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FE Modelling and Characterization of Chip Curl in Nose Turning process
University West, Department of Engineering Science, Research Enviroment Production Technology West. (PTW)
University West, Department of Engineering Science, Division of Manufacturing Processes. University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing. (PTW)ORCID iD: 0000-0003-0976-9820
Sandvik Coromant AB, Sandviken, Sweden.
(English)In: International Journal of Machining and Machinability of Materials, ISSN 1748-572XArticle in journal (Refereed) Submitted
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology
Identifiers
URN: urn:nbn:se:hv:diva-8670OAI: oai:DiVA.org:hv-8670DiVA, id: diva2:871452
Note

Inågr i licentiatuppsats

Available from: 2015-11-14 Created: 2015-11-14 Last updated: 2020-03-16Bibliographically approved
In thesis
1. Characterization & modeling of chip flow angle & morphology in 2D & 3D turning process
Open this publication in new window or tab >>Characterization & modeling of chip flow angle & morphology in 2D & 3D turning process
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Within manufacturing of metallic components, machining plays an important role and is of vital significance to ensure process reliability. From a cutting tool design perspective,  tool macro geometry  design  based on physics based  numerical modelling  is highly needed  that can predict chip morphology.  The chip morphology describes the chip shape geometry and the chip curl geometry. The prediction of chip flow and chip shape is vital in predicting chip breakage, ensuring good chip evacuation and lower surface roughness.  To this end, a platform where such a  numerical model’s chip morphology prediction  can be compared with experimental investigation is needed and is the focus of this work. The studied cutting processes are orthogonal cutting process and nose turning process. Numerical models that simulate the chip formation process are employed to predict the chip morphology and are accompanied by machining experiments. Computed tomography is used  to scan the chips obtained from machining experiments and its ability to capture the variation in  chip morphology  is evaluated.  For nose turning process,  chip  curl parameters during the cutting process are to be calculated. Kharkevich model is utilized in this regard to calculate the  ‘chip in process’ chip curl parameters. High speed videography is used to measure the chip side flow angle during the cutting process experiments and are directly compared to physics based model predictions. The results show that the methodology developed provides  the framework where advances in numerical models can be evaluated reliably from a chip morphology prediction capability view point for nose turning process. The numerical modeling results show that the chip morphology variation for varying cutting conditions is predicted qualitatively. The results of quantitative evaluation of chip morphology prediction shows that the error in prediction is too large to be used for predictive modelling purposes.

Place, publisher, year, edition, pages
Trollhättan: University West, 2015. p. 67
Series
Licentiate Thesis: University West ; 5
Keywords
Chip curl, Chip flow, Computed tomography, Chip formation, Machining
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-8671 (URN)978-91-87531-20-0 (ISBN)978-91-87531-21-7 (ISBN)
Presentation
2016-03-31, 11:00 (English)
Supervisors
Available from: 2016-04-01 Created: 2015-11-14 Last updated: 2019-12-03Bibliographically approved
2. Improved finite element modelingfor chip morphology prediction inmachining of C45E steel
Open this publication in new window or tab >>Improved finite element modelingfor chip morphology prediction inmachining of C45E steel
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Within the manufacturing of metallic components, machining plays an important role and is of vital significance to ensure process reliability. From a cutting tool design perspective, physics-based numerical modeling that can predict chip morphology is highly necessary to design tool macro geometry. The chip morphology describes the chip shape geometry and the chip curl geometry. Improved chip morphology prediction increases process reliability by improved chip breakability and effective chip evacuation.

To this end, in this work, a platform is developed to compare a numerical model'schip morphology prediction with experimental results. The investigated cuttingprocesses are orthogonal cutting process and nose turning process. Numerical models that simulate the chip formation process are used to predict the chip morphology accompanied by machining experiments. Computed tomography isused to scan the chips obtained from machining experiments evaluating its ability to capture the chip morphology variation. For the nose turning process, chip curl parameters need to be calculated during the cutting process. Kharkevich model is utilized in this regard for calculating the 'chip in process' chip curl parameters. High-speed videography is used to measure the chip side-flow angle during thecutting process experiments enabling comparison with physics-based model predictions.

