injection moulding -quality molded parts

The Injection Molding of Quality Molded Parts

ATI 1146e Increasing Productivity through Process Optimization

Plastics Business Group

2

Increasing Productivity through Process Optimization

Contents Page

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Quality criteria and factors influencing productivity . . . . . . . . . . . . . . . . . . . . 4

Influence of the material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Influence of the molded part geometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Influence of the mold. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Influence of the injection molding machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Influence of processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Environmental influences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Optimization strategies and concepts for process optimization . . . . . . . . . . . 17

Fault diagnosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

The difference between process optimization and fault diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Fault diagnosis procedure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Fault diagnosis aids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Example of fault diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Selecting the most appropriate remedies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3


IntroductionThe injection molding process has long beenestablished as a highly cost-efficient processfor the production of high-grade, complexmolded parts. The constantly increasing de-mands placed on plastics parts in terms ofquality, deadlines and costs make it essentialfor plastics processors to adopt appropriateprocedures to analyze and optimize the pro-cessing operation and the factors that influ-ence it [1].

The development of improved, automatedquality assurance systems has brought ad-vances in process monitoring for injectionmolding machines, thanks to new open-loopand closed-loop control facilities. This hasbeen made possible through rapid advancesin microelectronics and sensor technology.Today therefore, it is feasible to achievecomprehensive (100 %) monitoring of theinjection molding process on the basis oftarget/actual comparisons. In order to keepthe amount of data involved to a manage-able level, however, it is wise to restrict thismonitoring to a number of process parame-ters that affect quality [2].

An increase in productivity can be achievedby increasing the output-to-input ratio. If itproves possible to produce a greater num-ber of units (the output) while simultane-ously lowering the cost of molded-part pro-duction (the input), then this will have ful-filled the aim of achieving as many good-quality, fault-free parts as possible whichconform with the specifications (Fig. 1).

Figure 2 shows an example of a clear in-crease in productivity. Continual improve-ments to the different segments of theprocess chain have made it possible to re-duce the cycle time for CD production frommore than 20 s at the start of the 1980s toapproximately 3 s today. The clear reduc-tion in the price of CDs since then has beendue not least to this development.

In order to achieve cost-optimized produc-tion with a high level of productivity (cost-efficient production), the next step involvesoptimizing the processing operation fromthe angle of quality and reliability. Processoptimization generally forms part of thestart-up process for a new mold.

Output Input

Number of units produced Outlay on time and material

increa

se !

reduce !

Fig. 1: Increasing productivity

Fig. 2: Example of CD production

01982 1984 1986 1988 1990 1992 1994 1996 1998 2000

5

10

15

20

25

22

3

Cycle

time

(s)

∆ t z

= 19

s

Year

Cycle time Share of material

Share of processing technology

Share of machine and mold technology

4


The aim is to produce the specified moldedpart quality within the stipulated or agreedtolerances in as cost-efficient a manner aspossible. The outlay on optimization andmonitoring must, of course, be commensu-rate with the level of the quality require-ments and, where appropriate, with thescope of the overall order and the batch sizeof the individual series that are to be sup-plied.

In addition to this, both the prevailing com-petition and the proof of quality capabilitythat customers generally require will pro-vide an added incentive to take further stepsin the direction of process optimization. Themore intense the competition, the greatercare processors must take to produce ascheaply as possible while at the same timeensuring a reputation for reliability in re-spect of quality and meeting deadlines.Proof of quality capability to DIN ISO 9000ff. is provided by an audit carried out by thecustomer or through certification by an au-thorized institute. Documentation of processcontrol and quality monitoring is essentialin all cases.

Quality criteria and factorsinfluencing productivityBefore a start can be made on process opti-mization, it is necessary to determine whichquality criteria are of relevance for theprocess and what possibilities exist for in-fluencing these. The most important mold-ed part properties in the first instance are:

● appearance- color, transparency- surface- absence of faults

● mechanical and physical properties- toughness- stiffness- strength

and

● dimensional and shape accuracy

These properties are influenced directlyor indirectly by the following parameters(Fig. 3):

● the material employed (selection, pro-cessing characteristics)

● the design of the molded part (designsuitable for plastics, optimum wall thick-nesses)

● the mold (gate design, thermal layout,mechanical characteristics)

● the machine (size, rigidity, speed, costs,selection, setting)

● the processing operation (process con-trol)

● the environment (location, peripheralunits such as a dryer, employee skills,etc.)

Fig. 3: Influences on quality and productivity

Molded part designMaterial Molds

Processing

Molded part

Machine Environment

5


In order to achieve cost-efficient produc-tion, it is necessary to take a close look ateach individual link in this process chainand then to optimize it, making due al-lowance for the interaction between the dif-ferent parameters. Figure 4 shows just howimportant it is to observe and optimize eachindividual segment at the earliest possiblestage.

The majority of faults have their origins inthe development phase, but these faults aregenerally not rectified until the parts are in-spected after production, since it is only thenthat the faults are discovered.

The correlation between the point of originof a fault and the impact of this fault is alsodescribed by the 'rule of ten'. This states, onthe one hand, that the outlay required to rec-tify a fault increases tenfold with each stepfrom the idea for the part through to its de-ployment and, on the other hand, that thepotential for influencing the production costsfalls to a level of 10 %. This shows just howimportant it is to clarify in good time the in-fluence that the individual segments of theprocess chain have on quality and produc-tivity.

These individual points will now be lookedat, taking a number of practical examples.

Fig. 4: Origin and rectification of faults [3]

0

10

20

30

40

50

60

Definition Development Operational planning

Production Inspection Deployment

Freq

uenc

y (%)

Phases in the product life cycle

Rectification of fault

Origin of fault

6


Influence of the material

The material provides the first opportunityfor increasing productivity. The potentialthat the material holds in this respect can beillustrated with two examples. Optical datamedia such as CDs and DVDs have estab-lished a market as the storage media ofchoice. The market success of these discs isdue, firstly, to the high-quality sound re-production of audio CDs and, secondly, tothe low cost of CD-ROMs as storage me-dia. This development has been accompa-nied by a steady increase in productivity inthe manufacturing process, brought aboutin no small measure by the optimization ofthe material. The example of "CD produc-tion" illustrates how the cycle time for in-jection molding has been continuously re-duced from more than 20 s at the start of the1980s to around 3 s at present, thanks to op-timization of the material.

