Useful Process Data from the Injection Molding Machine · PDF filelyze the injection molding process, ... Useful Process Data from the Injection Molding Machine ... plastic melt (pressure,

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I N J EC T I ON MOLD ING

FELIX HEINZLER ET AL.

The production of high-quality injec-tion moldings demands precisemonitoring of the production

process. It is not unusual for an initially

stable process to become unbalanced dueto external factors – and bad parts are pro-duced. Changes in input conditions alsonecessitate adjustments to the process set-tings.

The machine operator has a wide va-riety of parameters at his disposal withwhich he can monitor the injection mold-ing process. Chart plotters and trendcurves visualize changes and allow the

production history to be viewed. But inorder to be able to comprehensively ana-lyze the injection molding process, toolsare required which allow a deeper insightinto the process.

KraussMaffei Technologies GmbH,Munich, Germany, is working actively onthis topic and cooperates here with re-search institutes such as the Faculty forEngineering Design and Plastics Machin-

© Carl Hanser Verlag, Munich Kunststoffe international 2/2014

Useful Process Data from the Injection

Molding MachineMaterial 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.

The wide variety of demands during injectionmolding requires a detailed process charac-

terization and precise process control

Translated from Kunststoffe 2/2014, pp. 52–56Article as PDF-File at www.kunststoffe-international.com; Document Number: PE111601

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Kunststoffe international 2/2014 www.kunststoffe-international.com

ery at the Institute for Product Engineer-ing (IPE) of the University of Duisburg-Essen, Germany, in order to further de-velop the state of the art. Within theframework of this cooperation, for ex-ample, new approaches to injectionmolding-specific process control are de-veloped and tested in practice. Examplesof this are the inline detection of theresidual moisture in hydrophilic plasticsamong the engineering thermoplasticsand a general monitoring of the meltstate in order to boost the process andproduct quality.

Indicators Describe theInjection Molding Process

Process parameters such as forces at thescrew shaft,mold cavity pressure, temper-atures, screw position or injection speedcan be easily visualized using chart plot-ters. Indicators derived from these, suchas maximum melt or mold cavity pres-sure, plasticizing time or mean cylinderand mold temperatures are recalculatedfor each injection molding cycles and dis-played (Fig. 1). In this way, even creepingchanges can be detected from the obser-vation of the historical development ofthe different parameters. The mold cavi-ty pressure, in particular, is a parameterfrequently used for improving the processcontrol and automated, model-basedquality control [1–3].

The increasing integration of the sen-sors installed in injection molding pro-duction cells allows vast amounts ofmeasurement data to be recorded that canbe analyzed with respect to the process.Standard machines, for example, have adata link to the frequency converters of

the drives, to the charge amplifiers of tem-perature and mold cavity pressure sen-sors or even to electronic water supplysystems. Torque and pressure curves, butalso flow rates and flow temperatures, canthus be continuously recorded and cor-related with the process and productquality [4]. In order to be able to identi-fy the right indicators for the various de-mands in the production environment,KraussMaffei and the Institute for Prod-uct Engineering have carried out exten-sive series of trials with different molds,raw materials and machines.

A parameter combination as a controlvariable which signals a very wide varietyof effects on the machine is the melt state[5]. This describes the “quality” of theplastic melt (pressure, temperature, vis-cosity) under the prevailing conditions.The information is collected during theprocess phases injection and plasticizing

and is made representable and evaluablei.a. by indicators such as a viscosity index.The viscosity index is formed by integra-tion of the melt pressure over the injec-tion time, rather like a flow index. Theintegration limits have to be modified ac-cording to the closing behavior of thenon-return valve (Fig. 2).

The plasticizing phase is crucial for theprocessing and the initial melt state be-fore injection. Until now the plasticizingtime has been available for evaluation ofthe plasticizing process. Indicators suchas the mean screw torque during plasti-cizing or the plasticizing energy appliedvia the screw (as the product of motortorque and screw speed) offer furtherpossibilities for gaining detailed informa-tion about the process. Initial trials showthat the flow properties during the injec-tion phase can already be influenced here(Fig. 2).

Fig. 1. In the con-trol system of in-jection moldingmachines (hereMC6, Krauss-Maffei) the trendand current val-ues for processparameters canbe visualized onchart plottersand trend curves

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100 min-1Plasticating speed: 175 min-1 250 min-16 g/10 minMFI: 11 g/10 min 19 g/10 min

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

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Effects of Raw Material Changesduring the Injection Phase

The dynamic injection phase is very wellsuited to deriving indicators which de-scribe the quality of the metered raw ma-terial. If we assume constant conditionsin the mold, then the effects of changes inthe raw material can be measured veryeasily. A proven method of monitoring isthe calculation of a flow index as a pres-sure integral over a defined section of thescrew stroke [4]. The influence of the vis-cosity on the process parameters duringthe injection phase can be seen from thisexample of three polypropylene gradeswith different viscosities (Fig. 3).

