Conventional manufacturing is centered around the need to mass produce goods with consistent quality and at a low cost. One of the objectives of conventional manufacturing was to reduce the effect of variations in components, sensor/actuator faults, or local disruptions in the supply chain on the quality of the product and productivity of the process. However, such implementations are not capable of addressing globally distributed manufacturing processes or dynamic changes in the market and in customer preferences.
Design of manufacturing systems in the age of Industry 4.0 requires a new paradigm that considers the distributed and networked aspect of the manufacturing process and provides a mechanism for the seamless exchange of data between the physical and cyber components. While this implementation of such paradigm facilitates efficient data flows between different machines in the manufacturing process until now it did not deliver on the promise of Industry 4.0 as the integration with supply chain, big data analytics or enterprise-level planning modules is a challenging task.
AIM and SCOPE
Our aim is to investigate a scientifically grounded computational framework for decision-based adaptable concurrent design, operability and reconfiguration of cyber-physical supply chain activities in cloud manufacturing networks.
The project has five phases (1) investigation of the existing computational framework and adjust to support cyber-physical supply chain activities in cloud-based manufacturing; (2) automatize the computational framework; (3) test computational framework and verify usefulness of the results; (4) utilize the computational framework in the architecture for design of Cyber-Physical-Product-Service (CPPS) systems; and (5) platformization of the architecture.
The value that we bring in is dynamic management of cyber-physical supply chain by making it adaptable to dynamic changes in the market and in customer preferences.
By working with Prof. Schaefer and Dr Milisavljevic Syed the successful candidate will have the opportunity to learn how to (1) frame the problem and identify questions worthy of investigation in decision-based design of cyber-physical supply chain; (2) design software frameworks and implement them; (3) publish high quality research articles; and (4) create new knowledge in the context of cloud-based manufacturing and Industry 4.0.
You will work within a vibrant and rapidly growing community of researchers in the Division’s focus areas of Cloud-Based Design and Manufacturing. In addition, you will have the opportunity for internal and external collaborations. Internally, you will have the opportunity to collaborate with colleagues from our Virtual Engineering Centre (VEC), the leading UK centre for Virtual Engineering expertise, which delivers technology development, the latest research, training and knowledge transfer around the application and adoption of advanced modelling, simulation and 3D immersive visualisation in support of product design and manufacturing innovation. Externally, you will have the opportunity to collaborate with experts in decision-based design, data-driven design and cloud-based design within the International System Realization Partnership (ISRP).
The studentship will be funded by EPSRC DTA covering tuition fees at the UK/EU rate for 3 years of your PhD and an annual stipend for 3 years of £15,007 per annum. To be eligible for this funding the candidate should be a UK citizen or an EU citizen that meets the EPSRC’s eligibility criteria. Non-UK/EU students may apply for this project if they have funding to support their studies.
We are seeking candidates with a suitable degree in Design, Engineering, Computer Science/IT, Operational Research or a related subject. Experience in system design, and/or manufacturing is preferred, and digital technologies are required, as are strong communication and team working skills.
HOW TO APPLY
Please apply through the University of Liverpool’s online system https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/
with a full Curriculum Vitae, covering letter, and contact details for at least two academic references