Plastic Injection Moulding Machine Research Articles

Design Of A Heating System In A Plastic Injection Molding Machine With A Working Temperature Of 250 C

The working system of the heating process on a plastic injection molding machine needs to be considered in more detail. Due to the influence of temperature and the type of material according to the quality of the product. In this study, the plastic injection machine that used a temperature variation used several different variations, and three experiments were given at each temperature variation of 200°C – 250°C using 75 grams of plastic material with a heating time of 120-141 seconds and 150 grams of plastic material with a heating time of 120-141 seconds. Warm-up 210-250 seconds. Temperature control using the REX C100 Controller. The injection machine can operate according to the design. Namely, the heating temperature can be adjusted. Implementation and control of the control system show a good response. The plastic to be melted is of the HDPE (High-Density polypropylene) type with a temperature for melting the plastic of 250°C.

Automatic Material Filling Machine for IBM

Abstract: Technological advancements are taking place day- by-day and industrial growth has been the key aspect of development of any nation. In plastic injection moulding machine, the provision is to transfer powder raw material from ground to the hopper is not provided or the powder transfer can be done manually in machine. Many small scale industries has moulding machine where they have to fill the raw material at a height where a human efforts are needed which increases the production time rate, leads to increases the wastage of raw materials. Also limited space and hence the system cost increases design of Raw Material feeding mechanism is made as per small scale industries need by considering the above constraints and accordingly. Accordingly theoretical design calculations are made for mini hopper, material volume. Types of raw materials Polyvinylchloride, Polypropylene are selected and testing their total fill time, empty time. Power consumption rate with respect to height in a design of raw material hopper feeding mechanism. Overall, this project involves processes like design, analysis, fabrication and assembling of different components

Development of a Reliable Vibration Based Health Indicator for Monitoring the Lubricating Condition of the Toggle Clamping System of a Plastic Injection Molding Machine

Plastic injection molding has become one of the most widely used polymer processing methods due to its ability to viably produce large volumes of complex parts in a short time frame. Most of the plastic injection molding machines currently used in industry possess a toggle clamping mechanism that undergoes a repeated clamping and unclamping cycle during operation. This toggle must therefore be properly lubricated to avoid catastrophic failure and eventual machine downtime. To overcome this limitation, the industry currently relies on the experience of a skilled operator, paired with a fixed empirical value, to determine the timing for re-lubrication. This method often leads to the machine operator either wasting lubricant by over-lubricating the toggle, or damaging the toggle by failing to re-lubricate when needed. Herein, we explore the use of vibration analysis to perform real-time condition monitoring of the lubrication condition of the toggle clamping system. In this study, our novel structural response analysis out performed both traditional time domain and frequency domain analyses in isolating the vibrational signatures indicative of lubricant degradation. Additionally, this study confirms that the vibration generated during the unclamping period of the toggle, proved to contain more valuable information relevant to the instantaneous lubricant quality than provided by its corresponding clamping period.

Rule-based explanations based on ensemble machine learning for detecting sink mark defects in the injection moulding process

Manufacturing quality control (QC) in plastic injection moulding is of the upmost importance since almost one third of plastic products are manufactured via the injection moulding process. Moreover, smart manufacturing technologies are enabling the generation of huge amounts of data in production lines. This data can be used for predicting the quality of manufactured plastic products using machine learning methods, allowing companies to save costs and improve their production efficiency. However, high-performance machine learning models are usually too complicated to be understood by human intuition. Therefore, we have introduced a rule-based explanations (RBE) framework that combines several machine learning interpretation methods to help to understand the decision mechanisms of accurate and complex predictive models – specifically tree ensemble models. These generated rules can be used to visually and easily understand the main factors that affect the quality in the manufacturing process. To demonstrate the applicability of RBE, we present two experiments with real industrial data gathered from a plastic injection moulding machine in a Singapore model factory. The collected datasets contain condition data for several manufacturing processes as well as the QC results for sink mark defects in the production of small plastic products. The experiments revealed that it is possible to extract meaningful explanations in the form of simple decision rules that are enhanced with partial dependence plots and feature importance rankings for a better understanding of the underlying mechanisms and data relationships of accurate tree ensembles.

A Density-based Clustering Approach for Monitoring of Injection Moulding Machine

Fault Detection and Isolation (FDI) is crucial and challenging problem in many industrial applications and continues to be an on-going research issue in the control community. In the literature, model-based techniques are mostly employed to generate residuals for diagnosis and decision-making. In this paper, we focus on FDI problem using a novel based-clustering approach. The key idea is to restrict each fault to be a data cluster with high-density gathering the most similar objects. In this way, the algorithm does not require prior analytic models to start. It uses rather a density measurement to detect and isolate cluster’s regions. The overall algorithm is expanded around two fundamental steps: cluster domain description and density-based clustering. To address properly the requirements of system control and monitoring, the algorithm is designed to work in real-time as observations are acquired and it is endowed with specific tools for data mining and feature extraction. A study case is proposed consisting of plastic Injection Molding Machine (IMM) to prove the effectiveness of the method.

