Diese Seite auf DE

Event

Learning Factory “Global Production“ [WS202149612]

Type
seminar/internship (S/P)
Präsenz
Term
WS 20/21
SWS
4
Language
Deutsch
Appointments
0
Links
ILIAS

Lecturers

Organisation

  • KIT-Fakultät für Maschinenbau

Part of

Literature

Medien:
E-Learning Plattform ilias, Powerpoint, Fotoprotokoll. Die Medien werden über ilias (https://ilias.studium.kit.edu/) bereitgestellt.

Media:
E-learning platform ilias, powerpoint, photo protocol. The media are provided through ilias (https://ilias.studium.kit.edu/).

Note

The learning factory “Global Production“ serves as a modern teaching environment for the challenges of global production. These are made tangible using the example of the manufacture of electric motors under real production conditions.
The course is characterized by its interactive hands-on sessions, which are theoretically supported by e-learning units. The e-learning units serve to convey essential basics as well as to deepen specific topics from the classroom units (e.g. site selection, supplier selection and planning of production networks). The focus of the hands-on sessions is the case-specific application of relevant methods for planning and managing global production networks.
First, classical methods and tools of Lean Management for the site-specific design of the production system (e.g. Kanban and JIT/JIS, Line Balancing) are learned and extended by methods of Industry 4.0. Within the scope of site-specific quality assurance, essential methods for data-driven quality assurance in complex production systems are taught and made practically tangible by means of a Six Sigma project. The focus is especially on methods of data mining with an excursus on artificial intelligence. In the area of scalable automation, it is important to find solutions for the adaption of the level of automation of the production system to the local production conditions (e.g. automated workpiece transport, integration of lightweight robots for process linking) and to implement them physically. At the same time safety concepts should be developed and implemented as enablers for human-robot collaboration. Finally, the view of the entire value chain network will be broadened by the integration of partners from the value chain. Thereby selected methods of supplier management (e.g. make-or-buy) and network design are learned and implemented. In the field of network management, collaboration between value chain partners and locations is considered a tool for increasing efficiency and avoiding disruptions. The special importance of digitisation as an enabler of collaboration is illustrated by the implementation of a traceability concept.
The course also includes an excursion to the production plant for the manufacturing of electric motors of an industrial partner.

Main focus of the lecture:

  • site selection
  • Lean Management and Industry 4.0
  • Six Sigma 4.0 - Data Mining for Site-Specific Quality Assurance
  • Scalable Automation and Human-Robot Collaboration
  • Supplier Management
  • Network Planning and Design
  • Collaboration and Traceability

 

Learning Outcomes:

The students are able to …

  •  evaluate and select alternative locations using appropriate methods.
  • use methods and tools of lean management to plan and manage production systems that are suitable for the location.
  • use the Six Sigma method and apply goal-oriented process management.
  • Derive automation potentials and systematically decide on a suitable degree of automation of production plants under given constraints.
  • make use of well-established methods for the evaluation and selection of suppliers.
  • apply methods for planning a global production network depending on company-specific circumstances to sketch a suitable network and classify and evaluating it according to specific criteria.
  • understand general interactions in the production network and effectively develop collaboration in the production Environment
  • apply the learned methods and approaches with regard to problem solving in a global production environment and able to reflect their effectiveness.

 

Workload:

e-Learning: ~ 36 h
regular attendence: ~ 64 h
self-study: ~ 80 h