ADDITIVE MANUFACTURING OF SPARE PART SUPPORTED BYDIGITAL DESIGN CONCEPT

Tarja LaitinenVTT Technical Research Centre of Finland Ltd

Tampere, Finland

Pasi JulkunenSandvik Mining and Construction Ltd

Tampere, Finland

Anssi Laukkanen, Pasi Puukko and Erja TurunenVTT Technical Research Centre of Finland Ltd

Espoo, Finland

ABSTRACT

Material processing (P) method defines through the forming microstructure(S), what kind of properties (P) the material has in certain environment andhow the material performs (P). Integrated computational materialengineering (ICME) transfers the traditional material development based onexperimental trial and error approach into digital approach and enables newangles for component design through true performance based materialdevelopment. Digital design and digital manufacturing combined with digitalmaterial design masters the life cycle of a component with endless variationpossibilities in extremely short time periods. The digitally developed,performance optimised, load bearing components can be executed throughpowder metallurgical (PM) route manufactured by 3D printing, e.g.,selective laser melting (SLM).

The concept based on digital design from component level down to materialsmicrostructure based on the performance needs is presented. Digital designroute is compared to the experimental route. The benefits are presentedthrough OEM case example.

INTRODUCTION

The process of joining materials to make objects from 3D digital model data,usually upon layer upon layer, as opposed to subtractive methodologies, isreferred to as additive manufacturing (AM). AM is expected to result in the“Third Industrial Revolution” [1] . Introducing Integrated ComputationalMaterial Engineering (ICME) principles and digitalizing the process andmaterial design for manufacturing of metal parts, it is argued that thepotential of AM and discovery of new novel solutions can be tapped into farmore effectively, which has great promise and significance forcompetitiveness of high technology industries. This will allow the industries

to benefit from and exploit multiscale modelling technologies in their designof advanced manufacturing processes, materials and components resulting inimproved competitiveness. By implementing ICME the development span ofmaterials-enabled products can be shortened, their overall time-to-marketand the affiliated costs decreased, as presented in Figure 1. The stages ofdiscovery, development, property optimization, system design, certification,manufacturing and deployment can be carried out far more efficiently andresult in improved, performance tailored and more competitive products [2] .The computational environment enables a decrease in complex and costlyprototyping stages, better control of uncertainties and a far more systematicapproach over the traditional trial-and-error approaches. Adaptation ofICME in establishing a digital factory for design is expected to decreasetime-to-market of new solutions and products by at least 25-50% [3] , resultin return-of-investment by a factor of 3 to 9 across industry sectors [4] [5]and do so at a fraction of the cost [6] .

Figure 1. Development of additive manufacturing processes, materials anddesigns and application to new solutions without (left) and with (right)integrated computational materials engineering.

PSPP CONCEPT AND APPROACH

First principles and thermodynamics are included for material design. Inorder to address the SLM manufacturing process, these methods provide abasis for both establishing the process models as well as formulation ofmodels tackling solidification and nano-microstructure formation by way ofa phase field approach. The nano-microstructure formation takes place in apowder bed. The thermomechanics of the powder bed are treated using adiscrete to continuous approach at the meso scale, at the scale of the materialmicrostructure. A link and coupling to continuum, macroscale componentbuild model is introduced in order to be able to work with the process andmaterial behavior at the scales of the macroscale component. In order toreflect upon the significance of the fundamental alloy design and theoutcome of the manufacturing process, a nano-microstructure foundedstructure to properties to performance modelling stage follows. These are aninput to the final stage of analysis, part design, which will input macroscaleinformation from the process model at full build scale, and incorporate thatalong with material property and performance results to address the problemof designing an AM component for a particular specific function. Thesecritical parts will be integrated. The core modules are software librariesbetween solvers and proprietary tools, to facilitate both functionality,integration, development of novel features and utilization of a limited set ofexisting proprietary modelling workflows.

The ICME multiscale modelling approach addresses the process, materialand component design for AM, particularly selective laser melting (SLM).The models being extended with respect to spatial and temporal scales aresummarized with respect to critical features in Figure 2, and also presentedin Figure 3 with respect to the multiscale modelling methods. The purpose ofthese four links in the multiscale modelling chain is to cover the respectivetechnologies of ICME of SLM for design of materials, processes andcomponents. The concept follows the Process-Structure-Properties-Performance (PSPP) [7] [8] [9] [10] . ICME paradigm applied to powdermetallurgical materials all the way to part design [11] [12] . The physics andmodels covered in the ICME approach are:

First principles, computational thermodynamics, kinetics and phasefields: Compositional material design, phase field modeling ofsolidification structuresMesoscale process modelling: Discrete and continuous modelling ofthe AM manufacturing process thermomechanics.Mesoscale nano-microstructure modelling: Discrete and continuousmodelling of the performance of nano-microstructures with respectto performance limiting mechanisms.Macroscale component design, tailoring and optimisation: Designand optimisation of small scale AM structures (e.g. superlattices)and part scale components.

