Context awareness opens new areas for flexible manufacturing system optimizationIn his doctoral dissertation, Mohammad Kamal Uddin presents a novel application of context-sensitive computing for flexible manufacturing systems (FMS) addressing KPI optimization at runtime.
Context awareness has garnered a lot of interest within ubiquitous and pervasive computing environments, especially with the advancement of embedded systems, semantic web technologies, service oriented integration, and associated web service standards. The research on context-based application development is also growing in different areas of manufacturing. However, relevant research is relatively new to the dynamic operating environment of FMS, where plant controls must handle last-moment changes in process parameters due to unscheduled or unplanned events.
Context extraction at source, context modelling, and context management for higher level application usage are the key research areas in manufacturing, and ontologies are considered to be the essential building block for context-based knowledge sharing and re-use in distributed environments. Context-sensitive computing for FMS aims to improve the overall transparency of the complex machines and operations, allowing the automatic integration of dynamic changes. This eventually brings intelligence to the lower factory level, facilitating optimized decision-making at runtime. Bridging of context-sensitive computing and FMS mainly facilitates manufacturing knowledge management between design tools and contextual knowledge exchange in a complex environment through decision support applications for global factory optimization.
In his thesis, Uddin proposes a methodology where runtime contextual entities are used to monitor KPIs continuously to update an ontology-based context model, and subsequently to convert it into business-relevant information via context management. The delivered high-level knowledge is further utilized by an optimization support system, providing KPI optimization at runtime. The proposed approach is presented as an add-on functionality for FMS control, where modular development of the overall approach provides solutions that are generic and extendable across other domains. Functional implementation has been addressed in a practical FMS use case within service-oriented architecture and web service -based control system. Results indicate that continuous improvement of the factory can be enhanced utilizing context-sensitive support applications that provide an intelligent interface for knowledge acquisition and elicitation. This can be used for improved data analysis and diagnostics, real-time feedback control, and support for optimization.
Public defence of a doctoral dissertation on Friday 26 May
The doctoral dissertation of MSc (Tech) Mohammad Kamal Uddin in the field of factory automation titled “An Application of Context-Sensitive Computing for Flexible Manufacturing System Optimization” will be publicly examined at the Faculty of Engineering Science of Tampere University of Technology (TUT) in the Festia building, auditorium Pieni Sali 1 (address: Korkeakoulunkatu 8, Tampere, Finland), at 12:00 on Friday 26 May 2017. The opponents will be Professor Esko Niemi (Aalto University, Finland) and Research Professor Rodolfo Elias Haber Guerra (Centre for Automation and Robotics, CSIC-UPM, Spain). Professor Jose L. Martinez Lastra from Laboratory of Automation and Hydraulic Engineering will act as Chairman.
Additional information: Kamal Uddin, +358 50 368 2559, mohammad.uddin (at) student.tut.fi