Apart from optimization of the material, thisclear reduction in cycle time has addition-ally been achieved through optimization ofthe machine and mold, and also the pro-cessing operation itself (Fig. 2). Materialswith a broad processing window offergreater scope for adjusting the processingsettings, and the interaction of the differentparameters is readily evident here. Figure 5illustrates the broader processing windowof Makrolon® DP 1-1265 compared withMakrolon® CD 2005. Selective optimizationof the material (a 15 % improvement inflowability) has contributed towards in-creased productivity and thus towards con-siderably reduced costs.

The two-shell overmolding technique pro-vides a further example of how productivi-ty can be increased through optimization ofthe material. This process involves a numberof individual shells being produced by in-jection molding and then welded together.Figure 6 shows an air-intake manifold forthe Mercedes A-Class in Durethan® KU 2-2140/30 H2.0 (PA6 GF30). Previous air-in-take manifolds were produced by the elab-

orate fusible core technique, since the burst-ing pressures attainable in welded partsmade of standard PA6 GF30 were not highenough. Only when selective improvementswere made to the weldability of the materi-al did it become possible to join togethertwo half-shells produced by the traditionalinjection molding process using conven-tional welding methods (heated tool or vi-bration welding).

Processing window of materials for optical data media (cycle time = 3.5 s)

• Makrolon CD 2005 (standard)

• Makrolon DP 1-1265 (15 % improvement in flowability)

Melt temperature (°C)

Cooli

ng w

ater

temp

erat

ure (

°C)

Cooli

ng w

ater

temp

erat

ure (

°C)

Melt temperature (°C)

30320 330 340 350 320 330 340 350

40

50

30

40

50

Fig. 5: Material optimization – a broad processing window

Welding Extrusion

Injection molding

Non-Newtonian PA

Durethan®

KU 2-2140/30 H2.0

Standard PADurethan® BKV 30 H2.0

Visco

sity

Shear

Fig. 6: Material optimization – weldability

7


Adjusting this product to give it more pro-nounced non-Newtonian characteristics ledto a broad processing window, less flash atthe weld and a reduced tendency to adhereto the heating element during heated toolwelding [4]. The bursting pressure was in-creased by some 40 % in the course of ma-terial optimization, and it also proved pos-sible to further extend the processing win-dow in response to frequent requests fromwelding engineers. In addition, it was onlyby virtue of this optimization that produc-tion by the two-shell overmolding techniquewas possible at all. Further success factorsincluded improved potential for rheologicaland mechanical computation.

Influence of the molded partgeometry

The design of the molded part marks a fur-ther link in the overall process chain. Para-meters such as wall thickness, rib-to-wall-thickness ratio, positioning of ribs, bossesand perforations, surface requirements andpermitted tolerances play a part in deter-mining the requisite component quality andhence the productivity. Figure 7 shows anexample of how productivity can be clearlyincreased through the selective optimizationof wall thickness.

In its original wall thickness of 4 mm, thelawnmower chassis shown below weighed1.83 kg and required a cycle time of 95 s.

The target set by the customer for achiev-ing more economical production was a wallthickness of between 3.0 and 3.5 mm andhence a weight of approximately 1.6 kg. Thecycle time was not to exceed 80 s. Workingon the basis of rheological and mechanicalcalculations, a design suitably tailored to thestress pattern was established, which not on-ly permitted the target to be attained but al-so led to further improvements. The opti-mized wall thickness was ultimately 2.5 –3 mm, bringing the weight down to only1.45 kg, while the cycle time was reducedto 65 – 70 s. The additional 10 % reductionin weight thus produced significant materi-al savings, and the reduction in cycle timeled to a further increase in productivity.

Lawnmower Weight Wall thickness Cycle timechassis: kg mm s

Current model 1.83 4.00 95

Successor model

Customer target: 1.6 3.0–3.5 80

Result after 1.45 2.5–3.0 65–70optimization: -10 %

Fig. 7: Molded part design – optimization of the wall thickness

8


Influence of the mold

The quality of the mold, together with itstemperature control, ventilation, number ofgates, gate design, type of hot runner andmold rigidity are just a few of the key factorsthat influence productivity. Uniform tem-perature control, for example, will permitboth an improvement in part properties anda reduction in cycle time, and the level ofinherent stress due to uneven cooling willalso be reduced. One means of achievingconformal cooling is to employ the CONTURA® heating/cooling system patent-ed by Innova Engineering GmbH (Fig. 8).This involves cooling channels being con-figured to match the geometry of the mold-ed part with the aid of the vacuum solder-ing technique.

Figure 9 shows the potential that this sys-tem offers for cooling a door liner. The toppicture shows the temperature distributionwith conventional cooling while the bottompicture shows this same door liner in a moldequipped with the Contura system. It is clearthat the temperature distribution is consid-erably more uniform and the temperaturelevel considerably lower with Contura. Thistechnology permits both a significant re-duction in cooling time and an improvementin part quality. As a general rule, the sav-ings potential for improved mold coolingworks out at between 10 and 40 %, de-pending on the part in question.

Fig. 8: The CONTURA® temperature control system

Fig. 9: Mold optimization –cooling

Door liner with conventional cooling

Door liner with Contura

9


A further element of the mold that has a pro-nounced influence on the quality of themolded part and the amount of waste, andwhich thus also affects the cost-efficiencyof the production process, is the gate withthe sprue. The gate must be large enough toavoid excessive shear acting on the melt andprevent the melt temperature from rising toa critical level. The gate should also notplace any restrictions on the processing win-dow – in other words, it must be possiblefor the holding pressure to be applied for asufficiently long period.

At the same time, cost-efficient productionmeans that the gate must not dictate the cy-cle time, that sprue waste must be kept to aminimum and that the sprue should be cutoff automatically if possible.

The design of the gate is one of the factorsthat contribute towards trouble-free pro-duction. One problem that frequently occurswith direct pin-point gating on high-glosssurfaces is the "matte circle". This is causedby excessive shear and too great an increasein temperature during the injection phase.The thin layer of melt that has already so-lidified close to the gate is torn apart againby the hot melt flowing in afterwards, andthe surface takes on a matte appearance. Theremedy here can be to adopt a graded injec-tion profile (slow –> fast). Figure 10 showsa system that can be used to achieve gradedinjection in a natural manner while keepingthe screw advance speed on a constant set-ting.

