Job opportunities

View All Vacancies

Post-Doctoral Research Associate (PDRA) RAMONA EPSRC project

Surrey Business School

Location:  Guildford
Salary:  £32,817 to £40,322
Fixed Term
Post Type:  Full Time
Advert Placed:  Monday 28 June 2021
Closing Date:  Wednesday 04 August 2021
Reference:  037021

We seek a post-doctoral research associate (PDRA) for the Business School with expertise in multi objective optimisation/mathematical modelling and knowledge of one or more of: supply chain, systems engineering, service design, cost modelling, process management, operations management or operations research. The position is part of an EPSRC cross-disciplinary research project titled Responsive Additive Manufacture to Overcome Natural and Attack-based disruption (RAMONA) led by Dr Gregory Gibbons (University of Warwick) with Co-Investigators Professor Parry from Surrey, Dr Philip Davies (Supply Chain - Henley), Prof. Carsten Maple & Dr Greg Epiphaniou (Cyber Security– Warwick), Professor MA Williams (Additive manufacture - Warwick). The University of Surrey and Henley Business School will develop the multi-objective optimisation for supply chain disruption theme of the project, with this PDRA taking a leadership of this part of the project.

BACKGROUND

We seek a researcher to be part of a new research project, named “Responsive Additive Manufacture to Overcome Natural and Attack-based disruption”  (RAMONA) funded through a Responsive Manufacturing research grant EP/V051040/1 from the Engineering and Physical Sciences Research Council (EPSRC).

Project summary: Disruption resilient manufacturing is becoming increasingly important, with the current COVID-19 pandemic bringing this to the fore. Whilst COVID-19 was a natural disaster, the increasing digitisation of supply chains and manufacturing processes means further widespread challenges with respect to malicious activity and cyber attacks that can cause significant disruption. Whilst the news suggests many of these take place on digital platforms or within financial or health institutions, there is growing evidence that cyber-physical systems, such as manufacturing, are becoming more regularly targeted and therefore subject to disruption. For instance, a recent Cisco (2017) report found that 28% of manufacturers across 13 countries suffered cyber-attacks that resulted in revenue loss, with this set to increase as digitisation of the manufacturing industry increases. Therefore, it is crucial to identify methods of both securing against and reconfiguring if needed the point of production within the supply network should a string within the supply network become compromised.

This research focuses specifically on additive manufacturing supply chains as part of a responsive manufacturing system, to address the significant security challenges within manufacturing supply chains to ensure greater levels of supply chain resilience for both UK and global manufacturing. In particular, this would address the call from Additive Manufacturing UKs (2017) UK National Strategy Report for AM, where they highlighted a critical challenge is to address security related challenges in AM production, with the importance of this increasing if production is to be distributed and responsive to emergent changes within the system, such as an adversary infiltrating elements of the supply chain.

To support such rapid reconfiguration of the manufacturing system across the supply network, our vision is to create a practicable methodology for manufacturing systems that can detect a threat and reconfigure themselves rapidly in the presence of an adversary. The work packages developed as part of this research further address the critical challenges outlined above and underpin our vision through the development of 'double lock' system, of physical hash on the product and digital hash on component files secured against a distributed ledger technology, that can be scaled across and tailored to different SC configurations, allowing manufacturing to be responsive to disruption and enable greater resilience and agility in UK manufacturing SCs. This proposal also considers both the current state of the art in academic research, and the fundamental needs and applied research from industry. This research is transformative as it meets the twin hurdle of academic rigour and industrial relevance.

To create tools and techniques for resilient additive manufacturing this research will address the following challenges:

- How to develop effective techniques to detect disruption;

- How to effectively and accurately analyse the disruption; and

- How to respond to disruption through reconfigured manufacture.

GOALS OF THE POSITION

Within the RAMONA project, this 30-month PDRA position, will concentrate on supporting the third work package described here.

WP3: Responsive additive manufacturing design, management and optimisation (addressing Research Objective 3 for the project).  

As defined in by our proposal, manufacturers responding to a disruption face a M-OOP (multi-objective optimisation problem). The research objective for this WP is therefore to develop and validate a M-OO method for AM enabled responsive manufacturing systems (RO3). To address RO3, this work package needs to first conduct preliminary qualitative research in tasks T3.1 and T3.2 before using the outputs of these tasks to inform the development of the multi objective optimisation method in T3.3. T3.1 develops a taxonomy for centralised and distributed AM system configurations from academic literature. T3.2. involves case study research undertaken with industrial project partners, providing insights into distributed AM design, process and practice, including relevant performance objectives and their weights under particular constraints. Primary and secondary data will be captured via document analysis, workshops (up to 4) and semi-structured interviews (up to 60), with data collection guided by T3.1 outputs. IDEF0 process mapping will be employed to capture current and future AM SC configurations. The maps communicate the design of AM enabled responsive manufacturing systems, their management practices and decision-making processes. T3.3 conducts quantitative analysis of AM enabled responsive manufacturing systems using the Supply Chain Operations Reference (SCOR) model. Different configurations of AM enabled manufacturing systems are assessed, with performance measured against standard SC performance objectives (e.g., speed, cost, location) [plus further objectives identified in T3.1&2]. Integrated within the SCOR model, a multi-objective optimisation method that further integrates knowledge from T3.1&2 and the impact and security analysis from WP2, will be developed and validated for production decisions following a disruption. The M-OOP method assesses alternative manufacturing system performance frontiers formed with Pareto efficient performance levels before applying meta-heuristic algorithms (e.g., NSGAII or MOPSO) that simultaneously optimise the multiple objectives identified in T3.1&2. The outcome of the analysis is used to determine the optimal SC configuration to implement post disruption. The deliverables for WP3 include: D3.1. an empirically grounded taxonomy for centralised and distributed AM configurations; D3.2. Integrated SCOR and multi objective optimisation model for AM enabled responsive manufacturing systems which, together with D3.1, provide mixed method validation of AM responsive manufacturing configurations and decision support for manufacturers. 