Optimization of Process Parameters of Plastic Injection Molding Machine by using Taguchi Method

Optimization of Process Parameters of Plastic Injection Molding Machine by using Taguchi Method

Optimization of mold temperature profile and process parameters for weld line reduction and short cycle time in rapid heat cycle molding

Weld line reduction is one of the major concerns in plastic injection molding (PIM) that results in high surface appearance and high strength of a plastic product. To resolve this issue, rapid heat cycle molding (RHCM) has attracted attention as an innovative PIM technology. In the RHCM, the mold temperature profile plays a crucial role in weld line reduction. On the other hand, high productivity as well as high surface appearance is also required in the PIM, and the trade-off between them will be observed. To achieve weld line reduction and high productivity simultaneously, it is important to adjust both the mold temperature profile and other process parameters in RHCM. A trial and error method is so widely used to adjust them, but it is much time-consuming task. In this paper, the mold temperature profile and several process parameters are optimized for the weld line reduction and the short cycle time. Therefore, multi-objective design optimization is performed. Numerical simulation in PIM is so intensive that a sequential approximate optimization using radial basis function is adopted to identify the Pareto frontier with a small number of simulations. The trade-off between the weld line reduction and the cycle time is clarified through the numerical result. Based on the numerical result, the experiment using a PIM machine (GL100, Sodick) is carried out. It has been confirmed through the numerical and experimental result that the proposed approach in RHCM is valid for the weld line reduction and the short cycle time.

Implementation of Voltage Optimization for Sustainable Energy

<p>The voltage control in the power distribution network is challenged firstly by constantly increasing in power demand and secondly by a growing number of distributed connections, which significantly changes the load flow in the network. Situation is worsening with the current heavily implemented micro-generation of Solar PV. Consequently, the uncontrollable rapid changes in the power distribution network would affect voltage instability at the feeder with wide area power demand. Voltage instability would affect the energy efficiency of the electrical equipment. Moreover, the lifespan of some equipment would be shortened due to the excessive and unstable voltage supplied. The proposed research aims to implement the low impedance voltage optimization system in solving the existing problem. The voltage optimization system had been tested on both resistive and inductive loads. The power consumption of the loads had been measured at a few discrete values of voltage optimization within the statutory region. Further tests were conducted on industrial water pump, general lightings with mixed loads, office building, restaurant and plastic injection moulding machine. The power measurements were logged and the results in term of power consumption were analysed. The results showed that the proposed optimization mechanism successfully optimize and saved 6.81%, 14.42%, 13.97%, 12.23%, and 26.23% of the power consumptions in respective tests.</p>

Numerical and experimental investigation on process parameters optimization in plastic injection molding for weldlines reduction and clamping force minimization

Weldlines are one of the major defects in plastic injection molding (PIM). The weldlines have an influence on not only the appearance of product but also the strength, so it is important to reduce the weldlines as much as possible. The melt plastic will be quickly solidified with the low weldline temperature that makes the weldlines long. On the other hand, clamping force also affects the product quality, but the relationship between the weldlines and the clamping force is rarely discussed in the literature. In this paper, the minimum weldline temperature is maximized for the weldlines reduction, whereas the clamping force is minimized for the high product quality. Therefore, a multi-objective design optimization of the process parameters is performed and the pareto-frontier between them is identified. Numerical simulation in PIM is generally so intensive that a sequential approximate optimization using a radial basis function network is used to identify the pareto-frontier. 3D cooling channel is used for the design optimization. Through the numerical simulation, the trade-off between the minimum weldline temperature and the clamping force is clarified. In addition, it is found that the 3D cooling channel is effective for the weldlines reduction and clamping force minimization, compared with the straight-type cooling channel. Finally, to examine the validity of the proposed approach, the experiment using the PIM machine (GL30-LP, Sodick) is carried out. It is found through the experimental result that the weldlines are reduced by the proposed approach.