Fig. 10: Gate system for graded injection


The transverse bar fitted just upstream ofthe gate causes the melt flow to divide intothree part-flows at the start of the injectionphase. This then reduces the speed at thegate. Once the transverse bar has been com-pletely filled, the compound continues toflow at the higher injection speed set on themachine. The lower speed of the melt at thestart of the injection phase serves to reducethe shear and the temperature increase, andthe thicker layer of melt then freezes on themold wall and can no longer be torn apartby the melt flowing in afterwards. A flaw-less, glossy surface results.

To ensure that complex cavities can be uni-formly filled via a number of different gates,it is important for a rheological calculationto be performed at the mold design stage.This will enable errors and problems to bepinpointed right at the planning stage, andpermit the gates to be optimally designed

and positioned (Fig. 11). The outlay on sub-sequent alterations to the mold will be keptto a minimum, series production can com-mence sooner, and component propertieswill be improved and the cycle time reduced.

10

Fig. 11: Rheological layout of the mold

11


Influence of the injection moldingmachine

The injection molding machine must be ad-equately dimensioned for the requirements.The chief selection criteria are:

● clamping force

● metering volume

● permitted mold size

Apart from these fundamental selection cri-teria, the following factors play a key rolein ensuring cost-efficient production:

● machine rigidity

● the type of open-loop or closed-loop con-trol

● the reproducibility of all the machinemovements

● machine costs (purchase cost and oper-ating costs)

Apart from this, it is also important to se-lect the appropriate screw with regard to themelting behavior and the residence time,since the melt compounding has a direct in-fluence on the quality of the molded part.The screw size should be selected such thatthe metering stroke is between a minimumof 1D and a maximum of 4D. The best rangefor achieving optimum melting is between1D and 3D (Fig. 12).

If the metering stroke is below this range(<1D), the residence time will rise to inad-missibly high levels and there will be a con-siderably increased danger of silver streaksdue to decomposition. The reproducibilityof the production process will also suffer onaccount of the short screw displacement. If

the metering stroke is above this range(>3D), then there is a danger that air will beintroduced together with the molding com-pound, which will once again lead to streakson the surface of the molded part. The opti-mum screw diameter for a specific part weightcan be estimated with the aid of Fig. 13.

Screw

1 D 2 D 3 D 4 D

< 1 D > 4 D

1D to 3D optimum range3D to 4D possible in exceptional cases<1 D and >4D not recommended

Fig. 12: Optimum metering displacement [6]

Fig. 13: Optimum screw size

Screw diameter

Meter

ing vo

lume c

m3

10 20 40 60 801

10

100

1,000

10,000

100 200 mm

Optimum range

12


Influence of processing

Once all the requirements have been ful-filled in respect of the optimum material,the molded part design, the mold and ma-chine, this still leaves the processing opera-tion to be optimized in a bid to ensure cost-efficient production. The first step here is toestablish which process parameters have abearing on quality. The processing parame-ters with the greatest influence on the prop-erties of the molded part and the productioncosts are the mold and molding compoundtemperature, the injection rate or injectionprofile, the point of switchover to holdingpressure, the level and duration of holdingpressure, the cooling time and the residencetime of the melt at high temperatures. Theprocess parameters that are of relevance willdepend on the geometry of the molded partand the requirements placed on this part.

These parameters must therefore be estab-lished during the initial processing trials thatare conducted.

Apart from determining which process pa-rameters affect quality, it is also necessary toknow how these parameters affect individ-ual quality characteristics, such as appear-ance, mechanical properties, and dimen-sional and shape accuracy. The only para-meters that have a direct impact on moldedpart quality during production are the pres-sure level, the pressure profile, the temper-atures, and the flow front velocity inside themold. The remaining parameters have onlyan indirect influence. It is possible to at-tribute key quality characteristics to the in-dividual phases of the injection molding

process (Fig. 14). It is of decisive impor-tance to achieve the correct machine settingand to ensure that this setting is reproducible[7]. The machine settings for the injectionand compression phase have a very clear in-fluence on viscosity, molecular weight re-duction, crystallinity and state of orienta-tion, and this essentially affects the me-chanical and physical properties of the in-jection molded part. The surface finish,shaping and weight are also clearly influ-enced during this phase, as is flash forma-tion. The holding pressure phase essential-ly affects crystallinity, orientation inside themolded part, shrinkage and hence dimen-sional stability, weight, and also voids, sinkmarks and demolding behavior.

Time

Influencing variables Holding pressure phase:– level and duration of holding pressure– mold wall temperature– mold deformation– level of clamping force

Influencing of:a) material parameters:– crystallinity– orientation inside molded part– shrinkage

b) molded part properties:– weight– dimensional stability– voids– sink marks– relaxation– ejection characteristics

Influencing variablesPacking phase:– switchover to holding pressure– pressure limit setting

Influencing variablesInjection phase:– injection speed– melt and mold temperature– melt viscosity

Influencing of:a) material parameters:– viscosity– molecular degradation– crystallinity– orientation in surface layer

b) molded part properties:– surface quality

Cavit

y pre

ssure

Injection phase Holding pressure phase

Packing phase

Influencing of:a) material

parameters:– crystallinity– anisotropies

b) molded part properties:– extent to which part is filled out– flash formation– weight

t0 t1 t2 t3

Fig. 14: Factors that influence quality characteristics

13


By measuring the cavity pressure it is pos-sible to highlight the individual processphases that are important for the quality ofthe molded part and then to use the corre-sponding pressure curve to optimize theprocess. In order to achieve an optimumpressure curve like the one shown in Fig. 14(with a gentle transition from injection pres-sure to holding pressure), it is important toselect the correct switchover point from theinjection phase to the holding pressurephase. Figure 15 shows the potential pres-sure curve for different switchover points.If the switch to holding pressure is made attoo early a stage, it is possible for moltenplastic to flow back into the space in front ofthe screw again, and the cavity will only becompletely filled when holding pressure isapplied. This will lead to surface defects. Ifthe switchover is performed at too late astage, the pressure will increase to an ex-cessively high level during the injectionphase and, after the switch to holding pres-sure, it will be possible for melt to flow backinto the space in front of the screw again.High inherent stresses will then develop inthe area around the gate, and overfilling mayoccur.

