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Electrolux Professional – Big Data Analytics for Insights into Professional Product Life Cycle – Ljungby, Sweden
Become part of a multidisciplinary and agile team at The Research Hub at Electrolux Professional AB in Ljungby, Sweden, developing the technology driving tomorrow’s laundry appliances.
Electrolux Professional is one of the leading global providers of food service, beverage and laundry solutions, serving a wide range of customers globally, from restaurants and hotels to healthcare, educational and other service facilities.
What drives us every day is our mission to make our customers’ work-life easier, more profitable – and truly sustainable.
Vision and Goal: We are looking to partner with a PhD student who will utilize Big Data to allow us to map the life cycle of our products and switch from a reactive to proactive approach in product development, production, and maintenance/repair.
Together with you, we seek to grow and create sustainable experience for people and the world around us, in food, beverage and laundry. Big Data will enable us to analyze and understand the events occurring during the lifetime of our equipment, from birth to replacement. With this in-depth understanding, we expect to create benefits internally, for our customers, and the world around us.
The focus of the research will be to:
- Work on quality improvement by focusing on developing/modifying weak components/modules
- Enhance quality in production by focusing on developing/modifying processes and end-of-line controls
- Increase speed of resolution for Quality related issues (easy access to data)
- Prevent equipment failure by redefining an adapted maintenance program (maintenance vs repair, benefit: less costly, less downtime)
- Maximizing cost saving for customers by analyzing utilization of equipment, program
- Expend the range of services (Service agreement, connectivity, consumables, …)
- Improve product reliability and customers satisfaction
The industry PhD-student will be employed at Electrolux Professional and enrolled in the graduate program at Linnaeus University. Therefore the position has some academic requirements that needs to be fulfilled.
General entry requirements
- has been awarded a second-cycle qualification
- has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second-cycle, or has acquired substantially equivalent knowledge in some other way in Sweden or abroad.
Specific entry requirements
- approved courses of a minimum of 90 credits in the subject Computer and Information Science or the equivalent
- an individual study project of a minimum of 15 credits in the subject Computer and Information Science, or the equivalent.
Good programming skills (in for example Java, C#, Ruby or Python), and a solid training in mathematics and theoretical computer science. Documented expertise and working experience within at least two of the following research and educational areas is a great advantage:
- Big data analytics
- Data visualization
- Machine learning
- Predictive Maintence
- Parallel processing
Because of the interdisciplinary character of the project and LNUC DISA (https://lnu.se/en/disa), the candidate should be an enthusiastic person who is interested in making sense of large and complex data sets of various types as well as capable of working both independently and within a group. Teamwork experiences should be documented in the application.
High proficiency in written and spoken English is required.
Applicants will be selected through a qualitative overall assessment of the competences and skills, assessed most suitable to conduct research and to contribute to a successful development of the research environment.