Developing engineering solutions through life cycle thinking

In ES2-Lab, we are interested in leading the research area of sustainable process systems engineering by: 

  • Developing advanced mathematical tools underpinned by life cycle thinking for the assessment and optimisation of more sustainable processes
  • Promoting the widespread use of these methods in a wide variety of applications to facilitate the transition towards a more sustainable economy

Aras of particular interest include:

  • Sustainability assessment of systems according to multiple criteria
  • Modelling of uncertainties and stochastic programming
  • Large-scale multi-objective optimisation of complex systems
  • Integration of multi-criteria decision-making and multi-objective optimisation
  • Simulation-optimisation for process design

Global challenges in sustainability


Green Supply Chain Management

Green Supply chain management (SCM)

Sustainable supply chains

Supply Chain Management (SCM) looks for the integration of a plant with its suppliers and its customers to be managed as a whole, and the co-ordination of all the input/output flows (materials, information and finances) so that products are produced and distributed at the right quantities, to the right locations, and at the right time. The main objective is to achieve suitable economic results together with the desired consumer satisfaction levels. The SCM problem may be considered at different levels depending on the planning horizon and the detail of the analysis: strategic, tactical and operational. We are at present developing multi-objective models for SCM problems that reduce their life cycle impact through the adoption of appropriate mitigation strategies and cleaner technologies. These models are being applied in a wide variety of problems, with emphasis on biofuels supply chains and energy systems. 

Sustainable Process Design

Sustainable Process Design

Process simulation

Process design has a great impact on the sustainability performance of chemical processes, as the most critical decisions are taken at the early stages of the process development. We are following two main approaches to improve the sustainability level of chemical processes: superstructure optimisation and simulation-optimisation algorithms. Our models account for several economic, environmental and social metrics that are assessed in the face of multiple uncertainties.

Other applications in sustainability

Short-cut methods of environmental impact

mol levCurrent LCA repositories contain information of a limited number of chemicals. Through the development of short-cut methods of sustainability performance, we can estimate the environmental impact of  chemicals currently missing in LCA databases, thereby enabling the fast screening of  alternative chemical routes.  To build our models, we combine mathematical programming with multi-variate statistical methods in order to identify key structural and thermodynamic properties of a chemical most strongly connected to its environmental performance. 

Assessment of chemical products and processes: Identifying the most efficient processes

Sustainability efficiencyProblems arising in sustainable engineering are inherently multi-criteria. Using the concept of efficiency and applying data envelopment analysis, we can analyse trade-offs between conflictive goals in a systematic manner. This allows us to identify the best performing solutions while establishing improvement targets for the suboptimal ones.

Macro-economic models: Systems optimisation combined with input-output 

polAt the macro-economic level, we are applying systems thinking underpinned by optimisation to provide integral solutions for global sustainability challenges. Here, we combine optimisation with input-output tables, the latter being used to describe monetary flows between countries and the corresponding environmental burdens embodied in them. This integrated approach allows us to identify solutions that decrease the impact globally with minimum impact on the countries' GDPs.