T he production of high-quality injection. Useful Process Data from the Injection Molding Machine

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1 The wide variety of demands during injection molding requires a detailed process characterization and precise process control Useful Process Data from the Injection Molding Machine Material Characterization. Hand-in-hand, research and industry are developing new avenues for injection molding-specific process control. If the relevant process data are collected and evaluated at the injection molding machine according to the requirements, changes in the process can be detected online. At batch, color or residual moisture changes, the operator immediately receives information on fluctuations in process and quality and can intervene directly. FELIX HEINZLER ET AL. T he production of high-quality injection moldings demands precise monitoring of the production process. It is not unusual for an initially Translated from Kunststoffe 2/214, pp Article as PDF-File at Document Number: PE11161 stable process to become unbalanced due to external factors and bad parts are produced. Changes in input conditions also necessitate adjustments to the process settings. The machine operator has a wide variety of parameters at his disposal with which he can monitor the injection molding process. Chart plotters and trend curves visualize changes and allow the production history to be viewed. But in order to be able to comprehensively analyze the injection molding process, tools are required which allow a deeper insight into the process. KraussMaffei Technologies GmbH, Munich, Germany, is working actively on this topic and cooperates here with research institutes such as the Faculty for Engineering Design and Plastics Machin- 42 Carl Hanser Verlag, Munich Kunststoffe international 2/214

2 ery at the Institute for Product Engineering (IPE) of the University of Duisburg- Essen, Germany, in order to further develop the state of the art. Within the framework of this cooperation, for example, new approaches to injection molding-specific process control are developed and tested in practice. Examples of this are the inline detection of the residual moisture in hydrophilic plastics among the engineering thermoplastics and a general monitoring of the melt state in order to boost the process and product quality. Indicators Describe the Injection Molding Process Fig. 1. In the control system of injection molding machines (here MC6, Krauss- Maffei) the trend and current values for process parameters can be visualized on chart plotters and trend curves Process parameters such as forces at the screw shaft, mold cavity pressure, temperatures, screw position or injection speed can be easily visualized using chart plotters. Indicators derived from these, such as maximum melt or mold cavity pressure, plasticizing time or mean cylinder and mold temperatures are recalculated for each injection molding cycles and displayed (Fig. 1). In this way, even creeping changes can be detected from the observation of the historical development of the different parameters. The mold cavity pressure, in particular, is a parameter frequently used for improving the process control and automated, model-based quality control [1 3]. The increasing integration of the sensors installed in injection molding production cells allows vast amounts of measurement data to be recorded that can be analyzed with respect to the process. Standard machines, for example, have a data link to the frequency converters of the drives, to the charge amplifiers of temperature and mold cavity pressure sensors or even to electronic water supply systems. Torque and pressure curves, but also flow rates and flow temperatures, can thus be continuously recorded and correlated with the process and product quality [4]. In order to be able to identify the right indicators for the various demands in the production environment, KraussMaffei and the Institute for Product Engineering have carried out extensive series of trials with different molds, raw materials and machines. A parameter combination as a control variable which signals a very wide variety of effects on the machine is the melt state [5]. This describes the quality of the plastic melt (pressure, temperature, viscosity) under the prevailing conditions. The information is collected during the process phases injection and plasticizing and is made representable and evaluable i.a. by indicators such as a viscosity index. The viscosity index is formed by integration of the melt pressure over the injection time, rather like a flow index. The integration limits have to be modified according to the closing behavior of the non-return valve (Fig. 2). The plasticizing phase is crucial for the processing and the initial melt state before injection. Until now the plasticizing time has been available for evaluation of the plasticizing process. Indicators such as the mean screw torque during plasticizing or the plasticizing energy applied via the screw (as the product of motor torque and screw speed) offer further possibilities for gaining detailed information about the process. Initial trials show that the flow properties during the injection phase can already be influenced here (Fig. 2). > Viscosity index 32 Pa s MFI: 6g/1min 11 g/1 min 19 g/1 min Viscosity index 26 Pa s 24 Plasticating speed: 1 min min -1 min Dwell time s Back pressure 1 Fig. 2. The indicator used for a material comparison (Sabic PP 571, 575, 576) is the viscosity index during injection. Parameters such as back pressure, plasticating speed or dwell time have little influence on the material used. A change in the MFI in the otherwise identical material, on the other hand, can be clearly identified Kunststoffe international 2/