Figure 2. Multiscale modelling methods of powder metallurgical problemsacross spatial and temporal scales.

Figure 3. Multiscale models, physics, links and interfaces in the multiscaleICME platform.

EXPERIMENTAL

The OEM case example component chosen was oil pressure distributor valveof a rock drill piston. AM feasibility was studied in one of the mostdemanding mechanic-hydraulic components – a rock drill. The distributorvalve annual load cycles in customer use are close to 300 million strokes.

Distributor valve regulates oil pressure, which controls movements of thepiston. The impact speed of the valve is ca. 5 m/s towards end stoppers.Currently valve is manufactured from low-alloy, medium carbon steelparison, which has been case hardened. Machining of such high hardnesssurfaces is demanding, time consuming and requires special tooling.Distributor valve is designed based on pure axial, impact loading. Surfaceroughness demand Ra is 0,4. Manufacturing tolerances are serving 20micrometers clearances. Slight dimensional errors can cause mechanicalfailure of the whole drill.

The case example component distributor valve was manufactured in OuluPMC facility using EOS M270 metal laser-sintering system. This machine isbased on powder bed fusion technology i.e. Direct Metal Laser-Sintering(DMLS) process as EOS calls that process. EOS M270 has building chamberwith size of 250 mm x 250 mm x 215 mm (9.85 x 9.85 x 8.5 in.). It isequipped with 200 W Yb-fibre laser and nitrogen shielding gas system. Inmanufacturing, standard set of parameters for this specific material, providedby EOS, was used. Creation of support structures as well as positioning ofparts on building platform was done by using Magics RP software byMaterialise. Tension bars were printed simultaneously with the distributor.

After printing, parts were removed from the chamber and support structureswere removed manually.

Distributor was printed from EOS MaragingSteel MS1 ultra high strengthsteel powder, composition presented in Table I. MS1 compositioncorresponds to US classification 18% Ni Maraging 300 and European EN1.2709, nominal composition presented for comparison also in Table I.Distributor valve was hardened in 490 C for 6 h after which the oxidizedsurface was cleaned by grinding in order to achieve demanded surfaceroughness 0,4. Final surface hardness was 53 HRC. Tension bars wereprinted simultaneously with the distributor. Tensile tests were performedaccording to ISO 6892-1 with as built and hardened tension bars.

Table I: Composition of the used EOS MaragingSteel MS1 powderand nominal composition of corresponding EN 1.2709 steel.

Fe Co Ni Mo Ti Al Cu Cr Mn Si C P SMS1 bal. 8,8 18 5,0 0,63 0,08 0,03 0,15 0,06 0,10 0,01 <0,01 0,01EN

1.2709bal. 8,5-

9,517-19

4,5-5,2

0,6-0,8

0,05-0,15

max0,5

max0,1

max0,1

max0,03

max0,01

max0,01

RESULTS AND DISCUSSION

In Figure 4 is presented on the left hand side a machined distributor, in themiddle printed distributor after hardening and on the right hand side printeddistributor after hardening and grinding. Tensile test results with as built andhardened tension bars are presented in Table II together with nominalmechanical strength values of type EN 1.2709 steel.

The printed distributor valve was tested in realistic drilling conditions up to150000 strokes in Sandvik Mining and Construction laboratory testbench,Figure 5. After the test the bearing distributor valve was visuallyinspected and no cracks, deformations or mechanical damage were observed.The test proved that AM technology itself is feasible for manufacturing loadbearing components for demanding conditions. However, conventionalmachining methods are still faster and cheaper, so next challenge with AMreal feasibility is the printing speed, material recipes and design methods.Real advantages of printing will come from, e.g., low volume spare parts,complex design possibilities and totally new type of material recipes.

Figure 4. On the left machined distributor, in the middle printed distributorafter hardening and on the right printed distributor after hardening andgrinding.

Table II: Tensile test results of the printed MS1 tension bars in as built condition and after age hardeningcompared to corresponding nominal values of EN 1.2709 steel.

