Abstract

The increasing demand for micro-injection molding process technology and the corresponding micro-molded products have materialized in the need for models and simulation capabilities for the establishment of a digital twin of the manufacturing process. The opportunities enabled by the correct process simulation include the possibility of forecasting the part quality and finding optimal process conditions for a given product. The present work displays further use of micro-injection molding process simulation for the prediction of feature dimensions and its optimization and microfeature replication behavior due to geometrical boundary effects. The current work focused on the micro-injection molding of three-dimensional microparts and of single components featuring microstructures. First, two virtual a studies were performed to predict the outer diameter of a micro-ring within an accuracy of 10 µm and the flash formation on a micro-component with mass a 0.1 mg. In the second part of the study, the influence of microstructure orientation on the filling time of a microcavity design section was investigated for a component featuring micro grooves with a 15 µm nominal height. Multiscale meshing was employed to model the replication of microfeatures in a range of 17–346 µm in a Fresnel lens product, allowing the prediction of the replication behavior of a microfeature at 91% accuracy. The simulations were performed using 3D modeling and generalized Navier–Stokes equations using a single multi-scale simulation approach. The current work shows the current potential and limitations in the use of micro-injection molding process simulations for the optimization of micro 3D-part and microstructured components.

Highlights

  • A consolidated trend in micro-manufacturing consists of the adoption of replication technologies for large-scale productions

  • To hasten the micro product design phase, optimize μIM process conditions as well as predict process quality and performance, significant attention has been dedicated to the numerical modeling and the simulation of such technology, aiming for the establishment of a μIM digital twin

  • The μIM process encompasses three families of products that significantly constrain the technical equipment required for processing and simulation [2], as described in Table 1. μIM process simulation has been developed from conventional IM modeling methods

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Summary

Introduction

A consolidated trend in micro-manufacturing consists of the adoption of replication technologies for large-scale productions. One other challenging aspect for μIM process simulation is the implementation of the cavity’s surface topography into the model Even though this term was found to be significant in altering the filling behavior of microfeatures [16], the boundary layer on all the skin parts would require a consistent extension of the number of elements and time required for the simulation. It is not cost-effective to measure the entire surface roughness of a mold cavity and correctly model it in a digital form. CThaTsehe se2e—sceocMnodnicdrcoac-asCseaeprreeffeerrss ttoo aannootthheerrsisningglelemmicricor-oco-cmopmopnoenntetnhtatthhaatdhaandoamninoaml pinaartl wpaerigthwt eoifg0h.1t of pp0mCsmoCaei.rrme1msafoomoCaepolgpdamcsadmfuarop.gepenpearhulrTplc.sgaaeTpeoohicotsTlhmct.gshoorytiitfhoepegiahoTryeeeooaefahtan-detphCnisffetr-dtpohlaeiefwrahootonlafcrsiahmoeropnwgftra.o,seopwtr,ahsinpDeparsoiDrpa-tdseetbaatrfledtbahmcaridahlricroliettellsstlietelaappwiita.cpotsosdycplisyope,iofaocne,rccnrtTcybnepr,tTtoeeoseheisXdDXiddmildmifdcesii,sie,ttcatcitmimUyresfUntsnpltosidlieSoeaSooacoFrFtrrAonsArnffioiitccnt,ggmhtt)i)iauTahuaahaceFaanmnlnleroeXrlinlnpeoedygdyn,efdfdrt3ou3saorhUeae,erich,vrrdhvesvmavSiemaaartaaiaanAancdsia3dilllsadtllluadt,i)iuayoatinboaaihoabaafholnhtgananlehtnianteolvosidaeohpdosolnapanollneofmahoilphofdllopofwaaypflailofwfyposacebolldfiarstovrlxlfacaiohemstlxafyaacpaaphl-lyatmpsacappaueihthmostaorteilaeohienoimtrtlttocefldyhhenilotaitnopfoeodhnyhrtioinownximlenyeotreoinythnonmlnfeeanteemtfdthrentanfleaniniflmeodp(ernetotaaPainntmefesot(lhOsotahPrhdnhtghyfbeelhMaOieeddacltgafetboeahsMo)imtehnmaceilper(onaadsHteim)aeenmhetldp(rdteo(ddHaeiotraPerinastyuncranttioOedot.asaornnasntyuaTnflMnaodtrlod.hsainymrggnbtμaT)fe.dmrioeoadiTIh(vycnorsMgfHuμheeCr.meamiinstTeIvdotlch2MtsiehesCrprci7seoitmtnyaeae0tarn2.slirt2pryfpuci7tsptT1o.amaaolae0w,rawrhrlfrtTg2oCmuttteapi1iedhpoelovswa,irapuelrnfgCeoCmantoacanhindcpdcwetorsa2rtieeultrsnodi7maassooμetcwn0eessniftcwtIca2ieeMa0oaod1asss.fln,1eess parameters

Multi-Scale Modeling and Meshing of Single Micro-Components
Findings
Multi-Scale Filling Simulation Validation at Mesoscale—Cases 3 and 4
Full Text
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