3 85 PP 1 PP 2 PP 3 s 35 4 PP 1 PP 2 PP 3 s 35 Mold wall temperature C mm Screw position Melt pressure mm Screw position s 2.3 Time s 2.7 Time Fig. 3. The example of the three tested polypropylene grades with different MFI shows the influence on the flow behavior in the cavity and on the closing behavior of the non-return valve. The temperature curve (left) and melt pressure curve (right), measured using a temperature sensor in the mold cavity wall and a force sensor behind the screw show the influences on the process Effects of Raw Material Changes during the Injection Phase The dynamic injection phase is very well suited to deriving indicators which describe the quality of the metered raw material. If we assume constant conditions in the mold, then the effects of changes in the raw material can be measured very easily. A proven method of monitoring is the calculation of a flow index as a pressure integral over a defined section of the screw stroke [4]. The influence of the viscosity on the process parameters during the injection phase can be seen from this example of three polypropylene grades with different viscosities (Fig. 3). Changes in the raw material (charge or color changes), however, often also lead to changes in the closing behavior of the non-return valve, so that the injection pressure curve is shifted parallel to and along the screw stroke [6]. A flow index formed over a fixed distance would interpret this effect as a change in the flowability of the raw material. The effect of changes in viscosity on the part weight can be very well illustrated in the trial with one raw material and different admixed color pigments (Fig. 4). Demands on Moldings with High Surface Quality Mean torque during plastication Changeover melt pressure Sabic PP 575 If the ambient conditions or the properties of the raw material change during production, the molding quality changes at the same time (with identical machine settings) [7]. For example, the moldings are over-filled or under-filled, or warpage or surface flaws occur. When evaluating the indicators, the whole system of machine, mold and cooling system has to be considered. A large number of effects can be explained by the combination of different indicators across the different process phases.a change in the mold temperature, for example, has a significant influence on the indicators for the injection phase, but not on the indicators for the plasticizing phase. On the other hand, external factors resulting from the drying of the raw material, for example, have an impact on both the plasticizing phase and the injection phase. In the field of visible parts and parts which are subsequently finished by painting or galvanizing, surface properties are playing an increasingly significant role. For these parts with their generally complex demands, a constant part weight or constant part dimensions can no longer Molding weight Plastication torque Changeover melt pressure white golden blue green brown yellow orange red 7.65 g 7.6 Fig. 4. In most cases the switch from the injection phase to the holding pressure phase is positiondependent. The admixture of a masterbatch changes the flow properties of the starting material. As a result, the mean torque during plastication and the pressure level at the time of the changeover are decreased Molding weight be taken as the sole quality criterion, so that 1 % visual inspections are frequently necessary. Even minimal changes in the residual moisture content of the raw material change the processing properties of the material and can then be seen on the high-gloss surfaces, for example as moisture streaks. With engineering plastics such as polybutylene terephthalate (PBT) or polyamide (PA), we have effects from the processing time in addition to the conditioning and drying which have an influence on the processing behavior and the part quality [8, 9]. Of course the manufacturer s specifications have to be observed with regard to the processing time and maximum residual moisture content; these are approx. <1 min dwell time in the plas- 44 Carl Hanser Verlag, Munich Kunststoffe international 2/214

4 ticating unit and <.2 to.4 % residual moisture content, e. g. for PBT. Random sample testing of a raw material during production, however, would involve a large number of measurements in the laboratory. But not even these checks would permit a continuous evaluation of the raw material state and of the part quality. As a rule, nominal drying times are specified for the hydrophilic raw materials. If different numbers of production lines now draw material from a central drying unit at different rates due to break and standstill times, the material state is undefined and process and quality fluctuations occur. Detection of Residual Moisture Influences In order to identify creeping fluctuations, a detection model for material changes during the running production process was developed. Here the required plasticizing energy and the mean motor torque during a constant phase of plastication are referenced and assigned to the process changes in the event of deviations. In the example presented below, selectively conditioned material with different residual moisture contents was charged into the process. During the plastication phase, there is a large and prolonged contact with the material via the screw and the necessary drive with a direct relationship to the flow properties. A clear relationship can indeed be clearly seen between the torques for the differently conditioned material and the residual moisture content (Fig. 5). The physical effects of the trapped residual moisture reduce the viscosity in Torque Torque Residual moisture.1 % Residual moisture.2 % Residual moisture.3 % s 1.6 Plastication time the process, so that the torque required for plastication drops. A characteristic mean plastication torque (without starting and braking torques) can be directly assigned to the residual moisture levels. The high resolution over time allows a clear distinction to be made between the mean torques required and a representation of the screw rotation. The energy input into the plastication process via the screw torque highlights this relationship, while the energy input by the heating system shows no significant relationship with respect to the material change (Fig. 6). The reference plastication energy and the characteristic mean torque thus allow a clear statement to be made about the material properties. For correspondingly referenced processes, a 1 % check can s 1.4 Plastication time Fig. 5. The plastication torque at the screw drive can be directly allocated to the residual moisture levels. The higher the residual moisture content in the material, the lower the flow resistance thus be installed even for minimal, but quality-determining effects of residual moisture fluctuations or other influences on the material properties. A particular advantage here is that the plastics processor does not have to install any additional sensors in the system, but can merely make use of the information already available. Conclusion The demands on the quality of injection moldings must be monitored using intelligent solutions for process control in order to be able to meet cost targets in the injection molding production. With the corresponding know-how, the possibilities available for monitoring and vi- > Plastication energy 5. kws Residual moisture content <.3 % Residual moisture content.1 % Residual moisture content.12 % Cycle 35 Fig. 6. The resulting energy level during plastication shows a significant relationship to the change in the material conditioning levels (cycle 1 and 24) in an exemplary process with Polyamide 6. The required drive energy shows during plastication, in line with the residual moisture levels, that a detection at the limits of the processing range with a large database can be very precisely implemented Kunststoffe international 2/

