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PhD student opportunity in Human-robot cooperation for hybrid assembly systems

26/01/2017

Dr Yan Jin

Yan Jin
Senior lecturer

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Research project will be linked to i-AMS on robotics and smart manufacturing

Title: Human-robot cooperation for hybrid assembly systems

Project background

Facing the fierce competition, manufacturers are looking for sustainable and flexible solutions to meet customers’ ever increasing demand towards high variety, high quality and low cost. Recent research shows that human robot cooperation will form an effective partnership which offers enhanced productivity and flexibility. Robot is good at repetitive tasks but not excel in recognition and decision, while human operators have great recognition and reasoning ability but lack of precision and consistency. Combining the merits from both parties will maximise the system efficiency and adaptability. For this aim, this project is to develop a human-robot cooperation method for hybrid assembly systems for future factory of aircraft production. 

Project Aim

The overall aim of this project is to design a human-robot cooperated production line for aircraft assembly. The objectives are listed as follows.

  • Comprehend existing manual processes in aircraft assembly
  • Propose an allocation method for assigning suitable operations and co-operations to both human and robot
  • Design a decision making strategy in between human and robot
  • Develop a compliance control method to implement human robot collaboration
  • Develop a demonstrator via 3D simulation and physical experiments
  • Conduct cost/time benefit analysis to compare with current processes

Requirements

Applicants should hold or expect to hold an MEng 1st class or 2.1 Hons degree (or equivalent) in engineering. Knowledge of robot programming, control and metrology is considered advantageous. 

The studentship covers the full university fees and includes an income of up to £18,500 per annum (comprising a £14,000 stipend, a potential £3,000 top-up and the opportunity to undertake teaching and demonstration duties to earn a further £1,500 per annum). The top-up is available, dependent on academic performance.  

Key transferable skills that will be developed during the PhD:

Apart from the help from supervisors, the student will also be supported by process/automation engineers from partner companies. Through the project, the researcher will gain the following highly sought-after skills:

-       Innovative thinking in design the human-robot assembly system

-       Robot control method

-       Discrete event simulation software

-       Method for cost benefit analysis

-       Experimental methods

-       Project and time management training to ensure milestones of the project are delivered.

-       Effective dissemination of research findings through presentation at international conferences and publication in high quality technical journals.

Interpersonal skills within a multidisciplinary team including academics and industrialists

First/Lead Supervisor and their contact details

Dr Yan Jin (Associate Professor/Senior Lecturer), Email: y.jin@qub.ac.uk Tel: +44 (0)28 9097 4102

Other Supervisors

Prof. Adrian Murphy, Prof. Mark Price

Pioneer Research Programmes (PRPs)

Enable researchers to form novel interdisciplinary collaborations to address emerging societal challenges.

The project will be undertaken within the newly created PRP in ‘Intelligent Autonomous Manufacturing Systems’. The PRP is worth up to £1.06 million over three years and includes 9 PhD studentships and funds to develop links with key centres in Europe, US and China. The PRP is design to provide a stimulating environment for the training of the next generation of post-doctoral graduates, directly feeding industry with high quality engineers. The PRP brings together complementary expertise to provide a training programme to develop technical knowledge and professional skills, aimed at preparing the students for their career as future engineering leaders. It also provides a supportive, team environment to undertake research and a wide network of industrial and academic collaborators, enabling students to understand how industry foresees its future engineering and technology needs. 

Dr Yan Jin (Associate Professor/Senior Lecturer), Email: y.jin@qub.ac.uk Tel: +44 (0)28 9097 4102

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