Changes in the raw material (charge orcolor changes), however, often also leadto changes in the closing behavior of thenon-return valve, so that the injectionpressure curve is shifted parallel to andalong the screw stroke [6]. A flow indexformed over a fixed distance would inter-pret this effect as a change in the flow-ability of the raw material. The effect ofchanges in viscosity on the part weightcan be very well illustrated in the trial withone raw material and different admixedcolor pigments (Fig. 4).

Demands on Moldings withHigh Surface Quality

If the ambient conditions or the proper-ties of the raw material change duringproduction, the molding quality changesat the same time (with identical machinesettings) [7]. For example, the moldingsare over-filled or under-filled, or warpageor surface flaws occur. When evaluatingthe indicators, the whole system of ma-

chine, mold and cooling system has to beconsidered. A large number of effects canbe explained by the combination of dif-ferent indicators across the differentprocess phases.A change in the mold tem-perature, for example,has a significant in-fluence on the indicators for the injectionphase, but not on the indicators for theplasticizing phase. On the other hand, ex-ternal factors resulting from the drying ofthe raw material, for example, have an im-pact on both the plasticizing phase andthe injection phase.

In the field of visible parts and partswhich are subsequently finished by paint-ing or galvanizing, surface properties areplaying an increasingly significant role.For these parts with their generally com-plex demands, a constant part weight orconstant part dimensions can no longer

be taken as the sole quality criterion, sothat 100 % visual inspections are fre-quently necessary.

Even minimal changes in the residualmoisture content of the raw materialchange the processing properties of thematerial and can then be seen on thehigh-gloss surfaces, for example as mois-ture streaks. With engineering plasticssuch as polybutylene terephthalate (PBT)or polyamide (PA), we have effects fromthe processing time in addition to theconditioning and drying which have aninfluence on the processing behavior andthe part quality [8, 9].

Of course the manufacturer’s specifi-cations have to be observed with regardto the processing time and maximumresidual moisture content; these areapprox. <10 min dwell time in the plas-

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white golden blue green brown yellow orange red

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NmMolding weightPlastication torqueChangeover melt pressure

Fig. 4. In most cases the switch from the injection phase to the holding pressure phase is position-dependent. The admixture of a masterbatch changes the flow properties of the starting material. Asa result, the mean torque during plastication and the pressure level at the time of the changeover aredecreased

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PP 1 PP 2 PP 3 sPP 1 PP 2 PP 3 s

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 closingbehavior of the non-return valve. The temperature curve (left) and melt pressure curve (right), measured using a temperature sensor in the mold cavitywall and a force sensor behind the screw show the influences on the process

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ticating unit and <0.02 to 0.04 % resid-ual moisture content, e.g. for PBT. Ran-dom sample testing of a raw material dur-ing production, however, would involvea large number of measurements in thelaboratory. But not even these checkswould permit a continuous evaluation ofthe raw material state and of the partquality. As a rule, nominal drying timesare specified for the hydrophilic raw ma-terials. If different numbers of produc-tion lines now draw material from a cen-tral drying unit at different rates due tobreak and standstill times, the materialstate is undefined – and process and qual-ity fluctuations occur.

Detection of Residual MoistureInfluences

In order to identify creeping fluctuations,a detection model for material changesduring the running production processwas developed. Here the required plasti-cizing energy and the mean motor torqueduring a constant phase of plasticationare referenced and assigned to the processchanges in the event of deviations.

In the example presented below, selec-tively conditioned material with differentresidual moisture contents was chargedinto the process. During the plasticationphase, there is a large and prolonged con-tact with the material via the screw andthe necessary drive with a direct relation-ship to the flow properties. A clear rela-tionship can indeed be clearly seen be-tween the torques for the differently con-ditioned material and the residual mois-ture content (Fig. 5).

The physical effects of the trappedresidual moisture reduce the viscosity in

the process, so that the torque requiredfor plastication drops. A characteristicmean plastication torque (without start-ing and braking torques) can be directlyassigned to the residual moisture levels.The high resolution over time allows aclear distinction to be made between themean torques required and a representa-tion of the screw rotation. The energy in-put into the plastication process via thescrew torque highlights this relationship,while the energy input by the heating sys-tem shows no significant relationshipwith respect to the material change (Fig. 6).

The reference plastication energy andthe characteristic mean torque thus allowa clear statement to be made about thematerial properties. For correspondinglyreferenced processes, a 100 % check can

thus be installed even for minimal, butquality-determining effects of residualmoisture fluctuations or other influenceson the material properties. A particularadvantage here is that the plastics proces-sor does not have to install any addition-al sensors in the system, but can merelymake use of the information alreadyavailable.

