Research Information system for a smart Lab - Use case scaling up of bio-fuel plant models

Abstract

In the research of biomass-based technologies, engineers and scientists develop models of industrial plants to produce bio-fuels.The goals of the research is to reduce the environmental impact and improve the process efficiency.To conduct the research, the knowledge about the input fuel is essential.However, the sources of this knowledge are very limited, stored in heterogeneous formats and need cross organizational data exchange. A reliable source of fuel characteristics data are accredited labors that conduct fuel analysis which is however a costly operation and in many cases conducted manually, leading to comprehensive paper documentation.To improve the processes and workflows, laboratories want to undergo a transformation towards Smart Labs where automation and interoperability are high priority goals.Therefore, chemical process engineering on fuels requires a solution to support efficient data management and availability.To improve the research workflows for the investigation of biomass-based technologies and build a base for digitalization of fuel laboratory towards a Smart Lab, this thesis introduces a method for designing a Research Information System (RIS).The thesis discusses the capabilities of software engineering to describe a complex domain knowledge, requirements elicitation, data collection and representation to improve research processes.The proposed improvement could be adopted by other disciplines to analyze complex use cases and advance digitalization processes.The research in this thesis follows the Design Science Cycle.To examine the problem arising from our use case, we conducted a literature analysis as well as interviews and workshops with domain experts.Based on the gathered knowledge, we created a domain knowledge model and derived requirements for the improvements.We propose the RIS Design Method to address the identified problems.To evaluate the RIS Design Method, we implemented a proof-of-concept prototype FuelRIS and conducted a user study with domain experts.The results of this thesis provide various solutions to problems of chemical process by applying software engineering. We provide description of use cases fuel transformation process and fuel analysis.Then we present a knowledge model to represent cause-effect relationships in fuel transformation process; the knowledge model scales with the project size.Furthermore we provide a method for designing information systems for research within Smart Labs to support and automate workflows specific to chemical engineers but probably applicable to other research domains.