Center for Material Science
The Center for Materials Science is devoted to the chemical materials analysis and to mathematical modelling in the context materials science.
Thematic Fields
Material Analysis
The team of the thematic field of materials analysis focuses on carrying out chemical material analysis using chemical spectroscopic methods available in-house. In addition to chemical characterization of oxidation processes and other material changes, we can determine very precise flow properties of liquids and pasty substances, also in combination with detection of molecular material changes in the course of shearing processes. We also offer advice and contac persons on suitable analysis methods.
Methodes
Spectroscopic characterization of the chemical bonds of oils, fats and polymer materials using vibrational spectroscopy methods
- Infrared (IR) spectroscopy
- Raman spectroscopy
Both methods supplement each other in terms of information content.
Spectroscopic determination of metallic atoms (all metals heavier than sodium) in liquid and solid samples using X-ray fluorescence analysis (XRF).
Rheological-spectroscopic determination of the pot life of resins and paints. The parallel detection of the Raman vibration spectra and the change in viscosity of the mixed substances allows a very precise determination of the polymerization time under constant temperature conditions.
Rheological determination of oil and fat viscosities.
Determination of friction values for material pairings.
Computed tomographic (CT) determination of material inhomogeneity (foreign bodies / air pockets).
Projects
Vib-HVDC: Vibration spectroscopic analysis of E-field induced transformer oil movement
Using Raman spectroscopy, non-polar mode oscillations can be detected without contact. Transformer oil molecules that are exposed to an external electric field align themselves in the field. This dipole-induced alignment of the hydrocarbon molecules is expressed in changes in the intensity of certain Raman vibration bands.
The research project aims to investigate the alignment behavior of transformer oils depending on the water content and oil composition. Furthermore, it contributes to clarifying the influence of paper as an electrode cover on oil molecule mobility. Results of this study are complementary to optical Kerr measurements and contribute to the interpretation of oil conductivity behavior.


Relaxed: Raman-based detection of the relaxation time of shear-induced material stresses
Mechanical shearing or high-frequency E-fields induce molecular movements in the material, which lead to an increase in the Raman background signal. Through time-resolved detection of the Raman signal intensity, we can determine the relaxation time due to shear without contact. The aim of the research project is to explain the currently unknown phenomenon of the shear-induced Raman signal increase.


Contact:
Prof. Dr. Kurt Schwindl-Braun
97421 Schweinfurt
Tuesday, 15.00h – 16.00 h ( 3 p.m. - 4 p.m.)
Programme Director of Wirtschaftsingenieurwesen (Master)
Head of SYSiDAT Lab
Teaching and research activities on methods of statistics, artificial intelligence and machine learning with application to the digital environment of industry and logistics and industrial data analysis.
News
Research Topics
- Predictive Maintenance with Methods of Machine Learning and Artificial Intelligence
- Predictive Analytics
- Business Processes AI
- Industrial Analytics
"Predictive Process and Business Analytics, Artificial Intelligence and Industrial Analytics are the technologies shaping the new business world of the future." (Kurt Schwindl)
Teaching Areas
Subject Areas
- Process optimization on the basis of statistical methods
- Material Flow Systems / Technical Logistics
- Industrial Data Analysis / Business Analytics
- Machine Learning
- Application of Artificial Intelligence in Industry 4.0 Environment
- Systems Simulation
- Methods of quality assurance / quality management
- Quantitative methods
Career
Curriculum Vitae
since May 2014: Head of the laboratory for AI-based System Simulation, Machine Learning and Industrial Data Analytics (SYSiDAT). On basis of this institution, research and third-party-funded projects are performed in the fields of factory planning, material flow- and process optimization, based on AI-supported data analytics - among other things with the aid of different simulation environments in cooperation with partners from industry and universities.
