General information
We would be delighted to supervise your final-year dissertation in the business chemistry degree program. The topics of the dissertations are thematically and methodologically linked to the research priorities of the Chair.
As part of your Master’s thesis , you will apply quantitative (computer-based) methods to evaluate or design solutions within the problem areas addressed, and further develop these methods to suit the specific problem. Working with software-based environments for modelling, evaluation and optimisation is therefore compulsory.
For the bachelor's thesis, a more literature-oriented approach to the topic is also possible as an alternative to the development and application of computer-based methods.
Examples of topics
Sustainability assessment of chemical processes
Abstract
The chemical industry faces the challenge of evaluating novel synthesis processes not only in economic terms but also from an environmental perspective. The aim of this thesis is to carry out life cycle assessments (LCAs) for selected innovative chemical synthesis routes and to compare them on the basis of relevant sustainability criteria. Based on the functional unit to be defined, key material and energy flows are modelled and quantified using, amongst other things, established LCA databases.
The scope of the analysis can be chosen. A process-oriented focus centres on the detailed mapping and evaluation of process operations within a single production site, for example with regard to energy input and process yields for alternative process variants. Alternatively, a value chain-based approach allows the analysis to be extended to upstream and downstream stages of the value chain, including raw material extraction and processing, transport and the utilisation of co-products.
In both cases, particular emphasis is placed on conducting numerical experiments to systematically investigate the influence of key parameters on environmental impacts such as global warming potential, resource consumption or acidification. The work combines the methodological foundations of life cycle assessment with software-based implementation in Python, utilising tools such as ecoinvent and Brightway2. The results provide a transparent basis for decision-making and concrete starting points for the sustainable design of chemical processes and value chain systems.
Possible components of the thesis
- Introduction to sustainability and life cycle assessment in the chemical industry
- Definition of objectives and scope of investigation
- Modelling of synthesis processes and data selection
- Implementation of the LCA in Python (Brightway2, ecoinvent)
- Conducting numerical sensitivity and scenario analyses
- Interpretation, comparison and discussion of the results
- Derivation of recommendations for sustainable process design
Resource-constrained project planning in the chemical industry
Abstract
Project management in the chemical industry encompasses a wide range of project types, such as product development, plant design and organisational improvements. These projects are often characterised by complex technical and organisational dependencies, limited human and financial resources, and uncertainties in project progress (resource-constrained project planning).
The aim of this thesis is to develop a mathematical optimisation model to support project planning in the chemical industry. Building on realistic project structures, work packages, objectives, resource capacities, and technological and organisational dependencies are formalised. The application context may, for example, be based on the project types mentioned above.
Using operations research methods (e.g. mixed-integer programming, heuristics), an optimisation approach is developed that explicitly takes into account the specific characteristics of project management in the chemical industry. Implementation is carried out in Python, with the solution typically utilising a commercial solver such as Gurobi. This thesis demonstrates how quantitative decision-making models complement traditional project management and enable well-founded, transparent planning of complex projects in the chemical industry.
Possible components of the thesis
- Fundamentals of project management and project scheduling
- Overview of project types in the chemical industry (e.g. R&D, plant design, maintenance, sustainability projects, etc.)
- Analysis of typical characteristics of projects in the chemical industry
- Mathematical formulation of the optimisation model
- Implementation in Python and solution using Gurobi
- Analysis of selected project and scenario variants
- Sensitivity analyses regarding resources, duration, priorities, etc.
- Discussion of practical implications and model limitations
- Outlook on scientifically and practically relevant model extensions
Design of plant complexes in the chemical industry
Abstract
Chemical production sites consist of complex networks of plants with material, energetics and logistical interdependencies. The aim of this thesis is the model-based design and optimisation of such plant networks subject to economic and technical constraints. The starting point is the formal description of a multi-stage production system comprising several plants, intermediate products and capacity constraints.
Using operations research methods, an optimisation model is developed to support decisions regarding plant utilisation, interconnections and sizing. Depending on the focus, costs, throughput, energy efficiency or flexibility can be considered as objective functions. Implementation in Python using Gurobi enables the solution of realistic-scale problems as well as the analysis of alternative structural and demand scenarios.
This thesis demonstrates how quantitative models can be used to support strategic and operational decision-making in plant management. The results provide valuable insights for investment, expansion and operational decisions in the chemical industry and highlight the benefits of integrated planning approaches.
Possible components of the thesis
- Introduction to process and plant management
- Description and definition of the plant network
- Mathematical modelling of the production structure
- Implementation of the optimisation model in Python/Gurobi
- Scenario and sensitivity analyses
- Interpretation of the results for plant management
- Discussion of limitations and practical applicability
Design of multi-stage production networks in the chemical industry
Abstract
Production networks in the chemical industry are geographically dispersed and multi-stage in structure, with complex interdependencies between production sites, intermediate products, transport links and capacity constraints. The aim of this thesis is the model-based evaluation and design of such multi-stage production and logistics networks using optimisation methods.
Based on a product portfolio to be defined, alternative network structures are formally described; these differ, for example, in the number and geographical location of production stages, the allocation of processes to sites, and in transport links and capacities. Using operations research methods, an optimisation model is developed that takes key objective functions into account, such as total costs, lead times and capacity utilisation. Sustainability aspects can be integrated as constraints or additional evaluation criteria.
The model is implemented in Python, with the solution calculated using commercial solvers such as Gurobi. This thesis demonstrates how optimisation models can be used for the systematic evaluation and design of complex production networks and provides a sound basis for decision-making regarding strategic and tactical planning issues in the chemical industry.
Possible components of the thesis
- Fundamentals of network planning
- Characterisation of multi-stage production networks in the chemical industry
- Modelling of sites, production stages, material flows and transport relationships
- Formulation of an optimisation model
- Implementation in Python and solution using Gurobi
- Analysis of alternative network structures and demand scenarios
- Sensitivity analyses of capacities, costs and transport relationships
- Interpretation of the results and derivation of design options
- Discussion of model assumptions and practical applicability
Proposals for your own research topics and final-year projects within the industry partnership
You are also welcome to suggest your own topics for your final-year dissertation. When submitting proposals for final-year projects in collaboration with industry, please ensure that the proposed topic demonstrates sufficient scientific novelty (e.g. it should not merely involve the implementation of established approaches in industry) and aligns with the methodological and thematic priorities of the professorship. Due to the specific requirements for final-year projects in collaboration with industry, we only supervise these at Master’s level, and not at Bachelor’s level.
