Defence of dissertation in the field of computer science, Manik Madhikermi, M.Sc. (Tech.)
Manik Madhikermi, M.Sc. (Tech.), will defend the dissertation “Moving towards data-driven decision-making in maintenance” on Monday 10 June 2019 at 12 noon in Aalto University School of Science, lecture hall TU2, Maarintie 8, Espoo. The central idea of the dissertation research is to enable industrial companies to move towards data-driven decision-making for improved maintenance.
Maintenance is a complex process that requires planning, decision-making and executing various activities in coordination with stakeholders with the objective to extend equipment life and improve its availability. Traditionally, in the maintenance industry, maintenance efficiency is limited by the capability of the experts making the decision. With the advancement in technology, it is possible to improve the effectiveness of maintenance by adding an insight from the data to expert judgement. Despite data and analytical tools, companies are still struggling to fully harness data asset due to data-centric challenges. Hence, the main objective of this dissertation is to identify and mitigate those challenges.
In this dissertation, firstly, quantitative and descriptive analyses of case studies of Finnish manufacturing companies have been carried out to identify data-centric challenges. The study identified Data Quality, Interoperability, and Data extraction as key challenges. Furthermore, each of the identified challenges have been investigated through one or more original publications. The main results achieved in this dissertation are methods and frameworks to I) assess data quality of maintenance reporting II) interoperability framework for system interoperability III) data discovery methodology for data extraction. The research primarily focuses on the improvement in maintenance decision-making in equipment manufacturing companies. The generic nature of the identified problems and proposed solutions make this research useful in other domains too with minor modifications.
Opponents: Professor Dante Augusto Couto Barone, Federal University of Rio Grande do Sul, Brazil and Professor Samir Lamouri, ENSAM, Arts et Métiers ParisTech, France
Custos: Adjunct Professor Kary Främling, Aalto University School of Science, Department of Computer Science
Electronic dissertation: http://urn.fi/URN:ISBN:978-952-60-8582-1