Final Thesis Leveraging Artificial Intelligence for Work Content Integration in Production Line Balancing A320 FALs Family (d/f/m)Airbus Operations GmbH • Hamburg, Hamburg, Germany

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Airbus Operations GmbH

Final Thesis Leveraging Artificial Intelligence for Work Content Integration in Production Line Balancing A320 FALs Family (d/f/m)

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Hamburg, Hamburg, Germany

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Job Description: Airbus Operations is looking for a Bachelorand/Masterand in the field of Digital Industrial Transformation (d/f/m), A320 FALs Family Paperless Production You are looking for a bachelor thesis/master thesis and want to get to know the work of our PMT transformation organization for Shopfloor? Then apply now! We look forward to you supporting us and enriching our team as a Bachelorand/Masterand (d/f/m)! As PSE (Production System Efficiency) & Digitalisation for FAL A320 family, we are responsible for defining the manufacturing engineering process, methods, tools and data for the A320 final assembly lines (FALs) in Hamburg, Toulouse, Tianjin and Mobile. Within the organisation you will join the Shop floor execution & efficiency Team, who are engaged to support the A320 family in a challenging ramp-up until 2027. One of the key conditions of success is to identify, develop and deploy sustainable digital solutions in order to upgrade the FALs PMT (Process, Methods & Tools) landscape. Location: Hamburg Start: As soon as possible Duration: 6 months Your location You will be working at the largest production site for civil aircraft situated in Hamburg. Its location on the southern banks of the river Elbe includes the option to commute by ferry. Experience the special flair of Hamburg in your spare time where vibrant cosmopolitan culture meets nautic legacy. Your benefits Work-life balance with a 35-hour week (flexitime). Traveling within Europe is possible after consultation and agreement from the department. International environment with the opportunity to network globally. Work with modern/diversified technologies. At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings. Opportunity to participate in the Generation Airbus Community to expand your own network. Your tasks and responsibilities The core challenge in line balancing is distributing tasks (work content and activities) among workstations to achieve a smooth, efficient flow, minimize idle time, and avoid bottlenecks. This is especially complex with high product variety, fluctuating rates, and dynamic production environments - which are all applicable in Aerospace industry. AI tackles this by leveraging data, learning patterns, and optimizing solutions in ways traditional methods cannot. We offer two fields for deep investigation: AI-driven E2E PERT/constraints review or definition: mining existing data sources (e.g. from CAD/PLM system, MES/ERP system, Work Instructions) or learning precedence relationships (e.g. Graph Neural Networks) AI-automated integration of Out of Sequence Work: constraint learning and refinement, constraint relaxation rules, identification of references & interdependencies in data The leading question could be: How AI can automatically identify and define task dependencies (precedence relationships) from existing data sources? Expected result: Pre-analysis and evaluation for use cases and requirements. Concept draft and evaluation of state-of-the-art AI technologies. In scope: Requirements Elicitation Functional Requirements Non-Functional Requirements AI Capability Mapping and Assessment Requirements Fulfillment Analysis Conceptual Framework Development Benefits and Challenges Desired skills and qualifications Enrolled full-time student (d/f/m) in the area of Economical Engineering, Computer Science, Production and Logistics, Artificial Intelligence or an equivalent field of study. First practical experience working in a matrix organization or a corporate setup is desirable. Understanding for Information Systems. Strong analytical skills and the ability to simplify complex topics and develop implementable solutions. Good communication skills. Fluent English language skills, German or French would be an advantage. Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate. Not a 100% match? No worries! Airbus supports your personal growth. Take your career to a new level and apply online now! This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company's success, reputation and sustainable growth. Company: Airbus Operations GmbH Employment Type: Final-year Thesis - Experience Level: Student Job Family: By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus. Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief. Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to . At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

Wünschenswerte Fähigkeiten

Artificial Intelligence
CAD
Data Mining
Machine Learning

Hamburg, Hamburg, Germany

Berufserfahrung

Data Engineer
Machine Learning
Data Scientist

Sprachkenntnisse

English

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