A distinction is drawn between three com-mon types of switchover:

● screw displacement-dependent

● time-dependent

● pressure-dependent

Apart from these switchover types, there arealso further ways of performing theswitchover, all of which have their advan-tages and drawbacks. Generally speaking,

good results will be achieved with all threeswitchover types. Their advantages anddrawbacks are set out in Table 1.

Time

Too early Too late Correct

Cavit

y pre

ssure

Fig. 15: Cavity pressure profiles for different switchover points

Switchover type Advantages Drawbacks

Screw Simple to set, accurate, Reproducibility depends on displacement- independent of injection the sealing characteristics of the dependent velocity non-return valve and accurate

positioning of the metering unit, sensitive to wear

Time-dependent Can be set highly accurately, Correction required if theindependent of wear and injection time is altered,fluctuations in metering sensitive to weardisplacement

Cavity pressure- Independent of screw Reacts sensitively to viscositydependent displacement and fluctuations and to changes in

injection time the processing parameters

Table 1: Advantages and drawbacks of different types of switchover to holdingpressure

14


The injection velocity should normally beset as high as possible. The installed injec-tion capacity (injection pressure x volumeflow) must be high enough for the set in-jection velocity not to be restricted by toolow an available injection capacity, sincethis would mean that the desired injectionvelocity was not attained. Figure 16 showsthe injection velocity that can actually be at-tained on an injection molding machine as afunction of the injection pressure required(in this case, hydraulic pressure). It is clearthat the injection velocity is restricted by theperformance limit of the injection moldingmachine.

The permitted injection pressure must be setat a sufficiently high level for the desiredinjection velocity to be attained without thissetting having to be exceeded. If this is notthe case, the injection velocity will be re-stricted by the injection pressure. This iswhy it is necessary for the set injection ve-locity to be compared with the injection ve-locity actually attained. A high injection ve-locity will facilitate mold filling and ensurebetter reproduction of the cavity surface. Atthe same time, relaxation processes will en-sure that orientation and inherent stressesare eliminated more reliably. It may, how-ever, be necessary to limit the injection ve-locity if excessively high shear develops innarrow gates or if the molded part incorpo-rates localized thin walls.

The holding pressure should be set just highenough for voids and sink marks to beavoided on parts of a flawless design and toensure that other quality criteria, such as di-mensional stability, etc. are similarlyachieved. In addition to the holding pres-sure level, the time for which the holdingpressure acts also plays a decisive role. Theholding pressure can only act until the gateis frozen. The optimum holding pressure du-ration can be established by determining thesealing point (Fig. 17).

The holding pressure is then increased untilno further weight increase occurs in themolded part, and there is no longer a kinkin the cavity pressure curve [7]. If the hold-ing pressure is maintained for too long, thecycle time will be lengthened unnecessarilyand, if the cycle time is kept constant, onlya shorter metering time will be available.An excessively short holding pressure du-ration will lead to voids, sink marks and anon-reproducible molded part quality.

Hydraulic pressure pH

Scre

w ad

vanc

e rat

e vs

0100

200

300

400

500

mm/s

40 80 120 160bar

vs,target = 500 mm/s

400 mm/s

300 mm/s

vs,max

Fig. 16: The performance limit of the machine

Pres

sure

Time

Too early

Cavity pressureHydraulic pressure

Too late Correct

tN Recommended

Fig. 17: Sealing point and the set holding pressure time

15


The melt and mold temperature affect thequality of the molded part, the amount ofwaste that results, the cooling time andhence the productivity. The melt tempera-ture should be established from the pro-cessing data provided by the raw materialsproducer and kept as constant as possibleduring processing, as well as during opti-mization. The mold temperature has a con-siderable influence on both the attainablecycle time and the quality of the moldedpart. A higher mold temperature will gen-erally be required in cases where stringentrequirements are to be met in terms of thesurface finish, the inherent stress level, andthe dimensional accuracy and stability ofthe molded part. It should be borne in mindthat all material-specific figures and rec-ommendations given for the cavity temper-ature relate to the cavity wall temperatureand not to the melt inflow temperature orthe temperature set on the cooling unit.

Figure 18 shows the pronounced differencesthat can emerge here. While the inflow tem-perature can be kept constant over the en-tire processing operation, the actual moldwall temperature increases as productionprogresses on account of the hot melt, andsettles at a high level. The temperature pro-

Temp

erat

ure (

°C)

Time (min)

40

50

60

70

0 5 10 15

1: Molded part surface2: Center of wall

2

3

4

1

3: Surface of cooling channel4: Inflow

Fig. 18: Cavity temperature profiles after start-up

file then adopts a saw-tooth profile due tothe heating during the injection phase andthe cooling during the holding pressure andcooling phase.

16


It is a good idea to measure the actual cav-ity wall temperature (via the surface tem-perature of the molded part immediately af-ter demolding, for example) and to have thistemperature monitored during optimizationand processing. At all events, it is importantto be aware of the correlation that exists be-tween the inflow temperature and the actu-al cavity temperature. If malfunctions oc-cur, for instance (causing interruptions toproduction), or if the mold wall temperatureis altered by a change in the inflow temper-ature or the cycle time, then this can resultin dimensional and weight changes (Fig.19). It is then essential to wait until the equi-librium temperature has become established

again, and it may be necessary to optimizeother parameters once more in order to makecorrections to dimensions and weight. Thiswill ultimately take a great deal of time andincur costs that have a negative impact onproductivity. This makes it clear just howimportant it is to maintain the optimum op-erating point during the start-up phase, andto keep to this during production. Interrup-tions to production and subsequent correc-tions to processing parameters should beavoided as far as possible, and the melt andcavity temperature should be taken as thebasis for all optimization steps.

Environmental influences

The environmental influences acting on theinjection molding process include

● drying and material conveyance

● the machine location

● cleanliness

● ambient temperatures and relative hu-midity

● the energy, air and water supply

● the handling of the injection moldedparts

● the skill level of the work force.