In summary, the provision of the practicable methodology will be achieved through the integration as a cohesive whole, WP1, 2 and 3, which together, enable a responsive additive manufacturing system to detect and respond to internal and external factors caused by malicious or natural events.

The PDRA will focus specifically on the third of the work streams, T3.3, but will support Co-I Dr Davies on the first two streams. Whilst the SCOR method is highlighted, we are open to the use of other techniques within the M-OO.

The business Schools role is to provide the multi-objective optimisation method that enables the rapid reconfiguration of supply chains. This falls under two clear goals:

  • Working in close collaboration with CoI from Henley and researchers from across the group of partner firms, alongside academics who have expertise in AM and cybersecurity. The PDRA will focus upon M-OO application, leading the development of this part of the project and contributing theoretical insights.
  • Work needs to be synthesised into journal articles. The perspective taken will depend on your skills (M-OO plus value, power, business models, supply chain, systems, service etc.), but outputs are important both for the project and your own CV 

The deliverables from this project will directly support and help integrate the work of other project partners who are developing the components of the manufacturing system, including the detection systems and analyse systems that analyse the disruption.

PRIMARY RESPONSIBILITIES

The key responsibilities of the position will be to:

  • Undertake research at an internationally competitive level.
  • Contribute to the development of the research project, specifically:
    • Leading the development of the multi objective optimisation for supply chain disruption and a taxonomy for additive manufacturing supply chains.
    • To publish journal articles, building on current skills that supports the project goals.
  • Disseminate research results to the project team, as well as through peer-reviewed publications and conference presentations. 

PROJECT PARTNERS

The RAMONA project is led by Dr Gregg Gibbons (PI & Technical Lead) from Warwick. Professor Parry is Co-I from Surrey. Other co-Investigators on the project include Dr Philip Davies (Supply Chain - Henley),Prof. Carsten Maple & Dr Greg Epiphaniou (Cyber Security – Warwick), Professor MA Williams (Additive manufacture - Warwick).

WHO ARE WE LOOKING FOR?

A PhD in Mathematics, Engineering, Operations Research or Computer Science or related subjects to the call as well as a high degree of organisation and ability to plan and manage your own studies are essential.  You will need to be able to offer thought leadership and hit the ground running. A knowledge of mathematical modelling/multi objective optimisation is essential.

Previous academic experience publishing in academic journals in an applicable area of academia is highly desirable.

Previous experience of some of Business and Management area related to the project – which may include Operations Management, Supply Chain Management, Operations Research, Engineering management is desirable. Expertise exist within the group on Operations and Supply Chain Management.  

Given the broad cross-disciplinary nature of the project, it’s expected that the PDRA would spend time visiting partners and working closely with the researchers at these institutes. Therefore, excellent communication skills and the ability to work with other disciplines are also essential. 

The position is for 30 months full time.

If you would like to discuss the position informally, please send us an email and we'd be excited to discuss the project further with you.

HOW MUCH WILL YOU BE PAID?

Ranging from Grade 4.1 to 4.8: Salary from £32,817 per annumdepending on experience.

Significant additional funding is available for travel expenses.

 

WHEN MUST YOU APPLY AND INTERVIEW?

Applications will close on the 4th August but please apply as soon as you can.

We aim to hold interviews between the 16th and 27th August. 

 

WHEN WILL YOU START?

To be agreed from September 1st 2021.

Candidates in the final stages of completing their PhDs are encouraged to apply only if they can provide a reference attesting that their PhD viva will be held by the end of December 2021, or shortly thereafter

More details

The role for the researcher is to focus on the third work package of the RAMONA project. We need someone who would be excited to take a leading role in developing relationships with our academic and business partners, applying their theoretical knowledge to practice. The PDRA will have strong modelling and quantitative skills to be able to develop the multi-object optimisation model for supply chain disruption. Depending on skills, either a systems perspective or process perspective may be taken.

More about the project

Online links:

  • https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/V051040/1

 

Email details to a friend
Further details:

For more information and to apply online, please download the further details and click on the 'apply online' button above.
 

The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all.  We place great value on diversity and are seeking to increase the diversity within our community.  Therefore we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities.

 

 

 


Get updates

Login

Athena Swan Bronze Award / Disability Confident Committed / Stonewall Diversity Champion