With regards to chip shape predictability, the numerical models that simulate the chip formation process are improved by improving the flow stress models and evaluating advanced damage models. The workpiece material, C45E steel, arecharacterized using Gleeble thermo-mechanical simulator. The obtained flow stress is modeled using phenomenological flow stress models. Existing phenomenological flow stress models are modified to improve their accuracy. The fracture initiation strain component of damage models' influence on the prediction of transition from continuous chip to segmented chip is studied. The flow stress models and the damage models are implemented in the numerical models through FORTRAN subroutines. The prediction of continuous to segmented chip transitions are evaluated for varying rake angles and feed rate ata constant cutting velocity.

The results from the numerical model evaluation platform show that the methodology provides the framework where an advance in numerical models is evaluated reliably from a 'chip morphology prediction capability' viewpoint forthe nose turning process. The numerical modeling results show that the chip curl variation for varying cutting conditions is predicted qualitatively. The flow stress curves obtained through Gleeble thermo-mechanical simulator show dynamic strain aging presence in specific temperature -strain rate ranges. The results of the phenomenological model modification show their ability to incorporate the dynamic strain aging influence. The modified phenomenological model improvesthe accuracy of the numerical models' prediction accuracy. The flow stress models combined with advanced damage model can predict the transition from continuous to segmented chip. Within damage model, the fracture initiation strain component is observed to influence the continuous chip to segmented chip transition and chip segmentation intensity for varying rake angle and feed rate and at a constant cutting velocity.

Abstract [sv]

Populärvetenskaplig Sammanfattning

Bearbetning är en 150-årig tillverkningsprocess som återfinns antingen direkt eller indirekt i nästan allt som tillverkas. I dagsläget med den snabba omställning motmer digitala arbetssätt riskerar allt som inte digitaliseras med stor sannolikhet att bli kvarlämnat. Två aspekter mot digitaliseringen av skärande bearbetningsprocesser har genomförts i detta arbete. Den första var en utvärdering av befintliga metoder och utvecklingen av nya metoder för att digitalisera komplexa spångeometrier som återfinns i bearbetningsprocessen, vilket inte tidigare gjorts. Nästa steg är att fånga fysiken som är involverad i en skärprocess för att kunna simulera denna med högre noggrannhet. I denna del av arbetet har inriktats till att urskilja små förändringar i ingångsförhållandena i dess relation till spånformning.

En spånans ytstruktur kan vara antingen slät eller korrugerad. Att veta vilken spånform som kommer att skapas ger oss förmågan att bättre kontrollera bearbetningsprocessen. I det genomförda arbetet har det skapats förbättrande materialmodeller som möjliggör en ökad noggrannhet vad gäller möjligheten att simulera spånformen vid skärande bearbetning. En stor del av arbetet här harägnats åt en ökad förståelse av ett materials uppträdande, i detta fall stål, vid skärande bearbetning. Detta har skett genom omfattande materialtestning där testresultaten har presenterats i form av matematiska ekvationer i de numeriska modellerna. Övriga metoder som har används för att skapa dessa digitala spånor inkluderar datortomografi, höghastighetsvideografi och matematiska modeller. När dessa kombineras med datorgrafik kan man erhålla numeriska modeller för att simulera skärande bearbetning.

Resultatet av denna förbättring av befintliga numeriska modeller är förmågan att se påverkan av hur små förändringar i skärverktygets geometri kan påverka formen på den av skärprocessen skapade spånan. Sammantaget kan resultatet av den genomförda forskningen bidra till att skapa ett obrutet virtuellt arbetssätt vidproduktutveckling av skärande verktyg.

Place, publisher, year, edition, pages
Trollhättan: University West, 2020. p. 93
Series
PhD Thesis: University West ; 34
Keywords
Chip curl, Chip flow, Chip segmentation, Computed Tomography, Damage modeling, Flow stress modeling, Machining, Spånkrökning; Spånflöde; Spånsegmentering; Datortomografi; Skademodelleringen; Modellering av Flytspänning; Bearbetning
National Category
Manufacturing, Surface and Joining Technology
Research subject
Production Technology; ENGINEERING, Manufacturing and materials engineering
Identifiers
urn:nbn:se:hv:diva-14979 (URN)978-91-88847-52-2 (ISBN)978-91-88847-51-5 (ISBN)
Public defence
2020-02-12, Albertssalen, 10:00 (English)
Opponent
Supervisors
Available from: 2020-02-19 Created: 2020-02-19 Last updated: 2020-02-19Bibliographically approved

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