Each of these points has a significant influ-ence on the quality of the molded parts andon productivity, since each one can interactwith the process parameters. The residualmoisture in the material, for instance, caninfluence both the surface finish and the me-chanical properties of a molded part. In ad-dition to this, the location of the machine(ambient temperature, relative humidity,cleanliness, etc.) is of paramount impor-tance. This is because the control responseof the temperature control systems can beadversely affected by constant changes inambient temperature if a machine is posi-tioned near to the door of a production shopthat is always being opened and closed.

115.50

Cavity-pressure-controlled process

115.45

115.40

115.35

0 10 20Cycle30 40 50 60

44.9044.8044.7044.60

Dime

nsion

s (mm

)We

ight (

g)

Fig. 19: Influence of external factors

17


Optimization strategies andconcepts for process optimization

Working on the basis of the quality criteriaand influencing factors that have been dis-cussed above, it is possible to derive the fol-lowing start-up and optimization strategyfor new molded parts and molds (Fig. 20):

First of all, the machine and mold must bepre-heated in order to ensure that a state ofequilibrium is attained as rapidly as possible.The requisite temperature settings can befound in the processing data sheets provid-ed by the raw materials producers or takenfrom the results of previous simulation cal-culations (which can similarly be performedby the raw materials producers). The settingsfor the cylinder and mold temperatures shouldbe taken from the processing data sheets sup-plied by the raw materials producers.

The clamping force must be set at a suffi-ciently high level to avoid flash. Moldbreathing additionally influences both thedimensions of the molded part in the clamp-ing direction and the weight of the moldedpart. It is important for the granules to havebeen correctly prepared in respect of dry-ing/pre-warming.

Once the preparatory measures have beencompleted, a basic setting is selected (usingprocessing data taken from the product doc-umentation or from simulation calculations)and a series of shots is run with the meteringdisplacement being gradually increased. Anassessment of the short shots will provideinformation on how the melt flows into themold, and a comparison can be drawn withsimulation calculations. The position of theswitchover point is also determined duringthis phase.

Taking the basic setting that has been es-tablished, the individual process parametersshould then be optimized by the conceptsset out below until such time as the qualityrequirements are fulfilled in respect of sur-face formation and freedom from voids andsink marks.

α

Set: ϑ1, ϑ2,...ϑD, pSt, pSp, pN, (tS), vS, tN, tK, tP, FS, T1, T2, SD, Sp, nS

Start-up

G = constant

Measure ϑM

ϑM target ?

G = constant ?

Measure ϑW1 and ϑW2

ϑW1 and ϑW2 = ϑW target ?

Monitor vS

vS = vS target ?

Optimize tN

G = Gmax

Quality control

G = constant

Series production

Assessment x = xtarget ?

Production

Change ϑ1, ϑ2,...ϑD

Change T1, T2 on thermostat

Correct vS

Correct pN

Correct pN

α

ϑ1, ϑ2,... = Cylinder temp.ϑD = Nozzle temp.pSt = Back pressurepSp = Injection pressurepN = Holding pressuretS = Injection timevS = Injection velocitytN = Holding pressure

timetK = Cooling timetP = Waiting timeFS = Clamping pressureT1, T2 = Heating/cooling

agent, temperatureSD = Metering

displacementSp = Melt cushionnS = Screw speedG = Part weightx = Mean dimensions

No

No

No

No

Fig. 20: Optimization strategy

18


To do this, the parameters are varied in thefollowing order (using the topmost value asseldom as possible in a test series and thelower values more frequently):

● melt temperature (by changing the cylin-der temperatures); since changing themelt temperature is a highly time-con-suming process, this should be changedas rarely as possible

● mold temperature – this is similarly ahighly time-consuming change

● injection velocity

● holding pressure level

● holding pressure time (to establish thesealing time)

● cooling time.

Once a reliable setting has been attainedwhich will give flawless parts, the next stepinvolves checking the remaining quality cri-teria, such as

● dimensional and shape accuracy

● stress status

● material degradation

● mechanical and physical properties

The associated parameters must then be cor-rected, where necessary, making sure thatthe optical properties are retained and thatproduction is not run with settings right ontheir upper or lower limits.

There are different methods that can beadopted for optimization. The chief targetsof process optimization are:

● production with a "robust" process set-ting. Although this will not smooth outinevitable disturbance factors such astemperature fluctuations, control toler-ances for velocities and pressures, orbatch-conditioned changes in molecularweight, additives and filler contents, etc.,it will nonetheless minimize the impactthat they have on molded part quality [8]

● improved cost efficiency through a re-duced reject rate and a shorter cycle time.

Precisely this requirement for a high levelof process reliability can make it necessaryto perform subsequent corrections to the in-jection mold. The most appropriate way ofestablishing a robust process setting and de-termining the changes required to the moldis to use systematic optimization tools, suchas statistical test planning. The optimum op-erating point can be established by meansof regression calculations or an assessmentaided by neural networks. These studies al-so provide information on the potential cen-tering parameters. A number of manufac-turers [9] offer predictive models based onthese data which use the data documentedduring the process to determine whether themolded part will probably be of good qual-ity, poor quality, or still needs to be assessed.The subsequent outlay on measurement anddocumentation can be reduced considerablyin this way.

It is important for the processing parame-ters and all the measured data to be docu-mented for each of the parameter variations.The setpoint values and the actual valuesobtained with these should be recorded forthe individual processing parameters, sincethese two values can deviate from each oth-er. Each time the setting is modified, it isessential to wait for a state of equilibriumto be established again. Only then will thereproducible molded part quality beachieved that forms the basis for stable pro-duction. The dimensions of the molded partshould be checked both immediately aftercooling and after the time stipulated in DIN16901 (24 to 98 h after production), sincethe dimensions can still change a long timeafter the injection molding process has end-ed. A relationship can then be establishedbetween the molded part dimensions directlyafter cooling and the definitive dimensionsfollowing an appropriate storage period,which can be used in future start-up process-es. Following this, all the setpoint valuesand resultant actual values for the optimumoperating point should be recorded so thatthey can be reproduced as rapidly as possi-ble for future start-up processes. This willkeep downtime and waste to a minimum andconsiderably improve productivity.

