PhD Position Smart Planning and Control for Sustainable and Reconfigurable Value Chains

2 Mar 2024
Job Information

Organisation/Company

Delft University of Technology (TU Delft)

Research Field

Technology

Researcher Profile

First Stage Researcher (R1)

Country

Netherlands

Application Deadline

15 Apr 2024 - 21:59 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

40.0

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

In today's rapidly evolving industrial landscape, the objective of any value chain is to sustainably utilize industrial systems to create outputs that maximize value for customers. However, achieving this goal requires navigating several challenges, both from an outward-looking perspective focused on customer value evolution and sustainability, as well as an inward-looking perspective concerning optimal resource utilization and intrinsic system disruptions.

Leveraging reconfigurable manufacturing systems (RMS) offers flexibility to adapt to changing demands and disruptions. Moreover, Production Planning and Control (PP&C) strategies play a relevant role in enhancing operational performance. These strategies span over different time horizons for effectively managing production activities, resource allocation, scheduling, and decision-making to optimize performance and achieve organizational goals. Feedback loops and real-time decision-making are particularly critical in complex and dynamic manufacturing environments where rapid adjustments are necessary to respond to changing conditions, such as fluctuations in demand, supply disruptions, or production constraints.

A research question arises: “How can planning and control strategies and mechanisms be designed and implemented to enhance the efficiency and reconfigurability of value chains in dynamic industrial environments?

To explore this area effectively, the PhD candidate could delve into several interconnected research areas:

Integration of Model Predictive Control (MPC) in value Chain Planning and Control: Investigate how MPC principles can be adapted and applied to optimize planning and control processes across reconfigurable value chains. This involves developing MPC strategies that can dynamically adjust production plans, resource allocations, and scheduling decisions in response to changing demand patterns, disruptions, and sustainability requirements.

Reconfigurability in value chains: Explore the concept of reconfigurable value chains and how it can be leveraged to enhance flexibility, resilience, and responsiveness. Study different approaches to designing and implementing reconfigurable systems, such as modular production setups, flexible supply chain networks, and adaptive logistics solutions

Dynamic modeling and prediction: Develop dynamic models and predictive algorithms to capture the complex behavior of value chains over time. This involves analyzing historical data, identifying patterns and trends, and using predictive analytics to forecast future demand, supply, and market conditions. These predictive insights can then inform MPC strategies and decision-making processes within the value chain.

Optimization and decision support: Design optimization algorithms and decision support systems that integrate MPC and reconfigurability principles to maximize value creation and sustainability in the value chain. This includes formulating mathematical optimization models, implementing simulation-based approaches, and developing real-time decision support tools that consider multiple objectives, constraints, and uncertainties.

Case studies and applications: Apply the developed methodologies and tools to real-world case studies and industrial applications across different sectors, such as manufacturing, logistics, and distribution. Evaluate the effectiveness and practical feasibility of the proposed approaches in improving operational performance, reducing costs, and enhancing overall value chain resilience.

Requirements
Specific Requirements

A master's degree in a relevant field such as industrial engineering, mechanical engineering, computer science.

The candidate should be ambitious and curious and will be supported to establish a collaboration with one or more companies and international research institutes.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements .

Additional Information
Benefits

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €2770,- per month in the first year to €3539,- in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Selection process

A pre-employment screening can be part of the selection procedure.

Additional comments

Are you interested in this vacancy? Please apply no later than 15 April 2024 via the application button and upload your motivation and CV.

• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.

For more information about this vacancy, please contact Alessia Napoleone: [email protected] .

For information about the application procedure, please contact Anita van Vianen, HR Advisor: [email protected] .

Website for additional job details

https://www.academictransfer.com/338500/

Work Location(s)

Number of offers available

1

Company/Institute

Delft University of Technology

Country

Netherlands

City

Delft

Postal Code

2628 CD

Street

Mekelweg 2

Geofield

Where to apply

Website

https://www.academictransfer.com/en/338500/phd-position-smart-planning-and-cont…

Contact

City

Delft

Website

http://www.tudelft.nl/

Street

Mekelweg 2

Postal Code

2628 CD

STATUS: EXPIRED