Plastic Injection Research Articles

Energy-carbon neutrality optimization in production scheduling via solar net metering

Energy is an indispensable resource in manufacturing, and it carries both financial and environmental pressures for enterprises. Considering this importance, this research presents an optimization framework to allow energy-intensive industries to move towards energy-carbon neutrality via production scheduling and renewable energy. This involves integrating renewable energy system decisions into production scheduling, incorporating solar photovoltaic modules and energy storage systems, and leveraging energy policies, such as net metering programs, that provide credits for net excess generation. The proposed optimization framework is built under a multi-objective Mixed Integer Linear Programming formulation, using time-indexed variables. The model is showcased within the context of a case study involving an energy-intensive plastic injection molding process. Furthermore, a robust optimization approach using Monte Carlo simulations is presented for the construction of confidence intervals used in estimating the lifespan of solar installations. Results demonstrate that manufacturing systems that enable their solar photovoltaic system with an energy storage dispatching capability are more cost competitive to lower net metering compensation rates than those that do not.

Effect of static mixer on optical properties of plastic injection molded parts

AbstractThe effect of an in‐mold static mixer on the optical properties of polystyrene (PS) parts was explored within the injection molding process. Several mixers were assessed via simulation and molding trials to identify the mixing ability and effect on optical properties including retardation and birefringence. It was found that the static mixers within the runner could successfully mix the polymer and disrupt property distributions including temperature but that there was only a slight improvement in retardation with some of the mixer cases. The experiments and simulations showed relatively good correlation in results although there were slight differences in the trends that could be due to the experimental measurement resolution or unaccounted‐for variables between the experiments and simulations. The retardation was experimentally measured using a custom‐made polariscope using photography and image processing. These experiments indicated that the use of a static mixer within the runner system of a mold could be used for homogenizing the polymer melt after the plasticizing unit. However, its effect on improving the optical performance of injection molded parts could be offset by the melt flow downstream of the static mixer and the potential increase of residual stresses due to flow restriction, suggesting the importance of mixer location and geometry.

Mold Design and Analysis for Multi-Component Plastic Injection Parts with Contrasting Functional Features: Case Study

The classical plastic injection method is based on the principle of injecting a single color of a single polymeric material into the mold cavity under high pressure. In cases where the products are expected to have contrasted functional features and different colors, the classic injection process and the conventional injection molds are not sufficient. This paper proposes a new design approach for multi-component injection molds required by products containing different polymeric materials or different colors of the same polymeric material at the same time. It also presents a case study including the design of the hot runner, electromechanical rotary-cross, cooling, and ejection systems of a two-component, eight-cavity toothbrush mold. The polymeric materials are polypropylene for the first component, and styrene based thermoplastic elastomer for the second component, which exhibit good bonding properties with each other. In addition, an analysis study covering the filling parameters and production defect generations is also provided. The adopted design approach provides a production rate of 1600 parts per hour, corresponding to 18 s cycle time and 200 cycles per hour, and makes it sufficient to rotate only the 80 kg core plate instead of 1120 kg entire core side. Compared to existing methods, the results show that the proposed multi-component injection mold design method eliminates the need for particular injection machines and robotic systems, shortens the cycle time, and reduces energy consumption.

Value Chain Comparison of Additively and Conventionally Manufactured Multi-Cavity Tool Steel Inserts: An Injection Molding Industrial Case Study for High-Volume Production

The development of injection molding tools is an expensive, time-consuming, and resource-intensive process offering little to no flexibility to adapt to variations in product design. Metal additive manufacturing can be used to produce these tools in a cost-effective way. Nevertheless, in an industrial context, effective methods are missing for the selection of the most suitable technology for the given tooling project. This paper presents a method to compare process chains based on additive and conventional subtractive technologies for the manufacturing of metal tooling for injection molding. The comparison is based on a technology focused-performance analysis (TFPA) through computer simulation performed using Tecnomatix Plant Simulation developed by Siemens Digital Industries Software combined with a customized cost–benefit economic analysis tool. The analysis of the technology comparison highlights potential bottlenecks for production, such as the printing phase and the heat treatment. It also gives a deeper understanding of the technology maturity level of conventional milling machines against laser powder bed fusion machines. The result is that the total costs for an insert made by AM and CM are indeed rather similar (the cost difference between the two tooling process chains is lower than 5%). The cost analysis reveals major costs drivers in the production of high-performance molding tools, such as the cutting tools employed for the milling steps and their changeover frequency. The industrial case of a 32-cavity mold insert for plastic injection molding is used to perform the study, develop the analysis, and validate the results.