5 sualizing process data can be used for quality control and process optimization. Due to the wide variety of quality demands, there will be no general panacea for compensating external influences in the near future, but the latest approaches offer flexible possibilities for referencing the process and the specific requirements. A selective inline detection of disturbances in the process is already possible today to support quality control. The derivation of expedient control strategies and the implementation of intelligent control concepts will significantly boost the quality of processes and products. The challenge of the future will continue to be the need to make ever larger volumes of information useful to the machine operator one approach here is to integrate corresponding assistance functions into the machine control system. ACKNOWLEDGMENT Lanxess Deutschland GmbH, Leverkusen, and mouldtec Kunststoff GmbH, Kaufbeuren, both Germany, supported this project with material and masterbatch. REFERENCES 1. Gruber, J.: Prozessführung beim Thermoplastspritzgiessen auf Basis des Werkzeuginnendrucks. Dissertation, RWTH Aachen. 2. Michaeli, W.; Schreiber, A.; Lettowski, C.: Optimierung der Prozessführung beim Thermoplastspritzgießen durch Online-Regelung auf Basis von Prozessgrößen. Kunststofftechnik, 4 (28), pp Mustafa, M. A.: Modellbasierte Ansätze zur Qualitätsregelung beim Kunststoffspritzgießen. Dissertation, University of Essen 2-4. Schiffers, R.: Verbesserung der Prozessfähigkeit beim Spritzgießen durch Nutzung von Prozessdaten und eine neuartige Schneckenhubführung. Dissertation, University of Duisburg-Essen Cavic, A.: Kontinuierliche Prozessüberwachung beim Spritzgiessen unter Einbeziehung von Konzepten zur Verbesserung der Schmelzequalität. Dissertation, University of Stuttgart. 6. Kazmer, D. O.; Velusamy, S.; Westerdale, S.; Johnston, S.; Gao, R. X.: A comparison of seven filling to packing switchover methods for injection molding. Polymer Engineering and Science, 5 (21), pp. 2,31 2, Boss, M.; Wodke, T.: Capillary Rheometry Optimizes Injection Molding. Kunststoffe international 97 (27) 11, pp Pongratz, S.: Alterung von Kunststoffen während der Verarbeitung und im Gebrauch. Dissertation, University of Erlangen-Nuremberg Ehrenstein, G.; Pongratz, S.: Beständigkeit von Kunststoffen. Carl Hanser Verlag, Munich 27. THE AUTHORS FELIX A. HEINZLER, born in 1984, has been research associate since 21 and since 212 Group Leader Injection Molding at the Institute for Product Engineering (IPE) of the University of Duisburg-Essen, Germany; felix.heinzler@uni-due.de M.SC. STEFAN KRUPPA, born in 1983, has been development engineer in the Machine Technology and Test division of KraussMaffei Technologies GmbH, Munich, Germany, since 21. DR.-ING. REINHARD SCHIFFERS, born in 1977, has been Head of the Machine Technology and Test division of KraussMaffei Technologies since 212. PROF. DR.-ING. JOHANNES WORTBERG, born in 1951, has held the Chair of the Faculty for Engineering Design and Plastics Machinery at the Institute for Product Engineering since Carl Hanser Verlag, Munich Kunststoffe international 2/214