Conclusion

The demands on the quality of injectionmoldings must be monitored using in-telligent solutions for process control inorder to be able to meet cost targets inthe injection molding production. Withthe corresponding know-how, the possi-bilities available for monitoring and vi-


Kunststoffe international 2/2014 www.kunststoffe-international.com

Plastication time

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Fig. 5. The plastication torque at the screw drive can be directly allocated to the residual moisturelevels. The higher the residual moisture content in the material, the lower the flow resistance

© Kunststoffe

Cycle

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35025 50 75 100 125 150 175 200 225 250 275 300 325

Residual moisture content < 0.03 % Residual moisture content 0.1 % Residual moisture content 0.12 %Fig. 6. The resulting energylevel during plasticationshows a significant rela-tionship to the change inthe material conditioninglevels (cycle 100 and 240)in an exemplary processwith Polyamide 6. The re-quired drive energy showsduring plastication, in linewith the residual moisturelevels, that a detection atthe limits of the process-ing range with a largedatabase can be very pre-cisely implemented

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sualizing process data can be used forquality control and process optimization.Due to the wide variety of quality de-mands, there will be no general panaceafor compensating external influences inthe near future, but the latest approach-es offer flexible possibilities for referenc-ing the process and the specific require-ments.

A selective inline detection of distur-bances in the process is already possibletoday to support quality control. The der-ivation of expedient control strategies andthe implementation of intelligent controlconcepts will significantly boost the qual-ity of processes and products. The chal-lenge of the future will continue to be theneed to make ever larger volumes of in-formation useful to the machine opera-tor – one approach here is to integratecorresponding assistance functions intothe machine control system.

ACKNOWLEDGMENTLanxess Deutschland GmbH, Leverkusen, andmouldtec Kunststoff GmbH, Kaufbeuren, both Ger-many, supported this project with material and masterbatch.

REFERENCES1. Gruber, J.: Prozessführung beim Thermoplast-

spritzgiessen auf Basis des Werkzeuginnendrucks.Dissertation, RWTH Aachen 2005.

2. Michaeli, W.; Schreiber, A.; Lettowski, C.: Opti-mierung der Prozessführung beim Thermoplast-spritzgießen durch Online-Regelung auf Basis vonProzessgrößen. Kunststofftechnik, 04 (2008), pp. 1–17.

3. Mustafa, M. A.: Modellbasierte Ansätze zur Qual-itätsregelung beim Kunststoffspritzgießen. Disser-tation, University of Essen 2000-

4. Schiffers, R.: Verbesserung der Prozessfähigkeitbeim Spritzgießen durch Nutzung von Prozessdat-en und eine neuartige Schneckenhubführung. Dis-sertation, University of Duisburg-Essen 2009.

5. Cavic, A.: Kontinuierliche Prozessüberwachungbeim Spritzgiessen unter Einbeziehung vonKonzepten zur Verbesserung der Schmelzequalität.Dissertation, University of Stuttgart 2005.

6. Kazmer, D. O.; Velusamy, S.; Westerdale, S.; John-ston, S.; Gao, R. X.: A comparison of seven fillingto packing switchover methods for injection mold-ing. Polymer Engineering and Science, 50 (2010),pp. 2,031–2,043.

7. Boss, M.; Wodke, T.: Capillary Rheometry Opti-mizes Injection Molding. Kunststoffe international97 (2007) 11, pp. 87–89.

8. Pongratz, S.: Alterung von Kunststoffen währendder Verarbeitung und im Gebrauch. Dissertation,University of Erlangen-Nuremberg 2000.

9. Ehrenstein, G.; Pongratz, S.: Beständigkeit vonKunststoffen. Carl Hanser Verlag, Munich 2007.

THE AUTHORSFELIX A. HEINZLER, born in 1984, has been re-

search associate since 2010 and since 2012 GroupLeader Injection Molding at the Institute for ProductEngineering (IPE) of the University of Duisburg-Essen,Germany; [email protected]

M.SC. STEFAN KRUPPA, born in 1983, has beendevelopment engineer in the Machine Technologyand Test division of KraussMaffei TechnologiesGmbH, Munich, Germany, since 2010.

DR.-ING. REINHARD SCHIFFERS, born in 1977, hasbeen Head of the Machine Technology and Test divi-sion of KraussMaffei Technologies since 2012.

PROF. DR.-ING. JOHANNES WORTBERG, born in1951, has held the Chair of the Faculty for Engineer-ing Design and Plastics Machinery at the Institute forProduct Engineering since 2001.

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Useful Process Data from the Injection Molding Machine · PDF filelyze the injection molding process, ... Useful Process Data from the Injection Molding Machine ... plastic melt (pressure,