Production of a multi-functional 420 stainless steel-copper surface by laser texturing and hot pressing: a new solution for plastic injection moulds

Production of a multi-functional 420 stainless steel-copper surface by laser texturing and hot pressing: a new solution for plastic injection moulds

Using an Artificial Neural Network Approach to Predict Machining Time

One of the most critical factors in producing plastic injection molds is the cost estimation of machining services, which significantly affects the final mold price. These services’ costs are determined according to the machining time, which is usually a long and expensive operation. If it is considered that the injection mold parts are all different, it can be understood that the correct and quick estimation of machining times is of great importance for a company’s success. This article presents a proposal to apply artificial neural networks in machining time estimation for standard injection mold parts. For this purpose, a large set of parts was considered to shape the artificial intelligence model, and machining times were calculated to collect enough data for training the neural networks. The influences of the network architecture, input data, and the variables used in the network’s training were studied to find the neural network with greatest prediction accuracy. The application of neural networks in this work proved to be a quick and efficient way to predict cutting times with a percent error of 2.52% in the best case. The present work can strongly contribute to the research in this and similar sectors, as recent research does not usually focus on the direct prediction of machining times relating to overall production cost. This tool can be used in a quick and efficient manner to obtain information on the total machining cost of mold parts, with the possibility of being applied to other industry sectors.

Artificial Neural Network Training Using Structural Learning with Forgetting for Parameter Analysis of Injection Molding Quality Prediction

The analysis of influential machine parameters can be useful to plan and design a plastic injection molding process. However, current research in parameter analysis is mostly based on computer-aided engineering (CAE) or simulation which have been demonstrated to be inadequate for analyzing complex behavioral changes in the real injection molding process. More advanced approaches using machine learning technology specifically with artificial neural networks (ANNs) brought promising results in terms of prediction accuracy. Nevertheless, the black box and distributed representation of ANN prevent humans from gaining an insight into which process parameters give a significant influence on the final prediction output. Therefore, in this paper, we develop a simpler ANN model by using structural learning with forgetting (SLF) as the algorithm for the training process. Instead of typical backpropagation which generated a fully connected layer of the ANN model, SLF only reveals the important neurons and connections. Hence, the training process of SLF leaves only influential connections and neurons. Since each of the neurons specifically on the input layer represent each of the injection molding parameters, the ANN-SLF model can be further investigated to determine the influential process parameters. By applying SLF to the ANN training process, this experiment has successfully extracted a set of significant injection molding process parameters.

Heat Dissipation Plays Critical Role for Longevity of Polymer-Based 3D-Printed Inserts for Plastics Injection Moulding

Injection moulding is a polymer processing method of choice for making plastic parts on industrial scale, but its traditional mould is made from tooling steel with time-consuming and costly production. Additive manufacturing technologies arise as an alternative for creating mould inserts at lower costs and shorter lead times. In this context, this study describes a series of stereolithography (SLA)-printed injection mould inserts fabricated from two photopolymer resins, utilised to mould standard tensile specimens of a commercial-grade polypropylene, aiming to evaluate effects on the polymer’s thermal and mechanical properties. Our results demonstrated that the glass fibre-filled resin inserts withstood more moulding cycles before failure, had superior mechanical properties, higher Tg and greater thermal conductivity. Calorimetric data revealed that PP thermal properties and degree of crystallinity were little affected, while mechanical testing suggests a significant effect in the elongation at break. Thus, these findings highlight the importance of adequate heat extraction during injection moulding and endorse further application of SLA mould inserts for the manufacturing of injection-moulded plastic parts in the case of prototypes or small batches, provided suitable cooling is made available, contributing to the feasibility and affordability of employing this approach for an industrial setting.

Optimization of the injection moulding process for plastics parts by using FEA

The paper presented the process of injection moulding for plastics with their innovative technologies and moulded plastic materials. The main goal of this research is to present a practical method for analysing the optimization parameters process of plastic injection moulding, such as filling time, melt temperature, mould temperature, maximum injection pressure, injection volume, cooling time, cycle, etc., The simulation was applied on a PC+ABS BAYBLEND T65 XF sample by using the FEA of Moldex3D Program.

Plastik Enjeksiyon Kalıplamada Farklı Soğutma Sistemlerinin Karşılaştırılması

Injection molding is preferred for plastic products due to its high efficiency. However, one of the most important factors after injection is the cooling of the part. Therefore, the cooling process considers being an essential part of the total molding time. Generally, the cooling process in plastic injection molds is done by circulating the cooling liquid through the holes opened in the radial and axial direction on the mold. However, in cases where the cooling is not at the wanted level, the efficiency is increased by placing high thermal conductivity coefficients materials in the molds. With the development of manufacturing methods, conformal cooling systems with cooling channels that follow the molded part geometry have emerged as an alternative to this method. However, this is an expensive method, and studies are ongoing. In this study, the mold cooling times were analyzed and compared with the help of the MoldFlow analysis program on a sample part with a conventional cooling system, as a result of placing a conformal cooling system and a material (insert) with a high thermal conductivity coefficient in the mold.