19


Different concepts can be employed for pur-poses of establishing the optimum operat-ing point as rapidly and reliably as possibleand hence for achieving optimum moldedparts. A number of these are listed here byway of example:

● the evolution strategy (with the appro-priate hardware and software)

- intelligent trial-and-error

- use of the evolution mechanisms

● statistical test planning (different methods)

- design of experiments

- planning by the Shainin method

- neural networks (for assessments)

- regression analyses (for assessments)

● start-up aids from machine builders orraw material producers, some of whomemploy the concepts listed above.

The evolution strategy, for instance, is basedon the evolution theory (Fig. 21). This in-volves the optimum operating point beingestablished automatically with the aid ofcomputer programs when a new mold is runin or when production is already running.The computer modifies the process para-meters within meaningful limits to this end.The quality results obtained in this way arerated either automatically or manually andnotified to the computer. Drawing a com-parison with the preceding settings and re-sults, the computer repeatedly selects newsettings, thereby approaching the point ofoperation that offers the most favorablecompromise between the individual quality

characteristics. The computer can then main-tain the optimum operating point establishedin this way within pre-set tolerance limits[7]. If this approach is compared with theheuristic method in which the parametersare modified on an individual basis and theimpact of the modification assessed (trialand error), then the evolution strategy hasclear advantages in that it is quicker to use,since more than one parameter can be variedat a time and the impact assessed automati-cally [2]. A further advantage comparedwith the single-point method is that the in-teraction effects of the individual parame-ters can be detected and assessed.

Parent

Offspring

Parameter 2

Parameter 1

Quali

ty

Fig. 21: The evolution strategy [2]

20


Apart from this system, which runs fully au-tomatically with the appropriate hardwareand software, it is similarly possible to varymore than one parameter at a time when us-ing methodically-compiled test plans (sta-tistical test design) that proceed from a "cen-tral point". A parameter variation with eightto sixteen machine settings and five to tencycles per setting is sufficient to generateinformative process models for the individ-ual case [9]. Figure 22 shows the methodused to compile a test design. Starting witha central point, such as the basic setting es-tablished during start-up, both an inner ex-periment (with just a slight change in the in-dividual parameters) and an outer experi-ment (with large-scale changes in the indi-vidual parameters) are performed. A test se-ries is first conducted with the central pointto this end. As the next step, the cornerpoints are approached by varying the threepreviously-chosen parameters that have abearing on quality. This step is then repeat-ed in order to check the reproducibility ofthe central point. A total of 2 x 8 + 2 tests arethus required for this example. Figure 23 shows the evaluation of the test

with the aid of multi-dimensional regressionanalysis. In this example, which involvesthe optimization of a length dimension, threeprocessing parameters (holding pressure lev-el, holding pressure time and cooling time)were varied around the central point in bothan inner and an outer experiment. The three-dimensional parameter variation range isworked through on a uniform basis, and theimpact of each parameter on the specific

characteristic taken for the evaluation. Thegraphic shows the mean values that emergefor the length dimension, the signal-to-noiseratio and the variance within the individualmeasurement series. The signal-to-noise ra-tio constitutes a measure of the robustness ofthe process and is calculated as follows [8[:

S/G = log (y2/s2) in [dB]where: y = mean value of characteristic

s = variance of each test setting

Para

meter

2

Parameter 1

Central point (basic setting)

Inner experiment

Outer experiment

+

+

+

–

Param

eter 3

Fig. 22: Statistical test plan for three free parameters

21


The ratio is expressed in decibels and is acomparative value which is independent ofthe units used for the characteristics. It canthus be taken as a quality index for all thequality characteristics being observed at anyone time. If the correlations between pro-cessing parameters and molded part prop-erties become too complex, a high outlaywill be required to present these with the aidof regression analysis. It then makes sense touse neural networks both for describing thecorrelations between the processing data andthe properties of the molded part and forpurposes of process optimization.

Figure 24 shows a test plan for five param-eters in which the number of tests requiredis reduced to a minimum by applying theDoE method (Design of Experiments). Inthis plan, the settings are moved towardseight different points arranged around a cen-tral point. Counting the control test con-ducted on the basic setting at both the startand the end of the overall test series, onlyten tests need to be evaluated here.

161.28161.26161.24161.22161.20161.18161.16161.14

90

88

86

84

82

A–Holding pressure (hydr.) Holding pressure time Cooling time

J– Z J+ A+ A– J– Z J+ A+ A–

SW

Varia

nce

S:N [d

B]Me

an va

lue [m

m]

J– Z J+ A+

0.00020

0.00015

0.00010

0.00005

0

Fig. 23: Effect of parameter variation on the length characteristic

Stage planParameter/unit Parameter 1 Parameter 2 Parameter 3 Parameter 4 Parameter 5

M M M M M MZ Z Z Z Z ZP P P P P P

Test planParameter 1 Parameter 2 Parameter 3 Parameter 4 Parameter 5 Cycle time

1V Z Z Z Z Z2V M M M M M3V M M M P P4V M P P M M5V M P P P P6V P M P M P7V P M P P M8V P P M M P9V P P M P M

10V Z Z Z Z Z

Part removalNumber Assessment Designation

5 for coordinate measuring table xV1. xV510 for attributive assessment (overheating marks completely excluded) xV1. xV2

M minus lower limitZ central point mean valueP plus upper limit

Fig. 24: Statistical test plan for five free parameters


Fault diagnosisThe different types of fault that can occurin injection molding are just as varied as thedifferent factors that influence the injectionmolding process. In view of the number ofpotential faults, it is not the individual faultsor classes of fault that are set out below butrather the basic procedure that should beadopted for fault diagnosis, illustrated withan example. At the same time, a number ofaids are listed which contain essential in-formation on fault diagnosis.

The difference between processoptimization and fault diagnosis

While process optimization generally pro-ceeds from a reliable process and sets out tooptimize this process, fault diagnosis is em-ployed when too many non-conformingmolded parts are produced. The chief targetof fault diagnosis is thus to analyze the causeof the fault as rapidly as possible and to findand implement the production conditionsthat will give conforming molded parts.Maximum cost-efficiency in the processthen ranks behind the aim of eliminating thefault as rapidly as possible. The differenttargets and procedures for process opti-mization and fault diagnosis are set out inTable 2.

After the fault has been successfully diag-nosed and eliminated, process optimizationcan be conducted in order to increase pro-ductivity once the process has sufficientlystabilized.