Numerical and experimental investigation of process parameters optimization in plastic injection molding using multi-criteria decision making

In plastic injection molding (PIM), the process parameters such as packing pressure, melt temperature, and cooling time should be adjusted and optimized for high product quality and high productivity. Warpage is one of the major defects in the PIM and should be minimized for high quality. Cycle time should be minimized for the high productivity. In addition to the warpage and the cycle time, clamping force affects the product both the quality and the productivity. Therefore, for the high product quality and the high productivity, it is important to minimize the warpage, the cycle time and the clamping force simultaneously. In this paper, a multi-objective optimization of process parameters in PIM for minimizing three objectives is performed. Numerical simulation in the PIM is generally so intensive that a sequential approximate optimization using radial basis function network is adopted to determine the optimal process parameters. The radar chart is used to perform the trade-off analysis among three objective functions. In addition, the better and worse solution are newly introduced for the trade-off analysis. It is found through the trade-off analysis that all objective functions of the conformal cooling channel are well improved in comparison with the ones of the conventional cooling channel. Therefore, 43% warpage reduction, 1,7% clamping force reduction, and 47% cycle time reduction can successfully be achieved using the conformal cooling channel. Based on the numerical result, the experiment using PIM machine (GL30-LP, Sodick) is carried out. The conformal cooling channel is developed by the metal 3D printer (OPM250L, Sodick). Through the numerical and experimental result, the validity of the proposed approach is examined.

Green density optimization of stainless steel powder via metal injection molding by Taguchi method

Metal injection moulding (MIM) has gains much attention due to its ability in producing large amount of small part with complex geometry and intricate shape. In order to obtain better shape retention, optimum density of green part is required. This paper deals with the application of Taguchi method in optimising the green density of moulded components base on parameters setting in plastic injection moulding machine. For this purposes only 7 process parameters were considered here are injection pressure, injection temperature, cooling time, injection speed, injection time, packing time and mould temperature. An orthogonal array of L27 experimental base design was conducted. Base on the experimental results, cooling time plays significant contribution to density followed by injection pressure, time, speed, mould temperature, packing time and injection temperature. Confirmation test was done base on optimization level for each factors and shows good results in green density of the injected moulded samples.

사출성형기의 고장모드 영향분석(FMEA)을 활용한 위험 우선순위

Plastic injection moulding machine is widely used for many industrial field. It is classified into mandatory safety certification machinery in Industrial Safety and Health Act because of its high hazard. In order to prevent industrial accidents by plastic injection moulding machine, it is necessary for designer to identify hazardous factors and assess the failure modes to mitigate them. This study tabulates the failure modes of main parts of plastic injection moulding machine and how their failure has affect on the machine being considered. Failure Mode & Effect Analysis(FMEA) method has been used to assess the hazard on plastic injection moulding machine. Risk and risk priority number(RPN) has been calculated in order to estimate the hazard of failures using severity, probability and detection. Accidents caused by plastic injection moulding machine is compared with the RPN which was estimated by main regions such as injection unit, clamping unit, hydraulic and system units to find out the most dangerous region. As the results, the order of RPN is injection unit, clamping unit, hydraulic unit and system units. Barrel is the most dangerous part in the plastic injection moulding machine.

Multiobjective Design of Turbo Injection Mode for Axial Flux Motor in Plastic Injection Molding Machine by Particle Swarm Optimization

This paper proposes a turbo injection mode (TIM) for an axial flux motor to apply onto injection molding machine. Since the injection molding machine requires different speed and force parameters setting when finishing a complete injection process. The interleaved winding structure in the motor provides two different injection levels to provide enough injection forces. Two wye-wye windings are designed to switch two control modes conveniently. Wye-wye configuration is used to switch two force levels for the motor. When only one set of wye-winding is energized, field weakening function is achieved. Both of the torque and speed increase under field weakening operation. To achieve two control objectives for torque and speed of the motor, fuzzy based multiple performance characteristics index (MPCI) with particle swarm optimization (PSO) is used to find out the multiobjective optimal design solution. Both of the torque and speed are expected to be maximal at the same time. Three control factors are selected as studied factors: winding diameter, winding type, and air-gap. Experimental results show that both of the torque and speed increase under the optimal condition. This will provide enough large torque and speed to perform the turbo injection mode in injection process for the injection molding machine.

Design with Concurrent Approach: Development and Flow Analysis of Injection Mould Tool for Computer Monitor Lamp Holder

The plastic product manufacturing industry has been growing rapidly in recent years. One of the most popular processes for making plastic parts is injection moluding. The design of injection mould is critically important to product quality and efficient product processing. Mould-making companies, who wish to maintain the competitive edge, desire to shorten both design and manufacturing leading times by applying a systematic mould design process. The mould industry is an important support industry during the product development process, serving as an important link between the product designer and manufacturer. Product development has changed from the traditional serial process of design, followed by manufacture, to a more organized concurrent process where design and manufacture are considered at a very early stage of design. The research presents the basic structure of two plate injection mould design, injection moulding machine selection, process analysis of the injection mould design using mould flow analysis to optimize the mould cost in the design stage. This injection mould design system covers both the mould design process and mould knowledge management. In this work, CAE tools have been used in the design stage to reduce the losses to obtain the shortened lead time, high quality and achieving low cost of the mould. The design of an injection process involves the simultaneous consideration of plastic part design, mould design and injection moulding machine selection, production scheduling and cost as early as possible in the design stage. The result indicated that conventional method will consume more time and also increases the cost of machining and delay in dispatching the product. If change in design happens before pre-production and after production by trial and error method then there will be a drastic increase in design change cost which effects on cycle time, waste of raw material, increase in process time and wastage of labour cost. These entire draw backs are eliminated by using computer aided design and computer aided engineering technology for mould design and manufactured in very short period of time with minimum cost. The future scope of work is to include cooling, warpage and fatigue analysis to optimize tool design and tool life.