Multi response optimization of injection moulding process to reduce sink marks and cycle time

In the rapidly growing field of technology, there is a demand for consumer goods made of plastic. To meet needs of customer, plastic products are made in different ways. There are different plastic manufacturing process. Numerous plastic manufacturing process are thereInjection molding is involves injecting molten material into a mold and allowing it to take on the shape of the mold.There are wide ranges of products such as plastic chairs, Computer cabinet etc. are manufactured with the help of smaller and more complex profiles. Due to lack of dimensional accuracy these complex profile produces defects inside the mold. Current study provides insights into transparent thermoplastic Polypropylene products. Five plastic injection molding variable criteria are considered for reducing the depth of sink mark in injection molding for commercial grade transparent thermoplastic (Polypropylene). Melting temperature (8C), mold temperature (8C), packing time (seconds), ratio of ribs to walls (%) and rib to gate distance (mm). According to Taguchi's design L27 experiments are performed and factors are optimized using the Taguchi based utility concept for multi criteria problems. The sink mark's depth on the part's surfaceis considered as quality of product and cycle time is considered as the productivity of product. It is the one of the best techniques, which can maintain the equilibrium between two.

Increasing the Sustainability of Manufacturing Processes in Plastic Injection: Recovering Out-Of-Service Robots to Eliminate Manual Assembly Operations

In the 20th century, there was a burst concerning the development of the automobile industry, which has become an essential asset for society. With its evolution, this industry created a foundation that based its competitiveness on satisfying people’s needs with the highest possible quality and always respecting the delivery deadlines. With the growth in demand, the improvement of certain processes was needed to achieve the desired production goals, accomplished through automation and robotics, as production and assembly lines increasingly used fully automated processes. In plastic injection lines, production is constant and carried out quickly, so it is desirable to perform component assembly steps that immediately support the output of the injection mould parts. This work consists of adapting an obsolete robotic cell to be implemented in one of the production lines to insert components into the injected parts, replacing labour work. Through a mechanical project and an automation design, the equipment was concluded and is currently in production, fulfilling the necessary requirements and improving the process’ cycle time. This proves that it is possible to recover old equipment, which is able to improve current tasks and common needs in modern industry, increasing the economic sustainability of the processes and saving resources.

Vibration Extraction for Melting Plastic Hydraulic Injection System with Stick Slip Vibration Analysis

IntroductionA hydraulic power injection machine is designed to use a driving screw to inject melted plastic into a specified mold. This machine can be found at an automotive spare parts factory. The cantilever-style heavy-duty screw injector is supported by one roller and secured at the end. An obvious need for vibration analysis on the roller support is essential. A mass spring damper model is proposed for deeply investigating the friction induced vibration mechanism for this injection system to well understand and analyze its vibration behavior.PurposeA mechanical mode of two degrees-of-freedom (DOF) is designed to improve research on the dynamic features of the Plastic Hydraulic Injection System (PHIS) mechanism.Materials and methodsExperimental investigation and analysis of this mechanism are explored to obtain the instability speed and critical stick slip (SS) speed. The numerical imitation results of this work will help with the design and development of the PHIS mechanism.ConclusionThe stability of the system and SS behavior are next examined by determining the critical variability speediness and critical SS speed. A simulation study is carried out to evaluate the effect of various parameters of the system on its stability and on the behavior of the SS motion.

The Correlation Between the Number of Heater and Energy Saving on Plastic Injection Molding

The number of human populations is increasing as well as daily needs and consequently increased the number of wastes that being produced including plastic waste. Indonesia itself consumed 17 kg/capita per year. Recycling the plastic waste is one of alternatives way to reduce waste, by melting the plastic waste using six heaters from electrical energy source. This research was conducted to obtain number of heaters that will be used in the injection molding process by considering the time consumed for the temperature of 50⁰ - 210⁰ C. The observation is being done by measuring the temperature and power supplied from 3, 4, 5 and 6 heaters and repeated for 3 times experiment. Based on the measurement data that has been carried out, it is found that the highest average power is the injection with six numbers of heaters consumed 956.80 W. The time measurement required to reach optimal temperature, for 3 number of heaters was taking the longest time which is 2842 Seconds. This condition is in line with the average of electrical power consumed to reach the optimal temperature is the using of the heaters 0.350 kWh. Based on three hypotheses that being done, the result shows that the Ha is accepted and there is significant influence between three models that being made.

