20/06/2019
The Human Resources Strategy for Researchers
Marie Skłodowska-Curie Actions

Phd scholarship in the field of risk-based scheduling in the manufacturing and re-manufacturing of turbine blades


  • ORGANISATION/COMPANY
    Politecnico di Milano
  • RESEARCH FIELD
    EngineeringIndustrial engineering
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    30/07/2019 12:00 - Europe/Athens
  • LOCATION
    Italy › MILANO
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    40
  • OFFER STARTING DATE
    01/10/2019
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / Marie Skłodowska-Curie Actions
  • MARIE CURIE GRANT AGREEMENT NUMBER
    814225

The Manufacturing and Production Systems Research Line of the Department of Mechanical Engineering (https://www.mecc.polimi.it/nc/us/) - Politecnico di Milano (https://www.polimi.it/en/), has an open PhD position in the field of RISK-BASED SCHEDULING IN THE MANUFACTURING AND RE-MANUFACTURING OF TURBINE BLADES.

The Manufacturing and Production Systems Research Line performs research in the design and management of manufacturing systems which are combined with the most advanced methodologies for performance evaluation, planning and scheduling under uncertainty, simulation, and optimization.

The PhD project is carried out in the framework of the Horizon 2020 MSCA Innovative Training Network DIGIMAN4.0 “DIGItal MANufacturing Technologies for Zero-defect Industry 4.0 Production”. Please look at the project website (www.digiman4-0.mek.dtu.dk/) before reading further.

This PhD project is related to the Early Stage Researcher (ESR) position no.11 of the DIGIMAN4.0 project. The candidate will be enrolled within the PhD Programme in Mechanical Engineering at Politecnico di Milano, within a 3-year path. Additional rules and regulations can be found here https://www.mecc.polimi.it/us/phd/organisation/ and here http://www.dottorato.polimi.it/carriera-dottorandi/iniziare-il-dottorato/ (annual evaluations, mandatory ECTS, etc).

Among the partners involved in the network, this position involves a direct collaboration in particular with Ansaldo Energia S.p.A. (https://www.ansaldoenergia.com/), a leading international player in the power generation industry, active as full service provider with a broad portfolio on heavy duty gas turbines offering complete maintenance solutions on power generation rotating equipment and plants, built both by itself or by other OEMs.

Background

Production scheduling in industry needs to cope more than often with the occurrence of uncertainty, incomplete information and unexpected events that may stem from a wide range of sources, both internal and external. The estimation of the duration of production activities could be inaccurate, as well as their resource needs, the availability of machines, workers - or production resources in general - could vary, the supplying of raw materials or work-in-progress products could be late in relation to the scheduled time, new activities like rush orders or reworks could need to be executed with a higher priority . Hence, robust scheduling approaches have been addressed, aiming at protecting the performance of a schedule by avoiding or mitigating the impact of uncertain events

Responsibilities and objectives

Scope of this project is the design and development of scheduling approaches able to manage the intrinsic uncertainty in the manufacturing and remanufacturing of blades for gas turbines devoted to production of energy. Specifically, the approaches are focused on the re-manufacturing of blades during the maintenance and/or refurbishing of the turbines.

Being one of the most expensive parts in a gas turbine for energy productions, high temperature blades are valuable products to be remanufactured after a first use cycle or during the maintenance of power plants. The blades of the turbines under maintenance are disassembled from the rotors and brought to the manufacturing plant to be inspected. Blades that are considered good to be re-used are scheduled to be re-manufactured and be back on the rotor. Missing blades must be specifically manufactured to be able to complete the number of blades needed for each rotor.

