with an optical 3D digitiser. Results of the experiments confirm that acoustic emission measuring during injection moulding of polymer materials is promising technique to characterise integrity of injection moulding tool regarding occurrence of cracks.

From the decades, injection molding is one of the favored manufacturing methods used in manufacturing industries. In this method, the granular plastic is fed through hopper, and the presence of pressure the melted plastic material is injected into the cavity and acquired final products. It is very useful for mass production processes with variety of applications such as automobile, toy, bottle, chair, computer part, etc. There are some inappropriate functions where injection molding process may fail such as injector stroke is not enough, material packing is high, cooling is not enough, and white mark appears on surface of product. Therefore, the molded part may classify into four categories—part design, mold design, machine performance and method conditions. With optimum design of these categories, the performance of injection molding process may increase. The main aim of this paper is to compare the mode of heat transfer, cooling time, product quality of different plastic materials used in injection molding process as well as the design parameters are summarized for optimal design of injection molding process for product quality and performance enhancement.KeywordsInjection moldingMold flowHeat transferCooling timeCooling channels

Multi-walled carbon nanotube (MWNT) was filled into poly (ethylene terephthalate) (PET) matrix and MWNT/PET composite was prepared by injection molding process. The microstructure and electrical conductive property were investigated carefully. After injection molding, the electrical conductivity of injected sample decreased sharply because of the orientation of CNT due to strong shearing force. The electrical conductive network of CNT had been destroyed after orientation of CNT. Because of the difference of shearing rate between the surface and the body center during the injection molding process, a skin-core structure emerged. Near the surface, the injected sample has higher degree of orientation of CNT and higher electrical resistance.

Injection Compression Molding. A Low Pressure Process for Manufacturing Textile-Covered Mouldings

Optimization and parameter adjustment of an injection molding (IM) process depend largely on a good modelling and prediction of industrial process, which has been received considerable attention in recent years. However, IM process is a typical multivariate production process with multiple product quality indices. It poses a great challenge for multi-output quality prediction problem to select key process variables as input with good interpretability. This study proposes a multivariate quality prediction method for IM process using copula entropy (CE) and multi-output support vector regression (MSVR). First, copula entropy is employed to characterize the association relationships between each process variable and the set of quality indices, thus key process variables can be selected by ranking CE. Then, the quantitative relationship between key process variables and quality indices is established by MSVR. Finally, the proposed method is tested by the experiment on a real IM process dataset. This study will provide an important reference for modelling and prediction of IM process and other multi-output problems.

Treatment for breast cancer has increased patient survivorship exponentially over the past few decades. With increased survivorship, more women are living with the longstanding effects of breast cancer treatment, such as lymphedema. Patients, health care providers, and payers depend on practical and efficient clinical measures to accurately diagnose and monitor disease progression or regression. However, current clinical measures do not include objective measures that assess lymphedetamous tissue accurately. This study compared current measures to a novel use of ultrasound (US) imaging to quantify tissue texture. Seventeen women diagnosed with lymphedema completed self-report questionnaires and then were tested twice by two lymphedema physical therapists who measured edema, fibrosis, and limb volume differences. One therapist measured subjects' limbs using US imaging and derived measures of entropy and average pixel intensity. Volume measures were consistent between therapists (p < 0.01) but palpation was not (0.01 < p < 0.72). Therapists' measures correlated better to subjects' self-report of edema (0.01 < p > 0.32) as compared to fibrosis (0.23 < p > 0.90). US measures were reliable (Cronbachs's α = 0.7 and 0.91 for entropy and API, respectively). Entropy measures demonstrated significant differences between subjects' involved versus uninvolved forearms (p = 0.03). Therapists were not consistent with each other when rating edema or fibrosis; however, they were consistent when measuring limb volume differences. US measures (entropy) demonstrated a significant difference between involved and uninvolved. US imaging, as a tool to quantify subcutaneous tissues, holds promise to be a safe, mobile, and effective method to measure lymphedema tissue texture.

Today, around 30% of manufactured plastic goods rely on injection moulding. The cooling time can represent more than 70% of the injection cycle. In this process, heat transfer during the cooling step has a great influence both on the quality of the final parts that are produced, and on the moulding cycle time. Models based on a full 3D finite element method renders unpractical the use of optimization of the design and placement of the cooling channel in injection moulds. We have extended the use of boundary element method (BEM) to this process. We introduce in this paper a practical methodology to optimize both the position and the shape of the cooling channels in injection moulding processes. We couple the direct computation with an optimization algorithm such as SQP (Sequential Quadratic Programming). First, we propose an implementation of the model reduction in the BEM solver. This technique permits to reduce considerably the computing time during the linear system resolution (unsteady case). Secondly, we couple it with an optimization algorithm to evaluate its potentiality. For example, we can minimize the maximal temperature on the cavity surface subject to a temperature uniformity constraint. Thirdly, we present encouraging computational results on plastic parts that show that our optimization methodology is viable.