Parameter Optimization of PET Plastic Preform Bottles in Injection Molding Process Using Grey-Based Taguchi Method

The paper investigated the optimization design of plastic injection molding process parameters for preformed bottle production using the grey-Taguchi method to minimize shrinkage defects. Diametrical (radial) and length (axial) shrinkage were taken as the responses for one-liter PET plastic preform bottle to perform optimization by controlling four injection molding process parameters. The obtained optimum parameter combination was 260°C melting temperature, 70°C molding temperature, 120 MPa holding pressure, and 15 s cooling time. Melting temperature was the most significant factor according to the ANOVA in PET plastic preform of bottle production. The experimental validation test was also performed using the optimal level settings, five samples of preforms were taken, and the result showed that the shrinkage of the preform was reduced by 22.55%. The average grey relational grade, 0.853, of the confirmation results was found between the confidence intervals of 0.581 and 1.125 for the 95% confidence level. Therefore, the confirmation test showed a good agreement between the predicted and experimental values.

Quality Monitoring and Multi-Objective Optimization of the Glass Fiber-Reinforced Plastic Injection Molded Products

Quality Monitoring and Multi-Objective Optimization of the Glass Fiber-Reinforced Plastic Injection Molded Products

Novel Method for Failure Modes Detection in UV-Cured Clear Coated Polymer for Automotive Interior Mechatronic Devices.

Plastic parts used in automotive interior are difficult to coat, due to their low surface energies as well as their sensitivity to temperature and solvents, rendering the development of coating systems for such substrates challenging. Automotive customer requirements are explicit and clear, mainly focused on functional and surface defects. A new failure modes detection methodology of UV clear coated polymers for automotive interior, obtained by a multi-step manufacturing process, is proposed. The polymer complex parts analyzed in this paper are manufactured in various steps as follows: two components plastic injection molding, primer coating, laser engraving, and UV-cured clear coating. The failure modes detection methodology of the parts within each process step is investigated using different tests and analyses as follows: surface tension test, painting adhesion test, optical 3D measuring, energy dispersive X-ray analysis (EDX), and microscopy. A design of the experiments (DoE) based on the Taguchi technique with the aim to detect the influence of the main factors that lead to surface defects was performed. The proposed methodology is validated by a case study. The results showed that the mold temperature and the laser engraving current have a significant influence on the surface defect occurrence. Additionally, a possible contamination of the molding tool can generate the defects. A solution to reduce the occurrence of the failures was proposed, reducing the defect rate from 50% to 0.9%.

Impact of New Design in a Plastic Injection Mold Made by Additive Manufacturing

Impact of New Design in a Plastic Injection Mold Made by Additive Manufacturing

Industry 4.0 In-Line AI Quality Control of Plastic Injection Molded Parts.

Automatic in-line process quality control plays a crucial role to enhance production efficiency in the injection molding industry. Industry 4.0 is leading the productivity and efficiency of companies to minimize scrap rates and strive for zero-defect production, especially in the injection molding industry. In this study, a fully automated closed-loop injection molding (IM) setup with a communication platform via OPC UA was built in compliance with Industry 4.0. The setup included fully automated inline measurements, in-line data analysis, and an AI control system to set the new machine parameters via the OPC UA communication protocol. The surface quality of the injection molded parts was rated using the ResNet-18 convolutional neural network, which was trained on data gathered by a heuristic approach. Further, eight different machine learning models for predicting the part quality (weight, surface quality, and dimensional properties) and for predicting sensor data were trained using data from a variety of production information sources, including in-mold sensors, injection molding machine (IMM) sensors, ambient sensors, and inline product quality measurements. These models are the backbone of the AI control system, which is a heuristic model predictive control (MPC) method. This method was applied to find new sets of machine parameters during production to control the specified part quality feature. The control system and predictive models were successfully tested for two groups of quality features: Geometry control and surface quality control. Control parameters were limited to injection speed and holding pressure. Moreover, the geometry control was repeated with mold temperature as an additional control parameter.

Plastic injection molding dies using hybrid additively manufactured 420/CX stainless steels: electrochemical considerations

This research focused on the corrosion resistance and microstructure of hybrid additively manufactured (HAM) samples of AISI 420/CX (420/CX SS) stainless steels. Potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and Mott–Schottky analyses as well as the electrochemical noise (EN) technique were used to evaluate the electrochemical behavior of the as-built and heat-treated HAM parts in NaCl solution. The results showed a more protective passive layer formed on the CX SS side. The distribution of Cr-rich M23C6 carbides in matrix of 420 SS side resulted in a lower corrosion resistance compared to the CX SS side. The noise data analysis confirmed an increase in the galvanic currents of the HAM parts after heat treatment. The stochastic analysis revealed the interface in the heat-treated condition increases pit growth more than the as-built one due to the evolution of nano-sized intermetallic compounds of Al-N/ (Cr, Nb) (N, C) at the heat-treated interface area.