Yield strengthMPa

Tensile strengthMPa

Elongation%

HardnessHRC

MS1, as built 1040 1150 15 33-37MS1, 490 C for 6h 1960 2010 3,5 53EN 1.2709,490 C for 6 h

1850 1950 55

Figure 5. Distributor valve test in laboratory drilling conditions

The digital paradigm, transfer from conventional machining to AM, will alsochange business logistics and create new business models and valuenetworks. It will bring a need for new models to optimise manufacturingassets across the supply chain. IBM Institute for Business Value estimated in2013 that the new software-defined supply chain will reduce the cost ofelectronics manufacturing by 23 %. According to Wohlers report 2013, costreduction from 5% to 66% can be achieved with utilization of additivemanufacturing. Especially big cost saving potential is in spare part business.Based on the calculation of IMB institute above, we can fairly assume thatcost savings caused by proper use of digitalisation in spare part businessescan be in the range of 10%.

Continuously decreasing product lifetimes, the increasing request for quicktime-to-market, and strict service level agreements have led to enormouscentralised warehouses. There can be thousands or even hundreds ofthousands spares in warehouses. For instance, Sandvik Mining andConstruction flies 1000 tonnes of spare parts annually around the globe.Spare parts are critical to assure operational conditions. However, capitalwhich has been bound on the critical spares is remarkable. In addition, as athumb rule, 80 % of the spare parts are slow movers. These parts areinfrequently asked for and count for less than 20 % of the sales, but OEMsare still obliged to deliver spare parts for equipment built in 70’s. Ondemand production near or at the assembly site would change businesslogistics remarkably. In addition, on demand production would liberate theinventory bound money for other purposes with higher ROI. This is validespecially in the end of product life time when no mould is availableanymore and in the end of tooling life time when it is no more feasible tobuild new tooling. Moreover, AM gives a possibility to continuous productimprovement by adjusting the design of spare parts and adding new featuresto it based on customer feedback and usage history of the spare part. Asophisticated decision tool for choosing the right business model fordifferent spare parts will give better margins for the equipment supplier andmore satisfaction for the end-user.

To demonstrate the digital design route, comprising of manufacturing,material and design, the case example was routed through an implementationof the ICME for AM adapting the PSPP approach as presented in Figure 1 toFigure 3. The derived methodology exploiting multiscale material modelingfor metal AM is presented in Figure 6. The approach links a metal AMprocess model (Process Structure) to microstructural model (Structure Properties) to case example component model under operating conditions(Properties Performance) to form a complete PSPP chain adopting ICMEprinciples. Further steps, such as digital product design including topologyoptimization can be introduced, and the digital design procedure can bedriven iteratively to systematically seek improvements and optimize productperformance via influencing the AM manufacturing process, material,material selection and its design, and critical product performance limitingmechanisms.

In current work, the process model relies on thermomechanical finiteelements and Calphad modeling for its inputs, a plain low alloy high strengthsteel is used as a basis for the investigation. A simplified model comprisingessentially of a single AM scan hatching is evaluated, and its properties arehierarchically upscaled in a multiscale manner to component scaleproperties. The results of the AM thermomechanical model, utilizingtabulated continuous cooling transformation (CCT) curves for phasetransformation kinetics in a mean field manner, are inputs to a structure –property problem. This problem is solved using a crystal plasticity modelcomprising of a microstructural morphology suited for the steel in question,and consists of a lath like (martensite – bainite like) microstructuralmorphology. The outcome of the crystal plasticity analysis is used viapolycrystalline homogenization to derive property profiles (true stress-straincurves) for component scale analysis, where the case example is subjected toimpact loading the component experiences during operation, and theprocessing routes which are found to produce significantly differingperformance outcomes are presented. This demonstrates the applicability ofthe methodology — the digital material, digital manufacturing and digitaldesign chain as an approach which can be exploited for superior productperformance and improvements in overall quality. The concept can beapplied to systematically develop more cost effective AM products andprocesses, and for example in working towards higher build rates andpushing the boundaries of currently limiting processing windows.

Figure 6. Performance driven digital design concept for manufacturing,material and design of metal additive manufacturing products.

A typical thermomechanical model outcome and temperature fields, SLM of15 layers of material, is presented in Figure 7. The model is developed forEOSINT M270 and all the model parameters are extracted from availablebuild process and system parameters, and a simplified unidirectional angledscanning strategy within a single hatch is considered, the hatch sizes beingsome millimetres in the different models that have been run. Conduction tobase plate and surrounding material and powder, heat transfer via top surfaceby convection and radiation are incorporated in the analysis. The resultsdemonstrate the thermal conditions during component build, and for

example, how the temperature histories at different locales during the scancan be greatly different e.g. near domain centers and edges.

Figure 7. Thermomechanical finite element modeling of metal AMmanufacturing of 15 layers using a model developed for EOSINT M270.