since Nov 2013: Director of the Master’s Degree Programm in Business and Industrial Engineering within the course of studies Business & Industrial Engineering at the University of Applied Sciences Würzburg-Schweinfur
Oct 2013 - Feb 2014: External lectureship for the department “Operations Research” at TU Darmstadt; representation of the former lecture of Prof. Dr. em. Wolfgang Domschke
since Jan 2013: Subject Editor of Applied Mathematical Modelling [see also a short biography at Elsevier - Journals - Applied Mathematical Modelling]
since Oct 2014 and between Oct 2011 and Sep 2013: Vice Dean of the Faculty of Business and Engineering at the University of Applied Sciences Würzburg-Schweinfurt
Dec 2009: Appointment as full professor for the teaching and research areas "Technical Logistics Systems" and ‘Process Optimization’ with effect from 01.03.2010 at the Faculty of Business and Engineering at the University of Applied Sciences Würzburg- Schweinfurt
Sep 2009 - Feb 2010: Lecturer at the Faculty of Business and Engineering at the University of Applied Sciences Würzburg-Schweinfurt
Jul 2009 - Dec 2009: Head of Quality, Process and Lean Management (Head of Department). In this function responsible for the introduction, maintenance and further development of the MAN SE production system for the total area of worldwide spare parts logistics at MAN Nutzfahrzeuge AG
Oct 2008 - Jun 2009: Module Manager Distribution Logistics in the area of cross-location international spare parts supply for MAN Nutzfahrzeuge AG; responsible for the leadership of 145 employees; parallel to this, project manager for the further development of the logistics center of the central spare parts warehouse, MAN Nutzfahrzeuge AG Munich, Dachau
Jan 2008 - Sep 2008: Head of process and quality management for spare parts logistics at MAN Nutzfahrzeuge AG; responsible for the continous development and optimization of the supply chain processes, in particular warehouse logistics and their technical material flow systems; project management for the reprogramming of the S7 control of an automated miniload warehouse; introduction of Toyota Production System methods and management of various Six Sigma projects
Jul 2006 - Dec 2007: Logistics planner for plant logistics at MAN Nutzfahrzeuge AG, Munich
Jun 2005 - Jul 2006: Process and quality manager for the planning, optimization and reorganization of the spare parts supply chain of the spare part center in Munich, Dachau; responsible for organizational development, initiation and implementation of CIP projects and for change and risk management for the introduction of SAP R/3 in the spare parts logistics of MAN Nutzfahrzeuge AG, Munich, Dachau
Apr 2004 - Jun 2005: Overall project manager for the introduction of a warehouse management system (WMS) across all locations at various european locations of MAN Nutzfahrzeuge AG within its spare parts logistics environment
Mar 2004 - Feb 2005: Lecturer at the University of Applied Sciences Munich, Faculty of Business Administration, as part of a teaching assignment in the field of ‘distribution logistics and intralogistics’ and ‘Algorithms in SAP APO'
Jun 2002 - Mar 2004: Process designer and sub-project manager for supply chain management and intralogistics as part of a larger SAP R/3 implementation project in the spare parts logistics area of MAN Nutzfahrzeuge AG, Munich
Nov 1997 - May 1999: Logistics planner for a mid-sized mechanical engineering company in the field of production logistics
University eductaion
May 2003 - Jul 2009: External doctorate at the Faculty of Economic Sciences of the Westfälische Wilhelms-Universität Münster in the field of Production Control / Production and Material Flow Optimization at the Institute of Business Informatics at the Chair of Quantitative Methods, Prof. Dr. rer. nat. Ulrich Müller-Funk (supervisor)
Jun 2002: Graduation to Diplom-Kaufmann (Univ.) after studying business administration at the University of Passau with a focus on business informatics, statistics, logistics and manufacturing management; diploma thesis on the topic of "setup time optimization in series production".
Jul 1994: After studying Physical Engineering with focus on "Technical Physics" at the University of Applied Sciences Munich, graduation to Diplom-Ingenieur (FH); Diploma thesis on "Capacitive acceleration sensors with pulse amplitude modulation" with SIEMENS AG Regensburg in the field of R&D Automotive, Airbag Sensors
in a nutshell:
Dr. Kurt Schwindl is a Professor of Quantitative Methods, Industrial Analytics and Management Sciences, at the Faculty of Business and Industrial Engineering at the University of Applied Sciences Würzburg-Schweinfurt, Germany. He received M.B.A. degrees in Technical Physics and Economic Sciences from University of Applied Sciences Munich and University of Passau and a Ph.D. from the University of Münster (Westfahlen, Germany) in Operations Research and Informations Systems. He has many years of practical experience as the head of department in the logistics area at MAN SE (Munich) in Process Optimization and Organization Consultancy and is recognized as an experienced Six Sigma Master Black Belt and leading expert in Analytical Process Optimization. His main research interests focus on Material Flow Optimization, quantitative and statistical Methods for planning and optimizing logistic processes, Computational and Artificial Intelligence in Technical Logistic Systems, Production Planning and Control (PPC), Natural Analogue Methods for Process Optimization, Autonomous Controlled Logistic Systems, Econophysics, and Machine Learning, Artificial Intelligence, Data Analytics all with the emphasis on logistics and manufacturing processes.
Multiscale Modeling
Multiscale modeling aims for descriptions of materials properties across length scales, starting with chemical processes via molecular dynamics to macroscopic properties such as thermal conductivities. Our expertise: we can simulate chemical, micro- and macroscopic dynamic processes under the influence of external fields, e.g. electric fields, such as those occuring in battery cells, electrolysis / fuel cells and insulating materials. The insight from the modeling results lead to targeted materials optimisation. A powerful computing cluster is available for the numerical implementation.
Methods
The partial differential equations of elasticity theory or (electro)hydrodynamics lead to macroscopic descriptions of solids and fluids. The corresponding materials constants are typically spatial average values or correlation functions of microscopic quantities.
