About the Project
Brazing is a well-established manufacturing process for a range of different safety critical components, however, a number steps are still operator dependent. Of particular criticality is the application of the brazing consumable, typically in a paste or wire form, which is used to form the joint. This requires the use of a skilled operator to correctly apply the consumable for each joint, which is a repetitive and time-consuming activity. The use process digitalisation to optimise the process and consumable application (creating greater production control) could result in significant improvements in process repeatability and robustness.
Many industrial manufacturing companies are driven by the desire for automation and smart manufacturing into the fourth industrial revolution – also referred to as Industry 4.0 – through automated and digital process cutting-edge technology such as the Industrial Internet of Things. Also, at the forefront of robotics is the idea of a robot capable of safe, collaborative working with operators to perform tasks across the process.
This research aims to study and develop an algorithm for human-robot learning control for collaborative output tasks. Such human-robot learning control needs to satisfy two cases:
• The desired output is directly available to the robot
• The robot infers the desired output from the human-achieved output
Therefore, the second challenge for this research is to develop a secure methodology to systematically digitalise a process that is typically very heavily operator dependent. It will be necessary to design robust, safe and secure hardware and software modules, which can be applied to the process to facilitate productivity improvements via the use of robotics. The overall objective is to develop an automated and repeatable digitalised process for the manufacture of safety critical components.
Developing a framework around capturing process data, part geometry and handling requirements, securely transferring this data to a service platform (i.e. a Cloud), and then performing data analytics to correlate part performance will be required. This will enable manufacturing companies to minimise downtime, reduce human – process errors, and decrease maintenance costs. Implementation of the framework will result in a more competitive market by providing more efficient solutions to the customer.
About Industrial Sponsor
TWI is a world leading research and technology organisation. Over 800 staff give impartial technical support in welding, joining, materials science, structural integrity, NDT, surfacing and packaging. Services include generic research, confidential R&D, technical information, technology transfer, training and qualification.
NSIRC is a state-of-the-art postgraduate engineering facility established and managed by structural integrity specialist TWI, working closely with lead academic partner Brunel University, top UK and International Universities and a number of leading industrial partners. NSIRC aims to deliver cutting edge research and highly qualified personnel to its key industrial partners.
Lancaster University is a strong and dynamic university with a very highly regarded Engineering Department. In the 2014 Research Excellence Framework, 91% of research quality and 100% of impact was assessed as being internationally excellent and world leading. Lancaster’s approach to interdisciplinary collaboration means that it has pre-eminent capacity and capability for the integration of Engineering with expertise in the areas of data science, autonomous and learning systems, intelligent automation, materials science and cyber security. The University is developing an ambitious growth plan for Engineering, including investment in staff, doctoral students, equipment and a new building focussed on research themes including Digital and Advanced Manufacturing. Lancaster is the current Times and Sunday Times University of the Year.
Candidates should have a relevant degree at 2.1 minimum, or an equivalent overseas degree. Candidates with suitable work experience and strong capacity in numerical modelling and experimental skills are particularly welcome to apply. Overseas applicants should also submit IELTS results (minimum 6.5) if applicable.
Tasks according to the type of project, typically involve:
• Knowledge and practical experience of computer operating systems, hardware and software
• knowledge of engineering science and technology
• analysing user requirements
• writing and testing code, refining and rewriting it as necessary
• writing systems to control the scheduling of jobs or to control the access allowed to users or remote systems
• integrating existing software products and getting incompatible platforms to work together
• maths knowledge
• analytical thinking skills
• design skills
• the ability to work well with others
• to be flexible and open to change
• continually updating technical knowledge and skills by attending in-house and external courses, reading manuals and accessing new applications.
For further information, please contact Dr Yingtao Tian ([Email Address Removed] )
Formal applications should be made via the Postgraduate Admissions Portal of Lancaster University.
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