Search Results (6)

The simultaneous improvement of injection molding process efficiency and product quality, as required by Industry 4.0, is a complex, non-trivial task that requires a comprehensive approach, which involves a combination of sensoring and information techniques. In this study, we investigated the suitability of in-mold pressure sensors to control the injection molding process in multi-cavity molds. We have conducted several experiments to show how to optimize the clamping force, switchover, or holding time by measuring only pressure in a multi-cavity mold. The results show that the pressure curves and the pressure integral are suitable for determining optimal clamping force. We also proved that in-channel sensors could be effectively used for a pressure-controlled SWOP. In the volume-controlled method, only the sensors in the cavity were capable of correctly detecting the end of the filling. We proposed a method to optimize the holding phase. In this method, we first determined the integration time of the area under the pressure curve and then performed a model fit using the relationship between the pressure integral and product mass. The saturation curve fitted to the pressure data can easily determine the gate freeze-off time from pressure measurements. Full article

Material as well as process variations in the composites industry are reasons to develop methods for in-line monitoring, which would increase reproducibility of the manufacturing process and the final composite products. Fiber Bragg Gratings (FBGs) have shown to be useful for monitoring liquid-composite molding processes, e.g., in terms of online gel point detection. Existing works however, focus on in-plane strain measurements while out-of-plane residual strain prevails. In order to measure out-of-plane strain, FBG inscribed in highly birefringent fiber (HB FBG) can be used. The purpose of this research is the cure stage detection with (a) FBG inscribed in single mode and (b) FBG inscribed in highly-birefringent side-hole fiber in comparison to the reference gel point detected with an in-mold DC sensor. Results reveal that the curing process is better traceable with HB FBG than with regular FBG. Thus, the use of HB FBG can be a good method for the gel point estimation in the RTM process. Full article

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. Full article

In compression molding using glass-fiber-mat-reinforced thermoplastic (GMT) sheets, a slightly longer compression waiting time from sheet placement on a lower mold to the start of sheet compression by an upper mold can cause incomplete filling due to a decrease in the sheet temperature. However, precise measurement techniques for compression waiting time have not been sufficiently established. A monitoring system was produced that includes pressure—temperature sensors mounted in a compression mold that can simultaneously measure the pressure and temperature of one local surface. Two types of distance sensors were also used to measure upper mold motion widely and precisely. Determination of compression waiting time was attempted by measuring the moment when the lower mold temperature slightly increases in response to contact with the melted GMT sheet and the moment when the melt pressure increases in response to compression by an upper mold. The results showed that compression waiting time could be precisely calculated using the profile data obtained. Moreover, it was also possible to observe the melt pressure overshoot that occurs depending on sheet stacking patterns and mold cavity shape, although in some cases, the overshoot was not observed. In conclusion, this study has demonstrated that the system is effective in monitoring the compression molding process widely and precisely. Full article

The recent trend in plastic production dictated by Industry 4.0 demands is to acquire a great deal of data for manufacturing process control. The most relevant data about the technological process itself come from the mold cavity where the plastic part is formed. Manufacturing process data in the mold cavity can be obtained with the help of sensors. Although many sensors are available nowadays, those appropriate for in-mold measurements have certain peculiarities. This study presents a comprehensive overview of in-mold process monitoring tools and methods for injection molding process control. It aims to survey the recent development of standard sensors used in the industry for the measurement of in-mold process parameters, as well as research attempts to develop unique solutions for solving certain research and industrial problems of injection molding process monitoring. This review covers the established process monitoring techniques—direct temperature and pressure measurement with standard sensors and with the newly developed sensors, as well as techniques for the measurement of indirect process parameters, such as viscosity, warpage or shrinkage. Full article

This work is aimed to present an innovative technology for the reinforcement of beams for urban furniture, produced by in-mold extrusion of plastics from solid urban waste. This material, which is usually referred to as “recycled plastic lumber”, is characterized by very poor mechanical properties, which results in high deflections under flexural loads, particularly under creep conditions. The Prowaste project, founded by the EACI (European Agency for Competitiveness and Innovation) in the framework of the Eco-Innovation measure, was finalized to develop an innovative technology for selective reinforcement of recycled plastic lumber. Selective reinforcement was carried out by the addition of pultruded glass rods in specific positions with respect to the cross section of the beam, which allowed optimizing the reinforcing efficiency. The reinforcement of the plastic lumber beams with pultruded rods was tested at industrial scale plant, at Solteco SL (Alfaro, Spain). The beams obtained, characterized by low cost and weight, were commercialized by the Spanish company. The present paper presents the most relevant results of the Prowaste project. Initially, an evaluation of the different materials candidates for the reinforcement of recycled plastic lumber is presented. Plastic lumber beams produced in the industrial plant were characterized in terms of flexural properties. The results obtained are interpreted by means of beam theory, which allows for extrapolation of the characteristic features of beams produced by different reinforcing elements. Finally, a theoretical comparison with other approaches which can be used for the reinforcement of plastic lumber is presented, highlighting that, among others, the Prowaste concept maximizes the stiffening efficiency, allowing to significantly reduce the weight of the components. Full article