In order to investigate possible process outcomes and significance tomaterial properties and case example performance, numerous processparameter combinations from around the nominal EOSINT M270 processwere trialled, as presented in Figure 8. The isosurface plots correspond tolayer 15 towards the end of the simulated production run, and it can be seenthat even nominally fairly minor variations in process parameters causedrastically different thermal histories, on the other hand providing avenues toinfluence the AM manufacturing outcome via process parameter control anddeveloping novel scan strategies. Also, the results provide a clear indicationwhy constant scan parameters can lead to limited process stability andconsistency with respect to processing windows, since even in this aselementary as possible geometry the thermal solution is significantly

affected, and various build instabilities or problems in even reaching theactual build rate can be envisioned.

Typical temperature history of two material points one near the edge of ahatch and one near center are presented in Figure 9 to further illustrate thethermal history. First, there are significant differences in local temperaturehistory when a single set of parameters is used throughout the scan. Also, theinfluence of adjacent passes and layers (such as heat transfer from previousand subsequent layers) can be clearly seen. The cooling rates are high, ascommon for metal AM processes.

In order to link the thermomechanical process to resulting materialproperties, the CCT curve derived phase information was input to a crystalplasticity model, the principle of which is presented in Figure 10 along withthree case process results. The crystal plasticity model has been previouslydeveloped primarily for martensitic microstructures and as a result serves thecurrently considered microstructural range and built outcome indemonstrating the concept properly. True stress-strain curves were extracted,and the homogenized results used in simulating the response of the caseexample undergoing impact loading. Component behaviour of twosignificantly differing processes is presented in Figure 11, process laserpower and scan speed being the differentiating features between the twoprocesses, the differences in cooling rates and thermal energy are theprimary contributors to the observed component scale differences. The AMprocess model results are projected to the component finite element mesh byinterpolating over component thickness. As a result, the other selectedprocess results in a higher surface strength material and a greater propertygradient over thickness, which is seen to respond far more amicably to theimpact loading the case component is subjected to. The results provide botha demonstration what the digital manufacturing, digital material and digitaldesign concept can produce, as well as a straightforward case example howproducts with improved performance can be holistically designed,systematically seeking improvements from a vast range of AMmanufacturing process and material properties and parameters.

a) b)

c) d)

e) f)

g) h)g) h)

Figure 8. Effect of process parameters on temperature field after 15 layersfor: a) P=120 W, v=0.9 m/s, t=2.4 s, b) P=190 W, v=0.9 m/s, t=2.4 s, c)P=230 W, v=0.9 m/s, t=2.4 s, d) P=300 W, v=0.9 m/s, t=2.4 s, e) P=190 W,v=0.7 m/s, t=2.4 s, f) P=190 W, v=1.2 m/s, t=2.4 s, g) P=190 W, v=1.5 m/s,t=2.4 s, h) P=190 W, v=0.9 m/s, t=2.0 s, i) P=190 W, v=0.9 m/s, t=3.0 s, j)P=190 W, v=0.9 m/s, t=6.0 s (P = laser power, v = laser velocity, t = layertime).

Figure 9. Thermal history of material points near edge of scan hatching andat the center of material region, material points from layer 5 of a 15 layerbuild.

Figure 10. Crystal plasticity model used for determination of materialmechanical response.

i) j)

Figure 11. Component deformation response during the design performancecritical axial impact, utilizing the process parameters yielding the mostsuited mechanical properties and higher surface strength (left) (P = 190 W, v= 1.2 m/s) and a set with less favourable response and lower surface strength(right) (P = 230 W, v = 0.9 m/s).

CONCLUSIONS

The results of the work can be concluded as follows:

1. The printed distributor valve passed the realistic drillingcondition test without any damage. Rock drill is one of themost demanding mechanic-hydraulic components.

2. Digital material – approach linked a metal AM processmodel (Process Structure) to microstructural model(Structure Properties) to case example componentmodel under operating conditions (Properties Performance) to form a completed PSPP chain adoptingICME principles, demonstrating a digital design conceptfor metal AM.

3. Digital design procedure was illustrated to be able tosystematically seek improvements and optimize productperformance via influencing the AM manufacturingprocess, material, material selection and its design, andcritical product performance limiting mechanisms.

4. The development of digital design tools and application ofsimulation driven design is viewed as a very effectivemethodology to further the adaptation of AM producedparts, by improving their performance and AM processconsistency, increasing build rates while retaining qualityas well as decreasing production costs. The complexities ofAM processes increase the significance of establishing andverifying digital design methodologies.

5. Two processes differentiating with process laser power andscan speed resulted in different surface strength materials

providing both a demonstration what the digitalmanufacturing, digital material and digital design conceptcan produce, as well as a straightforward case examplehow products with improved performance can beholistically designed.

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