“Up to 80% of the work done in an engineering department is identical or very similar to work done previously” as stated in an Arthur D. Little report [1,2]. due to redundant work done in engineering departments has been estimated to be as high as 80% , imposing significant costs on industry (estimated at €2m per year for one manufacturing business of a thousand knowledge workers [2,3]). (Hold that thought!).
The FormPlanet Open Innovation Test Bed (OITB) has established itself as an ecosystem around the value chain of the sheet metals forming industry. It has brought together a consortium of 18 industry and research partners across Europe providing a complete solution, or ‘One-stop shop’, for the metals forming industry. Naturally, a wealth of materials information has spun out of this project including ground-breaking work in Hot Forming processes, Hydrogen Embrittlement, Stepwise Modelling, Forming Limit Diagrams and prediction of Edge-Cracking, to name a few.
Ansys’ role in the FormPlanet OITB is to bring together this multitude of information in one place to deliver effective materials information management using a systematic approach supported by a mature software solution, Ansys Granta MI. This system is used by leading manufacturing industries to manage the diverse data sets required to define materials and processes in an engineering business and enable data to be linked, shared, controlled, and build material intelligence. Implementation of Ansys Granta MI for the FormPlanet OITB presents the partners with an effortless way to:
- Capture and manage data in a secure and traceable way for findability and formal reporting
- Generate and/or access design and simulation ready data for product development.
- Facilitate digital twin applications.
In this article, we aim to explain the importance of Materials Information Management for digital transformation and introduce the FormPlanet Database System which is helping partners and wider industry to achieve this goal.
Why Material’s Information Matters?
Behind the scenes in any engineering and science industry, there are many measures taken to reach an optimised part, and consistency of parts across sites and/or suppliers. Repeatability and reproducibility require harmonized characterisation methodologies and batch control before and after manufacturing. Optimisation requires capture of data over time, linking multiple scales from microstructure-process-property-performance (SPPP). Table 1 presents a set of questions that typically arise during a product development process emphasising that materials information is centric in product development with significant commercial impact .
Table 1: Example questions that a materials information management system addresses 
Materials information management is intrinsic to the facilitation of digital twins. The aim of a digital twin is to represent a physical asset with a complete digital model and simulation throughout its lifecycle to support design and decision-making. As such it accelerates the process to answer the above raised questions in Table 1 by breaking down boundaries surrounding research and product innovation. Granta MI ensures that the input data is accurate, capturing metadata for uncertainty and quality, and brings back the virtual result to create a larger, more extensive database than could be accomplished by physical testing alone.
FormPlanet FAIR Data Management
The FormPlanet Test Bed has established a central materials information management database system powered by Granta MI on characterization for forming processes by curating data from the partners’ characterisation facilities. The FormPlanet database system is tailored for the metal forming industry.
Granta MI manages various types of information to ensure full traceability for a product across the life cycle of a product such as Materials, Processes and Manufacturing pedigree, Specifications, Test Equipment and Test Set-up details, Suppliers, Modelling and Simulation pedigree, links to publications, among others. The data model types extend from text (including formatted material cards), numerical, functional (curves), tabular, images, and many more.
The data management best practices in combination with the software, schema, and interoperability/integration enablers, ensure FAIR requirements are met (findability, accessibility, interoperability, and reusability). For example, which equipment was used to measure the hydrogen content in specimens? Records in ‘Test Data: Diffusible Hydrogen’ has the answer and the equipment is hyperlinked to its own record. The relevant Test Equipment record has full details of the equipment (such as the name, make, model, serial number etc). Furthermore, the ‘Test Equipment record’ also has links directing the user to specific tests where the equipment was used. As such, the database can be exploited in the same way to also store and link supplier’s information, materials pedigree, specification values etc.
Data Flow – Data Curation from Test Data to Design Ready Data (example Diffusible Hydrogen)
Data Flow refers to the systematic approach to capture and link all the data produced, from data captured from test equipment through to design data formatted for a specific CAE tool, enabling comprehensive and repeatable analysis that can generate vital insight. Arriving at accurate Hydrogen Diffusion characterisation for modelling is critical in hot-stamping processes. Figure 2 shows an example of Data Flow developed with the University of Pisa and Letomec on ‘diffusible hydrogen’ where the objective was to determine the ‘critical hydrogen content’ as the threshold above which the material property, affected by the hydrogen content, drops below a specific value with respect to the hydrogen free condition (typically 30%).
