School of Mechanical, Electrical and Manufacturing Engineering

Staff

Jeanetta Zotter MBA, B.Sc.

Photo of  Jeanetta Zotter

Educational career:
06/2019 – 09/2020 MBA in Engineering Management International
Master Thesis: Cloud Migration and Cloud Adoption;
How Cloud Computing Technology impacts Customer Experience
In-depth Study: Implementation of AI into Retail
Specialization: Computer Science (subject area)


09/2014 – 11/2017 B.Sc. in Mechatronics & Microelectronics
Bachelor Thesis: Aerospace Engineering - Static Investigation of Needle Emitters
for Ion Engines
Specialization: Nanotechnology


Professional career:
More than 8 years of professional experience in Technical Sales, Pre-Sales, and Project Management in the Industrial Manufacturing and IT sectors.


Specialization areas: Production Engineering, Automation, Internet of Things, Cloud Computing, Data Center, Artificial Intelligence Technologies, Digital Transformation, Industry 4.0, Researching into Industry 5.0.


- Lead of IoT Lab at Intel Corporation München
- Leading numerous PoCs of implementation AI Technologies into retail, industrial production process and security, and safety system measures
- Leading quite a few companies through digitalization (moving data from the traditional Data Center into the Cloud)
- Leading a project of installing production lines for filling beverages in plastic and glass bottles or beverage cans into a Smart Factory for the company FEMSA (foreign assignment of 13 weeks in São Paulo, Brazil)

Due to the rapid development of computer science and advanced manufacturing technology, manufacturing production has evolved into a digitized and intelligent factory so-called Smart Factory over the years.

If manufacturing companies want to meet the requirements of the market today, they have to get onto the path of digital transformation. Relating to Industry 4.0, the most significant influence to realize intelligent manufacturing is to implement the latest innovative technologies e.g. IoT, Cloud Computing and AI. Cloud- Assisted Smart Factory has a large number of low-cost storage and computing resources that provide numerous cloud-based personalized smart factory applications for industrial data.

The unique benefit of cloud and industrial wireless networks and intelligent IoT devices can be connected directly to achieve product customization. Cloud computing is an effective solution for the sharing of resources and the exchange of information in Smart Manufacturing systems. The technological advantages of artificial intelligence have made significant advances in industrial manufacturing in many areas such as image processing, natural language processing, and speech recognition. The use of AI technologies in Smart Factories has brought about many significant changes, including smart devices, collaboration mechanisms with autonomous decision-making and reasoning abilities, and data processing methods based on the advanced AI algorithms.

The work of the research project deals with the question of how the traditional production model has changed over the course of hundreds of years and how we can build a smart factory thanks to innovative technologies through the IoT which provides data based on the findings of AI for Cloud-Assisted Smart Factory, that is to say build a factory which one will come to live by 2030.

The research project also focuses on the following research topics: Development of a cloud-based smart factory architecture with intelligent devices and AI technologies, emphasis on intelligent manufacturing systems, production engineering computing, implementation of predictive and preventive maintenance, manufacturing execution system and advanced manufacturing technology. The most important technical problems and challenges of AI technologies in an intelligent factory are analyzed, discussed and appropriate solutions found.

Athena Swan Bronze award

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The Wolfson School of Mechanical, Electrical and Manufacturing Engineering
Loughborough University
Loughborough
Leicestershire
LE11 3TU