Marketplaces and Interoperability - Data Creation, Curation and Exploitation. The View of a Software Owner

Transcription

1 Marketplaces and Interoperability - Data Creation, Curation and Exploitation The View of a Software Owner

2 1. Background - Introduction to Thermo-Calc 2. Our Data - Creation - Curation - Exploitation 3. Our view on data on marketplaces - Current mega-trends - Disruptive changes in other areas - Software as a Service, data as a service - Marketplaces and Simulation/Integration platforms - Thermo-Calc Products on a Marketplace 4. Conclusion

3 Thermo-Calc: Who we are? Thermo-Calc is like a small version of EMMC Taken from EMMC roadmap Thermo-Calc!

4 Thermo-Calc activities Thermo-Calc compared to EMMC Thermo-Calc activities Taken from EMMC roadmap Thermo-Calc activities Thermo-Calc activities Thermo-Calc activities Manufacturers Translators Software Owners Modellers Validation

5 Mole fraction Thermo-Calc: What do we do? TIME = Hattori et al. (2006) 1523K, 48hr Ru W CELL #1 Phase diagrams Distance, m Diffusion Mainy for metals, also oxides Precipitation

6 Thermo-Calc History First graphical user interface First version of Thermo-Calc First external Thermo-Calc user First external DICTRA user First external PRISMA user New Generation of Thermo-Calc Thermo-Calc for Mac OS X Properties model calculator Release of TC Python Currently ~45 employees Thermo-Calc Software Inc. (USA) Thermo-Calc Software AB The Foundation Development of Thermo-Calc starts at KTH in Stockholm

7 Thermo-Calc Customers Academia (material science, mech. engineering,..) Governmental research labs Industry o o o o Steel and metal producing companies Manufacturing companies o Automotive o Electronics and semi-conductors o Aerospace & defense o Industrial equipment o Naval, maritime o Consumer goods Energy & environment Consulting services

8 The Thermo-Calc Family Regular training sessions, user-group meetings, presence at conferences, customer visits, Close contact to customers through network of representatives.

9 1. Background - Introduction to Thermo-Calc 2. Our Data - Creation - Curation - Exploitation 3. Our view on data on marketplaces - Current mega-trends - Disruptive changes in other areas - Software as a Service, data as a service - Marketplaces and Simulation/Integration platforms - Thermo-Calc Products on a Marketplace 4. Conclusion

10 Thermo-Calc Product Portfolio Software maintenance and support Training courses Project work

11 The CALPHAD Method T=700K Liquid α + β G α (x) T = x A G α + x B G α + RT(x A lnx A +x B +lnx B ) + x A x B L E G α (T) x = A + BT + CTln(T) + ET -1 + FT 2 +

12 The key to CALPHAD s success: EXTRAPOLATION MnO x SrO T=1200C LaO 1.5

13 The key to CALPHAD s success: Model system Fe-C + Mn Real system: Fe-C + Mn + Si+P+S+O+N+Ca+Al

14 Assessment: Example Al-Li

15 Example Al-Li B. Hallstedt and O. Kim, 2007, Int. J. Mat. Res. 98(10): Phase diagram data Metastable PD EMF data (enthalpy of formation) 0 K Lattice stability Mixing enthalpy, activity data, chem. potential (Ab Initio)Well structured repository for experimental and ab initio data would be very useful and cut database development times. 6 phases, >1000 experiments reproduced with 26 parameters

16 The CALPHAD Method Thermochemical: Enthalpy Entropy Heat capacity Activity Ab Initio Calculations: Lattice Stabilities Heat capacity ONLY possibility for metastable phases! Phase equilibria: Liquidus Solidus Phase boundary Gibbs Energy of Individual Phases G m a = f (x, T, P) Applications

17 CALPHAD Database purely from Ab-Initio? Phase diagram data Metastable PD EMF data (enthalpy of formation) 0 K Lattice stability (Ab Initio) Mixing enthalpy, activity data, chem. potential

18 CALPHAD Database purely from Ab-Initio? Very useful additional data, BUT: Uncertainties in DFT models themselves: Simplifications required to solve the Schrödinger Equation. Calculation of mechanically unstable phases not possible. Uncertainties in temperature dependence: magnetic contribution, electronic contribution, harmonics, anharmonics, Large cell sizes required for disordered multicomponent phases How to describe the liquid phase? Also: current CALPHAD databases are not valid to 0 K. 3 rd Generation Database Project.

