Edit StudentProjectForm: Analysis of multi-machine/multi-sensor data

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Summary:	MANDATORY: (provide a one-line* summary of the project)*
Programme:	OPTIONAL: (Name and the number of credits)
Keywords:	OPTIONAL: (Give 4-5 keywords)
TimeFrame:	MANDATORY: (Indicate time for the project, for example, Fall 2024)
References:	OPTIONAL: (Give 2-3 references for students to start with)
Prerequisites:	OPTIONAL: (Courses, any other important information)
Supervisor(s):	MANDATORY: (can be multiple names, coma-separated)
Examiner:	OPTIONAL: (Name of project Examiner)
Author(s):	OPTIONAL: (can be multiple names, coma-separated)
Level:	MANDATORY: choose one, preferably <Master>
Status:	MANDATORY: choose <Open> when the topic is ready for students to select

Project description (free text)

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Research question
Whether it’s more software or hardware related
A very brief description of 3-4 work packages
Deliverables/outcomes/results

This is a fantastic opportunity to work with Alfa Laval, a world's leader and pioneer in producing separator machines. This data mining project aims to generate insights from multi-machine/multi-sensor time series data generated by Alfa Laval machines. Various problems such as clustering, co-clustering, anomaly and outlier detection, and sequence mining can be investigated depending on the student's interests. Please contact supervisor via email to discuss more: hadi.fanaee@hh.se

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Edit StudentProjectForm: Analysis of multi-machine/multi-sensor data

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