Figure 2: The ‘One-Stop-Shop’: The FormPlanet Database System provides a rich resource of data, information and experience that is valuable for industries involved in sheet metal forming processes
The different types of records are explained:
- Test Data Record: Information from each test performed to a given materials specification, test methodology (including equipment information) and results, together from a Test Data Record. In this example we have several Test Data records for the Four Point Bending Test (FPBT) and Slow Strain Rate Tests (SSRT) conducted on hydrogen charged specimens. The key information in these records is the resulting graph of ‘stress at failure vs hydrogen content’ for a material.
- Statistical Data Record: A Statistical Data record stores key results from all Test Data records related to each type of test. Furthermore, links to individual Test Data records is also provided for traceability (for example, if a user wishes to interrogate a specific Test Data record, then the user can click on the relevant link and access that specific Test Data record). In this example, we have two Statistical Data records each corresponding to its relevant test type (i.e., FPBT and SSRT).
- Design & Simulation Record: Test Data and Statistical Data records are processed to provide a designer or product developer with key information needed for their decision making and/or export to CAE tools for further processing. In this example, all the FPBT and SSRT tests are processed to provide the ‘critical level of hydrogen’ beyond which the material has a high risk of failure.
Figure 3: Dataflow – Test Data record curation to Statistical Data records of post-processed data, to generation of Design and Simulation records exportable to various CAE tools
Diverse Materials Information in One Place
Like the Design ready data on ‘Diffusible Hydrogen’, there is also Data Flow leading to simulation ready data. An example of simulation ready data is the work on ‘Stepwise Modelling (SMM)’ by Lulea Technological University that presents ‘Failure strain at Triaxiality’. These datasets can be integrated to plot a ‘Modified Mohr Coloumb curve’ to inform a Generalized Incremental Stress State Dependent Damage Model (GISSMO) forming model that is popularly used in the sheet metals forming industry processes.
As such, FormPlanet has several such innovative research work published by the different project partners. Although not exhaustive, Figure 4 shows an overview of the tests each partner have conducted during the FormPlanet project. Together, the FormPlanet Database System becomes a resource for FAIR data management, and a rich materials and process library for the metals forming industry where a user can ‘save time’ by accessing required information and thus, ‘save costs and time’ by avoiding duplication of testing.
Furthermore, as Granta MI directly integrates with computer-aided design (CAD), computer aided engineering (CAE) or simulation, and product lifecycle management (PLM) software, the ‘simulation ready data’ from FormPlanet can then be used to facilitate digital twin applications.
To conclude, the FormPlanet Open Innovation Test Bed has brought together a strong set of partners pioneering research on metals forming industry. Ansys’ role has been to present the work of the partners in a FAIR way using the Granta MI materials information management solution. Partners’ contributions are ready for design and simulation to encourage digital twin application for its use in the project and in the commercial life of the Test Bed after the project.
In January 2022, Ansys will release the ‘Ansys Forming’ solution for metal stamping. The solution will present an end-to-end workflow for the entire die process on a single platform. https://www.ansys.com/news-center/press-releases/10-14-21-ansys-will-transform-metal-stamping-through-launch-ansys-forming
 Bilello P., “What does a successful PLM implementation look like?”, PLM Innovation Conference, Munich, 2012
 Feldman S., Sherman C., “The High Cost of Not Finding Information”, IDC White Paper, 2001
 Warde S., Fairfull A., “The Business Case for Material Intelligence- The impact of materials information on productivity, innovation, cost and risk in the engineering enterprise”, Granta MI Business White Paper, 2020
The market-leading Ansys Granta products have been developed over 25 years to enable you to capture, safeguard and capitalize on your organization’s Material Intelligence. Ansys helps businesses digitalize their company’s materials knowledge, choose the right materials for their products, and provide resources for materials education.