Fault diagnosis procedure

As with process optimization, it is worth-while adopting a systematic approach tofault diagnosis too. The causes of the faultsthat occur must similarly be sought in all sixfactors that have an impact on the quality ofthe molded part (Fig. 3). The following step-by-step approach can be taken as a guide tofault diagnosis:

● Precise description and classificationof the fault

Photographs and descriptive texts constituteessential aids for fault classification. Thecauses of the fault can be further differenti-ated by employing technical aids such asmoisture measurement units, balances,calipers or measuring gauges, microscopesand, where appropriate, chemical analyses.

● Establishment of boundary conditionsA description of the boundary conditionsmakes a decisive contribution to fault diag-nosis. These can be clarified with the fol-lowing questions:

Where did the fault occur?- close to the gate- remote from the gate- on ribs or bosses- on perforations- on weld lines- ...

What does the fault look like?

When did the fault occur?- during start-up- during initial sampling- after a production stoppage- after a material or batch change- suddenly, without any evident change in

the boundary conditions- sporadically, or on every part- ...

Process optimization Fault diagnosis

Starting Stable production conditions Production with a high percentagesituation permitting reliable series of parts that do not meet

production the specifications

Target Improved cost-efficiency Elimination of the fault, establishment of reliable production conditions

Increased output-to-input ratio Cycle time and resource deploymentonly of secondary importance

Procedure Use of statistical experiment Determination of the cause of planning or similar measures to the fault optimize the production conditions; Determination of remedial measures productivity then increased through Where appropriate, elimination of further adjustments to the injection the identifiable defect through molding machine and mold alternative measures

Table 2: Comparison between process optimization and fault diagnosis

22

23


Which material was used?- semi-crystalline or amorphous- unfilled, fiber-reinforced, mineral-filled- hygroscopic- especially sensitive to processing- ...

What mold structure was employed?- with a hot runner- a three-platen mold- with direct gating- ...

What measurements were recorded for theactual processing conditions?- melt temperature- mold surface temperature- injection time (injection velocity)- fluctuations in the processing conditions- ...

● Determination of potential causes ofthe fault

The information that is established shouldbe compared with recommendations fromtroubleshooting guides, start-up aids fromthe machine builders or raw material pro-ducers, or with the appropriate computerprograms or expert systems.

● Search for further detectable faults

In many cases, a closer inspection will re-veal further faults on the reject parts. Theseadditional faults, known as symptoms as inmedicine, will provide further informationon the most probable causes of the fault andthus permit a more reliable diagnosis.

● Classification of these additional faults

The questions set out above regarding theboundary conditions should then be an-swered for these additional faults that havebeen established either on the molded part orduring the production process, and the po-tential causes of the faults determined.

● Determination of the most probablecauses of the faults

Determining the causes that most faultswould tend to suggest.

● Establishment of the best remedialmeasures

Allocation of remedial measures to the mostprobable causes of the fault, selection ofpromising remedial measures on the basisof the following criteria:- efficiency- implementation outlay- economic impact (cycle time, energy requirement, finishing work).

The best solution is always to eliminate theactual cause of the fault (due to the machineor the mold, for example). Only in excep-tional cases should the symptoms be elimi-nated by adjusting the processing parame-ters.

● Rectification of the fault and continu-ation of production

Fault-diagnosis aids

Machine operators can eliminate a largenumber of faults very rapidly by virtue oftheir general experience of injection mold-ing or their knowledge of the particularprocess employed. When it comes to recti-fying more complex faults, the operator cancall upon advice from experienced col-leagues or from experts at the machine man-ufacturer's or raw material producer's.

More detailed information on troubleshoot-ing can be found in both the printed litera-ture [10, 11, 12, 13] and the electronic lit-erature [14]. Where several faults have oc-curred simultaneously, the most probablecause can readily be established with com-puter-based aids. Background information,such as integrated "Application Technolo-gy Information" can then be used to selectthe best corrective action.

24


An example of fault diagnosis

Figure 25 shows just how difficult it can beto provide a precise description of a fault,along with its probable causes.

All four faults would appear to be almostidentical at first sight. A more detailed ob-servation and knowledge of the differentfault types is required before the faults canbe precisely allocated to the appropriate cat-egories. Figures 26 to 28 show potentialtypes of fault, together with their causes andremedies. In this case, the faults are classi-fied on the basis of the subtle differencesthat make it possible to give a precise de-scription of the faults at all.

In the case of faults with a similar appear-ance, further tests will frequently be requiredbefore the fault and its most probable caus-es can be precisely classified. To assist inclassification, the TVI test can then be con-ducted to determine the moisture in the gran-ules, and the cycle time can also be extend-ed. Extending the cycle time increases theprobability of charred streaks occurring,while the longer residence time in the dryerwill reduce the probability of moisturestreaks. If the streaks are oriented in the di-rection of demolding, this would suggestthat the surface is being damaged during de-molding.

Fig. 25: Different types of fault

CauseExcessive thermal stressing of the melt

1 Melt temperature too high:Optimize processing conditions

2 Melt residence time too long:Select a different machine

3 Screw speed too high:Optimize processing conditions

4 Nozzle and flow channel cross-sections too small:

Optimize machine or mold

5 Production interrupted without the temperature being reduced:

Train personnel

Fig. 26: Needle-like streaks in the direction of flow

25


Selecting the most appropriateremedial measures

Figure 26 shows a fault in the form of "nee-dle-like streaks in the direction of flow" withits key cause and the appropriate remedialmeasures. Once the potential causes of "ma-terial too moist" and "air incorporated dur-ing plastication" have been excluded, themost probable cause is that the melt is beingsubjected to excessive thermal stressing.