 

The PhD project will have the following objectives:

  1. Model the uncertainty affecting the process, specifically, the occurrence of the need of rework activities, the probability of blades to be rejected during the re-manufacturing process, etc.
  2. Develop a risk-based approach for the scheduling of the re-manufacturing activities of blades. The aim of the scheduling approach will be at minimizing the risk associated to not delivering the refurbished turbine in time. Specific risk measures will be used to drive the scheduling approach (e.g., conditional value-at-risk, etc.
  3. Fit the proposed approaches in the planning and scheduling system architecture with the requirements at Ansaldo Energia, taking into consideration the available data, the scheduling cycles, the decisions to be taken, etc.
  4. Build and validate a demonstrator showing the benefits of this system in a real  turbine manufacturing and re-manufacturing environment at Ansaldo Energia.

Benefits

The selected candidate will be appointed a temporary contract for 36 months, to be renewed annually; salary will be in line with the funding schemes of MSCA action, and in accordance with Italian rules and regulations within this regard and Country specific requirements, as stated in the Grant Agreement and Guide for Applicants. Monthly salary (living allowance + mobility allowance) will be of approx. 4.000€ (gross amount), allocated following Italian specific contract conditions for MSCA candidates. Family allowance will be granted upon specific conditions.

Eligibility criteria

At the time of recruitment, the Early Stage Researcher (ESR) must not have resided or carried out his/her main activity (work, studies, etc.) in Italy for more than 12 months in the 3 years immediately prior to his/her recruitment under the project (July 2019). Eligible candidates must be, at the time of the recruitment, in the first four years of their research career and have not been awarded a doctoral degree.

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the PhD Programme of Politecnico di Milano.

In addition to a Master of Science, candidates are required to present an English Language Certification, complying with the rules and regulations of the PhD School of Politecnico di Milano, as stated in page five of the following document http://www.dottorato.polimi.it/fileadmin/files/dottorato/concorso35/Bando_ENG_XXXV.pdf

Selection process

The assessment of the applicants will be made by Prof. Marcello Urgo, Marcello Colledani, Massimiliano Annoni. For additional information please contact Prof. Marcello Urgo (marcello.urgo@polimi.it)

Additional comments

Politecnico di Milano is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

The Department of Mechanical Engineering is currently ranked 7th in the world (QS World University Rankings, Mechanical, Aeronautical and Manufacturing Engineering)

Required Research Experiences

  • RESEARCH FIELD
    EngineeringIndustrial engineering
  • YEARS OF RESEARCH EXPERIENCE
    1 - 4

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Engineering: Master Degree or equivalent
  • REQUIRED LANGUAGES
    ENGLISH: Excellent

Skills/Qualifications

Candidates should have a MSc Degree (120 ECTS points) or a similar degree with an academic-level equivalent to a Master of Science (5 years minimum duration Bachelor + Master).

  • MSc in Mechanical Engineering, Computer Science or similar;

  • Strong background in mechanical engineering and computer science;

  • Knowledge in the field of scheduling approaches and algorithms, stochastic scheduling, Markov Chains, machine learning;

  • Knowledge and experience with computer programming using C++, Python, AI frameworks (e.g., tensorflow);

  • Knowledge and experience in the field of production planning and scheduling in complex industrial environments;

  • Strong commitment to complex research activities and the development of advanced optimization approaches;

  • Ability to work independently, to plan and carry out complicated tasks, and to be a part of a large, dynamic group;

  • Excellent communication skills in English, both written and spoken;

Specific Requirements

Applications must be submitted as one PDF file containing all materials to be given consideration.

To apply, send an e-mail with title "DIGIMAN-APPLICATION" to marcello.urgo@polimi.it and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter);
  • Curriculum vitae;
  • Grade transcripts and BSc/MSc diploma.

A conference call will be organized with the candidates to:

  • Discuss about their CV, skills and experiences;
  • Assess their communication skills in English;
  • Discuss about the research/organisational topics that will be brought to their attention in form of scientific papers or similar during the call.

Candidates may apply prior to obtaining their master's degree but cannot begin before having received it. Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

Map Information

Job Work Location Personal Assistance locations
Work location(s)
1 position(s) available at
Politecnico di Milano
Italy
Lombardia
MILANO
20156
Via La Masa, 1

EURAXESS offer ID: 419639

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