Fields or subjectsDigital and Virtual EngineeringMaterials and Process EngineeringNetworking in ManufacturingICT for ManufacturingKnowledge-based ManagementIntelligent Production SystemsLife Cycle Sustainable Management
Graduate School of Excellence advanced Manufacturing Engineering in Stuttgart
The support of the development of young researchers is of utmost importance to the University of Stuttgart. With our dual, innovative doctoral program, and excellent record of advanced scientific research the Graduate School contributes to it immensely.
With cutting-edge research and inter-disciplinary training - from all areas of engineering - our goal is to develop sustainable scientific fundamentals in manufacturing engineering. We believe our doctoral candidates will be prepared for the challenges of the factories of the future.
Our focus is to incorporate the outstanding quality in research, training and supervision of doctoral candidates. The innovative nature of our doctoral program has been confirmed by another 5-year funding by the Deutsche Forschungsgemeinschaft (German Research Foundation) within the "Excellence Initiative" and by winning the Best Practice Award for Improvements in doctoral theses in the field of Engineering.
The collaborative, interdisciplinary research at a number of research institutes, non-university research institutions and companies from the private sector, combined with a theoretical knowledge, practice, technology, management and application is what makes the Graduate School innovative.
The dual training offered by the Graduate School, a combination of individual advisory and profile-specific training based on knowledge and experience of each doctoral candidate thus offers ideal conditions within a broad international scientific environment.
GSaME is the major scientific institution at the Universty of Stuttgart, Germany, which offers gaining a PhD degree, disposes of individual admission, study, examination and a specific governance structure. 33 professors from 5 faculties at the University of Stuttgart, along with international corporate partners from various scientific and commercial sectors, are promoting a doctoral program in research and development.
The research areas are divided into interdisciplinary clusters:
Stuttgart Enterprise Model is the Base
Digital and Virtual Engineering
Materials and Process Engineering
Networking in Manufacturing
ICT for Manufacturing
Intelligent Production Systems
Life Cycle Sustainable Management
Cluster directors are responsible for the further development of research and scientific education in the specific field within the clusters. The Supervisory Board ist he highest organ oft he graduate School and consits of members from the University of Stuttgart, industry and science. The Scientific Advisory Board is an international committee of representatives from international universities, the University of Stutgart faculties, industry, science and international federations.
Stuttgart Enterprise Model is the Base The theoretical basis is the Stuttgart Enterprise Model which is related to the systems theory. According to this definition, the factory itself is a product with different life cycles. It is hierarchically structured in performance units. The single performance unit has to be considered a self-organizing cell that carries out assigned tasks and controls, thus configures and optimizes itself. With consistent standardization, this approach is applicable to any process chain on every scale and leads to a sustained transformability of production.
Digital and Virtual Engineering The application of digital and virtual methods aims at comprehending the factory as a complex product and at optimizing it integrally in order to produce even small lots cost-efficiently and timely for the current fast moving and individualizing markets. For that purpose, the digital factory models the status quo of the existing factory including its resources, logistic demands and production orders. In the virtual factory the planning gets optimized: The future production is simulated on all scales, based on the actual condition of the present factory. Thus, the impact of improvements can be tested fast, economically and without risk in virtual reality and creates optimized planning scenarios by "learning from the future".
Materials and Process Engineering The materials and process engineering wants to develop new substances, whose properties are determined in advance and thus are ideally adapted to their future application. Material properties can be influenced by the substance itself, material combinations and the production process. Thereby the reciprocal effects between materials production techniques have to be further examined. This well directed controlling of material behavior will be coped with on all scales from nano and micro parts to complete machines.
Networking in Manufacturing A smooth and well orga¬nized value chain from the supplier to the work flow design is a key factor to cost-efficient production. The high demands which small lots, customized goods and high process and product complexity as well as on-demand manufacturing put on these organizational structures cannot be met with classical lean management, geared towards huge lots and simple processes. Due to this fact, a standardization initiative is to be created including all aspect of modern production networks. Therefore, a special focus is put on the reliability and availability of systems and the use of synergies.
ICT for Manufacturing Modern production systems need efficient tools for managing, engineering and processing which are completely included in internal and external communications architectures and applications. Open systems and embedded electronics make it possible to realize an integrated, knowledge-based production. Standardization, modularization and system engineering contribute to the transformability and mutability of production. One aim is the real-time factory in which the present state of the factory can be digitally reproduced via architectures and applications and possible adaptations, for example, triggered by changes in customer requests can be performed self-adaptively.
Knowledge-based Management Knowledge about machines, processes and networks existing implicitly and explicitly in all units of a company, has to be documented and made publicly available in order to have best-practice libraries for the future. In order to sustainably guarantee the transformability and mutability of a factory, the knowledge-based management has not only to be applied to employees but also integrated in machines and processes. For the actual application this includes using and handling technologies, building expert networks and managing innovations.
Intelligent Production Systems Today, production enterprises must be able to react quickly and efficiently to changing requirements. Flexible, reconfigurable and intelligent production systems are an important basis for this. A consequently modular structure, the use of mechatronic system components, an efficient control and drive technology as well as knowledge-based software systems for engineering and programming are key elements. The aim of this cluster is to continue with development of these technologies consistantly and to promote new research fields such as condition-dependent maintenance and repair, intelligent sensor data processing, situation-oriented user assistance as well as self-learning, self-adapting, self-optimizing and the use of digital machine models for the control and diagnosis of these production systems.
Life Cycle Sustainable Management Sustainable life cycle management develops methods and concepts combining economic and ecological as well as societal and entrepreneurial aspects. Within the economic system this includes survival strategies for turbulent markets as well as identifying and supporting long-lasting technologies. An efficient use of energy and resources in production and processes not only avoids waste, but gives also important incentives for the planning of plant and supply networks.
GSaME scientific program is exclusive and consists of the core program, a cluster - specific program and the supplementary program.
This unit provides all doctoral candidates with general knowledge of advanced Manufacturing Engineering. Doctoral candidates acquire the knowledge though attending lectures, seminars, writing term papers and participating in various workshops.
Cluster specific Program
In this unit doctoral candidates will be provided with in-depth knowledge of their cluster programs. The objective is to give the candidates the best opportunity to process their research projects. Crucial will be self-study, lectures and seminars.
This unit objects the complementation of doctoral candidates existing knowledge (Management though Technology and Computer Science). Mentoring and Supervision will be based upon doctoral candidates individual knowledge, experience and needs.
A masters degree or equivalent (from a university or university of applied science with regular study modules, including a minimum of 9 semesters) in an engineering discipline (Engineering, Business, Electrical engineering), Computer Science or Business studies is a requirement for admission to the GSaME.
The Graduate School GSaME regularly announces vacant research topics on its website.
Approvals are based on a standardized recruitment scheme.
The GSaME has its own regulations of admission, examination and study.
There is a possibility of receiving various scholarships
Involvement of partners from industry and science throughout the process: Concept of the graduate school, the definition of research topics, recruitment of doctoral candidates and support during the training.
Graduate School of Excellence advanced Manufacturing Engineering in Stuttgart (GSaME)
Universität Stuttgart Nobelstr. 12 70569 Stuttgart Germany