This can be due to the following more de-tailed faults and can be rectified by the ap-propriate measures:

Melt temperature too high:

Optimize the processing conditions

Melt residence time too long:

Select a different machine,Optimize the cycle time

Screw speed too high:

Optimize the processing conditions

Nozzle and flow-channel cross-sections toosmall:

Optimize the machine or mold

Production interrupted without the temper-ature being reduced:

Train personnel

These different remedial measures involvevarying degrees of time, trouble and ex-pense. Optimizing the processing conditionsis generally the cheapest option, but per-forming an optimization to remedy the faultthat has occurred can also have a negativeimpact on other quality criteria or on thecost-efficiency of production. The other faultcauses should therefore also be taken intoconsideration for purposes of a detailed faultrectification. A step-by-step approach willfrequently prove successful in these cases:

● rectification of the fault by implement-ing the easiest remedial measure andthen continuing with production

● rectification of the actual cause of thefault during a production stoppage orplanned maintenance interval

● optimization of the process to achievean enhanced quality level and reducedproduction costs

Causes

● Excessive residual moisture in thegranules

Remedial measures

● Check the drying process(temperature, time and hourly through-put)

● Examine dryer filter for contamination

● Check direction of rotation of drivemotor

Causes

● Entrapped air

● Metering stroke of the plasticating unittoo long

Remedial measures

● Optimize the plasticating conditions

● Increase the back pressure (within accept-able limits); reduce the screw retraction

● Position injection nozzle tight up againstthe hot runner mold

● Use a larger plasticating unit to reducethe length of the metering stroke (< 3D)

or

● Increase the temperature of the feed section, reduce the screw speed, increase thecycle time and, as an additional, optional measure, increase the melt cushion by1 D if possible

Fig. 27: U-shaped streaks open towards the flow direction

Fig. 28: Brush-shaped streaks over a large area

26


ProspectsRaising productivity levels will continue toplay a key role in the production of parts byinjection molding in future too. Advancesin machine and mold technology, new spe-cial processes and combinations of existingprocesses, plus tailor-made materials willall ensure that the injection molding processbecomes more cost-efficient and that newmarkets are opened up for thermoplastic in-jection moldings at the same time.

Process optimization and control strategieswill also contribute towards achieving in-creased productivity. Establishing the opti-mum process conditions will assume greaterimportance, as will automatic process mon-itoring. Advances in data technology willpermit large quantities of data to be handledin future and will make image data pro-cessing accessible for commercial-scale ap-plication. It will then be possible for boththe start-up process and fault diagnosis tobe largely automated. These measures willpermit

● less mold proving, with fewer alter-ations to the mold

● higher product quality

● production close to the theoretically at-tainable limits

SummaryThe level of productivity that can be attainedin injection molding is conditioned by alarge number of different factors. While ob-serving a process solely from the optimiza-tion angle will certainly contribute towardsincreasing its productivity, this will not be aseffective as a holistic observation of all thefactors in the process chain: the material,molded part design, mold, machine, pro-cessing and the environment. It is thus im-portant for optimization to start at the de-sign phase and continue right through to thefinal quality inspection (Fig. 29).

The justifiable outlay on optimization is al-so conditioned by the number of articles tobe produced. The extreme cases here arepackaging, on the one hand, where even theinjection molding machines are series-pro-duced, and small series, on the other, whereproduction runs are so small that just thefew molded parts produced for a statisticaltest plan will be sufficient to cover the an-nual production requirement.

Where injection molding faults occur andprevent the production of flawless parts, run-ning production at the lowest possible costceases to be the prime concern. The maintarget in this case will be the re-establish-ment of a reliable production process. Onlywhen this has been achieved can the processbe further optimized.

Processing

Material

Molded part designMold

MachineEnvironment

1. Audit of

high-potential articles

2. Identification and

elimination of problems

Fig. 29: Increasing productivity through process optimization

27


References[1] B. M. Bauer Investigations into the use of an automatic optimization

system for material assessment in injection molding,Diploma Thesis (in German),University of Erlangen 1996

[2] H. Offergeld, J. Lochner Darwinian optimization of operating points (in German),Kunststoffe 85, Carl Hanser Verlag 1995

[3] H. Jahn Production quality, the logical consequence of thequality of workmanship (in German), VDI-Z,130 (1988) 4, pp. 4-12

[4] Anon Durethan® KU 2-2140/30 H2.0Application Technology Information 0953e Bayer AG 1996

[5] Anon CONTURA System, Presentation documents fromInnova Engineering GmbH

[6] A. J. Kaminski, Relationship between screw diameter,F. W. Lambeck metered volume, density and shot weight

ATI 1103e, Bayer AG 1997

[7] S. Joisten Injection molding: process optimization and controlPI 061e, Bayer AG

[8] R. Bourdon Quality optimization in injection molding throughrobust process settings,Seminar on optimum injection molds (German),Süddeutsches Kunststoff-Zentrum, Würzburg 1999

[9] Hohenauer, Michaeli, Injection molding: reliably predicting the quality of each Vaculik, Savoie dividual part (in German), QZ 39, Carl Hanser Verlag 1Rapperswil, Wybitul

[10] K. Niemann (Ed.) Machine-setting strategy for thermoplastic injectionmolding machines (in German),Hüthig Verlag, Heidelberg 1992

[11] M. Bichler Injection molding flawless plastic parts (in German),Hüthig Verlag, Heidelberg 1999

[12] P. Thienel, R. Sass, Troubleshooting guide for surface defects onC. Vitz, J. Wahle thermoplastic molded parts (in German),

Kunststoffinstitut, Lüdenscheid 1992

[13] A. J. Kaminski, Spritzgießen – Fehler, Ursachen, AbhilfenF. W. Lambeck Injection moulding – Faults, causes, remedies

Moulage par injection – Défauts, causes, remèdesCD-ROM, Bayer AG 1999

[14] Anon Guide to Injection Moulding, CD-ROM,Bayer AG 1999

This information and our technical advice – whether verbal, in writingor by way of trials – are given in good faith butwithout warranty, andthis also applies where proprietary rights of third parties are involved.Our advice does not release you from the obligation to verify the in-formation currently provided – especially that contained in our safetydata and technical information sheets – and to test our products as totheir suitability for the intended processes and uses. The application,use and processing of our products and the products manufactured byyou on the basis of our technical advice are beyond our control and,therefore, entirely your own responsibility. Our products are sold in ac-cordance with the current version of our General Conditions of Saleand Delivery.

Unless specified to the contrary, the values given have been establishedon standardized test specimens at room temperature. The figuresshould be regarded as guide values only and not as binding minimumvalues. Please note that, under certain conditions, the properties can beaffected to a considerable extent by the design of the mold/die, theprocessing conditions and the coloring.

Bayer plastics on the Internet:www.plastics.bayer.com

Bayer AG Bayer Polymers

D-51368 Leverkusen

2002-09KU 11829en

injection moulding -quality molded parts

Documents