19 Data curation example: The Steel Database Ar Al B C Ca Ce Co Cr Cu Fe H Mg Mn Mo N Nb Ni O P S Si Ta Ti V W Y Zn Zr Also: Ni, Al, Mg, Ti/Al, Cu, HEA, Noble Metals, Solder, Oxide & Ceramics, etc

20 255 done (80%) 255 done (8%) 77 done (0.4 %) Data curation example: The Steel Database Ar Al B C Ca Ce Co Cr Cu Fe H Mg Mn Mo N Nb Ni O P S Si Ta Ti V W Y Zn Zr Also: Ni, Al, Mg, Ti/Al, Cu, HEA, Noble Metals, Solder, Oxide & Ceramics, etc

21 Carbon content (%) Carburization 4,8 %C 4,4 4,0 3,6 3,2 2,8 2,4 2,0 1,6 1,2 0,8 0,4 0,0 Fe-12Cr-2Ni-2Mo-0.12C at 955 C: profil carbone calculé en fin d'enrichissement Calculated carbon profile at the end of the enrichment step profil carbone calculé après 3h de diffusion Calculated carbon profile after 3h of diffusion Turpin et al., Met. Trans. A 36(2005), pp µm 900 Distance from surface ( m) 2.60 m Ball screw for the Airbus A380 aircraft: a martensitic as carburized stainless steel by Aubert & Duval

22 Data Exploitation: indirect PRISMA DICTRA & Phase Field Input for database API, e.g. TC-Python

23 What standardization did we need to do? Definition of database format: the TDB file, unencrypted, text format, even if it can be used by competitors! Decision on models to be used: sublattice model, ordering models Use these even if you think there might be better ones! Decision on description of pure elements (SGTE Database) and live with it! Heat capacity of Manganese Heat capacity of Manganese Current databases (SGTE) 3 rd Generation Database

24 1. Background - Introduction to Thermo-Calc 2. Our Data - Creation - Curation - Exploitation 3. Our view on data on marketplaces - Current mega-trends - Disruptive changes in other areas - Software as a Service, data as a service - Marketplaces and Simulation/Integration platforms - Thermo-Calc Products on a Marketplace 4. Conclusion

25 Music industry evolution

26 Blockbuster vs NETFLIX vs

27 Current trends in technology Taken from FORBES Many are relevant to us and will change our business Trend 1: The increasing datafication of our lives Trend 2: The Internet of Things (IoT), everyday devices are becoming more smart Trend 3: Exponential growth in computing power is fueling massive tech advances Trend 4: The incredible rise of artificial intelligence (AI) Trend 5: The unstoppable freight train that is automation Trend 6: 3D printing opens up amazing opportunities for manufacturers Trend 7: We re interacting with technology in very different ways anything as a service Trend 8: Blockchains: An invention that could change our world Trend 9: Platforms are the way forward for businesses

28 Current trends in technology Taken from FORBES Many are relevant to us and will change our business Trend 1: The increasing datafication of our lives Trend 2: The Internet of Things (IoT), everyday devices are becoming more smart Trend 3: Exponential growth in computing power is fueling massive tech advances Trend 4: The incredible rise of artificial intelligence (AI) Trend 5: The unstoppable freight train that is automation Trend 6: 3D printing opens up amazing opportunities for manufacturers Trend 7: We re interacting with technology in very different ways anything as a service Trend 8: Blockchains: An invention that could change our world Trend 9: Platforms are the way forward for businesses

29 XaaS: anything as a service Between 2016 and 2020, the XaaS market is forecast to grow by 40 per cent each year: On-demand, in the cloud, accessible everywhere and anywhere. But: Some customers will never accept a cloud solution (e.g. military, AM community scared of data being leaked, etc ) But: Cloud computing often driven by requirement for expensive hardware, e.g. servers (CRM) or supercomputers (e.g. CFD). Not the case for Thermo-Calc.

30 Conclusions CALPHAD type data is considered a pragmatic way to bridge the dimension gap between the atom and the part. Data curation is permanent and never ending job. Good experimental data is (still!) key. For us, marketplace would be useful for collection of Well-structured experimental data. Assessed databases in TDB format from publications. Ab-initio data on lattice stability. Various small codes and models. More information Contact nicholas@thermocalc.com