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R&D Engineer Manufacturing Virtualization

Date:  04-Aug-2022
Location: 

ROMA, Italy

Type of work:  On site

Predictive Modelling Digital Engineer
(Manufacturing Virtualization)

 

Position Snapshot

  • Type of Contract: Permanent
  • Full-time
  • Location: Rome
  •  

Purpose and Content of the Role

  • To contribute to the virtualization of R&D processes, with special focus on industrialization and manufacturing, through the adoption of predictive models, both physics-based (e.g. based on FEA technologies) and data-driven (e.g. based on big data and analytics, as well as ML \ AI technologies).
  • To enable mechanism understanding in other R&D Functions in the Technical Center.
  • To support Tire Development and Manufacturing Engineers in the Technical Center in the application of developed models, gathering feedback and requirements to be routed in the solution development process.
  • To work strictly in contact with other team-mates in charge of Digital Engineering Solutions (FE Analysts  \ Data Scientists  \ Digital Twin Engineers  \ Tire and Vehicle Modelling \ Driver-in-the-loop Simulation Engineers).
  • In particular, she \ he will contribute to the Manufacturing Virtualization projects (defined by specific Statements of Work) in contact with R&D Digital Engineering Team, as well as 3rd Party Consultants and Project Managers, focusing her \ his activities on:
    • Supporting development of:
      • FE Simulations.
      • Data driven predictors and algorithms.
      • automatic pre-processor and post-processor integrated to Bridgestone proprietary Virtual Development Platform.
    • Generating and maintaining a set of validation cases for each Predictive Model.
    • Coordinating -when required- the activities of involved 3rd Party Consultants and Project Managers.

 

 

Responsibilities \ Main Tasks

  • Cooperate with other Digital Engineering team members, to:
  • Expand \ enhance Predictive Modelling capabilities (both physics-based and data-driven) of the Technical Center.
  • Design solutions leveraging data coming from FE simulations in combination with available experimental and field data, to feed data-driven Models.
  • Develop \ enhance advanced simulations and ML \ AI-based predictors, in the area of Tire Manufacturing (e.g., Curing, Building, Material Extrusion, Mixing).
  • Cooperate with other functions in the Technical Center, to:
  • Intercept their needs regarding the implementation, integration, operation, maintenance and support of Predictive Modelling Solutions.
  • Make the implemented solutions - based both on FE and Advanced Analytics technologies - extensively adopted, thanks to wide accessibility and ease of use for all stakeholders and \ or final users.
  • Validate implemented Predictive Models, by comparing their outcomes with relevant experimental results.
  • Enable the development of physical mechanism understanding through proper FE analysis and \ or data-driven analysis of available experimental \ simulated data.
  • Support focused pilots / trials on implemented Predictive Models, to secure validation \ acceptance by Stakeholders \ selected End Users, and enable transition to final scale-up.
  • Cooperate with other Technical Centers (i.e., Japan and US), as well as other business functions in Bridgestone EMIA Business Unit, to effectively share information, build common strategies and exploit synergies to enhance the simulation and predictive modelling capabilities of R&D area.

 

Her \ his activity will be led by:

  • Bridgestone Essence, through the four foundational behaviors:
  • Seijitsu-Kyocho (Integrity and Teamwork).
  • Shinshu-Dokuso (Creative Pioneering).
  • Genbutsu-Genba (Decision-Making Based on Verified, On-Site Observations).
  • Jukuryo-Danko (Decisive Action after Thorough Planning).
  • Bridgestone Sustainability Values, through E8 Commitment encompassing the eight key values:

 

 

 

Competences & Skills

  • Analytical Skills  \ Creativity
  • Possessing a very good knowledge of mechanics, paired with a proven ability to think out-of-the-box.
  • Proactive and open to propose original and appropriate analysis methodologies to shortly catch and describe tire properties and criticalities, with special focus on the industrialization and manufacturing processes.
  • Attitude
  • Open-minded independent and able to create links with other functions.
  • Able to implement complex FE-based models autonomously.
  • Able to coordinate implementation of advanced analytics models and algorithms.
  • Ready to provide the rationale underlying his \ her choices of a particular solution.
  • Technical Background
  • Strong knowledge of Continuum Mechanics (Solid Mechanics, Applied and Theoretical).
  • Finite Element Theory (Implicit and Explicit Codes).
  • Abaqus knowledge is required.
  • LS-Dyna knowledge is an asset.
  • Fortran \ Python Scripting for Abaqus is a plus.
  • HyperWorks Suite (HyperMesh and HyperView at least, Tcl for HyperWorks is a plus).
  • Knowledge of Tire Mechanics is an asset.
  • Basic knowledge of Advanced Analytics and Machine Learning core concepts.
  • Basic Linux bash shell commands knowledge.
  • MS Office Suite (Excel, Power Point and Project at least).
  • Familiarity with software development and version control Git.
  • Ability to work in an Agile process.
  • Familiarity with Atlassian suite (JIRA, Confluence and BitBucket).

 

  • Other Skills
  • Very Good written and verbal communication in English
  • Able to prepare and execute both technical and executive presentations and ready to represent her \ his argumentations in front of a diverse and multicultural audience.
  • Able to plan proper project schedule, spanning over 16+ weeks.
  • Able to carry on her \ his projects independently.
  • Possessing strong communication capabilities.
  • Proactive in providing new ideas on how to apply his \ her capabilities in Bridgestone environment.
  • Ready to continuously learn (in a kaizen \ continuous improvement approach).

 

Education \ Experience

  • Minimum MS degree in Mechanical \ Aerospace Engineering (or similar degrees in Industrial Area) with a specific focus on numerical analysis.
  • Minimum 2 years working experience in similar roles (FE Stress Analysis).
  • Automotive experience \ knowledge in the field of tire manufacturing is a plus.

 

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