Sopron, Hungary

University of Sopron

PhD in Wood Sciences and Technologies - Cziraki Jozsef Doctoral School

Smart Manufacturing refers to the fully integrated, collaborative manufacturing systems that respond in real-time to meet changing demands and conditions in the smart factory, in the supply network, and in customer needs. It is the use of real-time data and cutting-edge technologies to support factories to make effective and accurate engineering decisions and create highly differentiated, cost-effective, and competitive products that match the market needs.

The Doctor of Philosophy (PhD.) Programme in Smart Manufacturing aims to provide students with a detailed understanding of each level of the manufacturing process, combining skills in mathematics, science, and business to prepare them in developing innovative ways of systems design and product production. The programme design focuses on providing fundamental knowledge as well as hands-on training in the curriculum. Students graduating from the programme will be versatile and well-equipped to derive valuable insights and make sound decisions. The programmes will also offer new pedagogical training to prepare research students with specialized and transferrable skills to cope with new manufacturing engineering settings.

A graduate of the PhD programme should be capable of conducting high-quality original research, creating new knowledge, showing valuable insights, and making a significant contribution to academia and the field.

Smart Manufacturing refers to the fully integrated, collaborative manufacturing systems that respond in real-time to meet changing demands and conditions in the smart factory, in the supply network, and in customer needs. It is the use of real-time data and cutting-edge technologies to support factories to make effective and accurate engineering decisions and create highly differentiated, cost-effective and competitive products that match the market needs.

To qualify for admission, applicants must meet all of the following requirements. Admission is selective and meeting these minimum requirements does not guarantee admission.

i. General Admission Requirements of the University

Applicants seeking admission to a master's degree programme should have obtained a bachelor’s degree from a recognized institution, or an approved equivalent qualification;

Applicants seeking admission to a doctoral degree programme should have obtained a bachelor’s degree with a proven record of outstanding performance from a recognized institution; or presented evidence of satisfactory work at the postgraduate level on a full-time basis for at least one year, or on a part-time basis for at least two years.

ii. English Language Admission Requirements

Applicants have to fulfil English Language requirements with one of the following proficiency attainments:

TOEFL-Revised paper-delivered test: 60 (total scores for Reading, Listening and Writing sections)

IELTS (Academic Module): Overall score: 6.5 and All sub-score: 5.5

* refers to the total score in one single attempt

Applicants are not required to present TOEFL or IELTS score if:

they obtained a bachelor's degree (or equivalent) from an institution where the medium of instruction was English.

This programme is for HKUST(Guangzhou) Pilot Scheme Admission.

For more programme information, please refer to pg.ust.hk/programmes.

Admissions Option 2

On successful completion of the PhD programme, graduates will be able to:

Model a manufacturing system in order to create a formal process for characterizing manufacturing performance;

Demonstrate a broad-based knowledge and process capability of various smart manufacturing technologies and production processes;

Find optimal solutions to models of manufacturing systems in specific disciplinary contexts;

Demonstrate critical thinking and analytical skills and apply them to manufacturing engineering;

Conduct high-quality original research independently in areas of manufacturing and systems engineering and provide a substantial scientific contribution to the discipline;

Translate and transform fundamental research insights effectively in academic fields and industry; and

Apply cross-disciplinary knowledge and skills in data analytics, real-time sensing, and optimal planning to improve manufacturing process capabilities.

Program Outcome

Master

Engineering Studies

Manufacturing

Located at the Clear Water Bay of Hong Kong, the Hong Kong University of Science and Technology (HKUST) is a research-focused institution that ranks first among top young universities in the world (Times Higher Education Young University Rankings, 2020). With an international outlook and global reputation, the university aims to be a leading university, both locally and internationally, through excellence in teaching and research.

With the unprecedented demand for high-end talent in support of the development of Hong Kong and the world, The Hong Kong University of Science and Technology (Guangzhou) (HKUST(GZ)) will be set up in Nansha, south of Guangzhou, to synergize with its Clear Water Bay (CWB) counterpart, nurturing talents and facilitating collaboration amongst Hong Kong, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and beyond on education, research and knowledge transfer.

PhD in Smart Manufacturing

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PhD in Wood Sciences and Technologies - Cziraki Jozsef Doctoral School