Near-optimal prediction of geometrical requirements of injection moulded parts using Mamdani-based fuzzy logic controller

Injection moulding process is popularly used to fabricate complex and intricate parts with thermo plastic and composite materials. In this paper, Mamdani-based fuzzy logic (FL) controller has been developed to predict the quality of the parts produced using plastic injection moulding machine. It is to be noted that the quality of the parts produced depends on various geometrical requirements, such as global warpage, lower edge surface planarity and hole circularity of the manufactured part. However, these geometrical requirements depend on various input process parameters, namely melting temperature, mould temperature, packing time and packing pressure. As the input-output relationship of the injection moulding process is highly non-linear, FL technique is considered to model the process. It is important to note that the performance of the FL system depends on its knowledge base (that is, rule base and database) developed by the human expertise. In the present paper, genetic algorithm (GA) is used to optimise the optimal knowledge base of the FL system. Further, the prediction accuracy of the developed models has been tested with the help of 20 test cases and found reasonably good accuracy.

Design of an Intelligent Tool for the Observation and Follow-Up of Lockout Procedures during Maintenance Activities on Industrial Machines

Workers performing maintenance, repair and un-jamming operations on industrial machines and processes are required to follow lockout procedures in accordance with occupational health and safety regulations. However, industries seem to have difficulties in the appropriation and implementation of lockout. Reports of severe accidents, often fatal, involving industrial machinery show the extent of the problem concerning the application of lockout procedures. In this context, an intelligent tool incorporated at the design stage of a machine, which helps to apply and record lockout procedures, could be useful. Thereby, the design of a laboratory prototype has been explored for a particular maintenance task on an automated plastic injection moulding machine. Its architecture has been based on three electronic cards, sensors and wireless communications. Despite the limitations of the current version of the tool, the feasibility of designing an intelligent tool capable of following and recording lockout procedures is demonstrated.

Development Overview and Direction of Energy-Saving Technology on Plastic Injection Molding Machine

The main energy-saving method of injection molding machine is that variable-frequency technology, variable pump system, servo control technology or energy accumulator is used to improve the hydraulic system and the efficiency of effective energy used on a hydraulic-driven system. At present, a larger development has been achieved in the injection molding machine energy-saving technology, but there are still some shortcomings, in order to better promote the research and development of energy-saving technology of injection molding machines, the characteristics of various energy-saving means of plastic injection molding machines is summarized and on this basis that the development direction of energy-saving technology of injection molding machines is put forward.

Quality Improvements by Implementing Lean Manufacturing Principles

Nowadays, customers are well aware of quality and they purchase only quality products. Thanks to globalization! In order to achieve highest quality products, companies need to adapt the latest and advanced technologies in their industries. Failure to adapt these new trends would lead to less profit and or huge loss and eventually shutdown of their business to its competitors. A case study on discrete manufacturing company was conducted to analyze the above phenomenon. The selected case study company is pioneer in manufacturing plastic injection moulding machines in India. Several lean tools and techniques are implemented to eliminate its unwanted waste in their production line. All these aid to development of optimum facility layout, good workplace, ergonomic designed work cells for operators, improvement in productivity of the operator (by 28%), to name a few. By achieving all these, the overall product (plastic injection moulding machine) quality is improved by 23%.

Design of Open Motion Control System in Fully Electrical Plastic Injection Molding Machine

This paper intends to configure a control system of the plastic injection molding machine using a Motion Controller. It narrates the wiring methods of the control system based on “PC + Motion Controller” architecture. Furthermore, it divides some functions by the language of C++ Builder. This work aims to produce a low cost and high efficient control system which has good expansibility and transplantation.

The Control Research of Neural Network on Barrel Temperature of the Plastic Injection-Molding Machine

The temperaturel contror of injection molding machine barrel was acted as the research object in this paper, by combining artificial neural network with SPIDNN ,we created the basic structure and algorithm models of neural network on the injection molding machine barrel temperature control. Using of Matlab, control of the neural network on barrel temperature was simulated, the quite satisfactory control effect had obtained. The results show that the control strategy proposed can effectively improve the injection molding machine barrel temperature control accuracy, there is important reference value for temperature control of injection molding machine barrel.