In the case of electrolyte solutions, e.g. contaminated insulator oils or battery fluids, the Poisson-Nernst-Planck theory provides a mesoscopic description of the dynamics. This provides access to quantities such as the DC-conductivity or the impedance so that macroscopic RC models are dispensable.
A microscopic description of the spatial structure of non-uniform liquids on the length scale of molecular diameters is possible using classical density functional theory (DFT), within which, in partiular, short-range intermolecular interactions can be taken into account. This description on molecular length scales requires technically complex nonlinear integral equations, the solution of methods for which we have many years of experience in.
Chemical reactions, such as redox reactions at metal-fluid interfaces or dissociation reactions, are modeled in the working group by using quantum mechanical density functional theory (DFT), which can resolve the molecular structure on atomic length scales. This allows for the calculation of reaction rates and reaction paths, even under the influence of external E-fields.
Projects
First global modeling of the conductivity behavior of transformer oils from the molecule to the current curve
The properties of application-relevant material systems are often characterized by an interaction of processes on different length scales. For example, if the Joule heat from high-voltage transformers (dimensions 0.1-10 m) is to be dissipated using insulating oil, the latter is usually separated from the metal of the transformer windings using insulating paper (thickness 10-100 µm). The electric field present in the pores of the insulating paper (diameter 10-100 nm) leads to various molecular processes (chemical bond length 100 pm) such as redox reactions, field-enhanced dissociation and electrical breakdown. The correct functioning of the transformer is determined, among other things, by the quality of the oil, whose insulating properties can decrease over time due to the molecular processes mentioned.
In order to technically control (if necessary avoid) such changes in properties, a comprehensive understanding of the interplay of the processes relevant to materials science on the individual length scales is of crucial importance.

The greater the spatial separation of the occupied and unoccupied molecular orbitals under consideration, the more strongly the molecule is polarized by the electric field, which in turn causes the tendency to split into ionic compounds. At 100 kV/mm the strongest polarization results when the field acts parallel to the terminal bond (c).
Structure of ionic fluids on inhomogeneously charged surfaces
With the help of electric fields that arise between charged surfaces, the structure of fluids, i.e. the distribution of molecules, can be easily influenced, which can be used, e.g., to modify the interfacial tension (electrowetting) or to control chemical reactions (electrolysis or batteries). Since the concentration of ionic components in fluids can be tiny but it does not vanish exactly, electrostatic fields in the absence of currents are shielded inside the fluid. For uniform surface charge distributions, the relevant decay length is given by the Debye length λ, which depends on the ion concentration and which can be, e.g., 1 µm in pure water, many 100 µm in purified organic solvents and less than 1 nm in concentrated electrolyte solutions. The fundamental question arises as to how far an arrangement of fluid molecules created by a uniform distribution of surface charges can extend into the interior. Information about this distribution of fluid molecules is crucial, e.g., for the design of supercapacitor, in which the capacitive properties of the arrangement of ions close to the surface are exploited.

Contact
Prof. Dr. Kurt Schwindl-Braun
97421 Schweinfurt
Tuesday, 15.00h – 16.00 h ( 3 p.m. - 4 p.m.)
Programme Director of Wirtschaftsingenieurwesen (Master)
Head of SYSiDAT Lab
Teaching and research activities on methods of statistics, artificial intelligence and machine learning with application to the digital environment of industry and logistics and industrial data analysis.
News
Research Topics
- Predictive Maintenance with Methods of Machine Learning and Artificial Intelligence
- Predictive Analytics
- Business Processes AI
- Industrial Analytics
"Predictive Process and Business Analytics, Artificial Intelligence and Industrial Analytics are the technologies shaping the new business world of the future." (Kurt Schwindl)
Teaching Areas
Subject Areas
- Process optimization on the basis of statistical methods
- Material Flow Systems / Technical Logistics
- Industrial Data Analysis / Business Analytics
- Machine Learning
- Application of Artificial Intelligence in Industry 4.0 Environment
- Systems Simulation
- Methods of quality assurance / quality management
- Quantitative methods
Career
Curriculum Vitae
since May 2014: Head of the laboratory for AI-based System Simulation, Machine Learning and Industrial Data Analytics (SYSiDAT). On basis of this institution, research and third-party-funded projects are performed in the fields of factory planning, material flow- and process optimization, based on AI-supported data analytics - among other things with the aid of different simulation environments in cooperation with partners from industry and universities.
since Nov 2013: Director of the Master’s Degree Programm in Business and Industrial Engineering within the course of studies Business & Industrial Engineering at the University of Applied Sciences Würzburg-Schweinfur
Oct 2013 - Feb 2014: External lectureship for the department “Operations Research” at TU Darmstadt; representation of the former lecture of Prof. Dr. em. Wolfgang Domschke
since Jan 2013: Subject Editor of Applied Mathematical Modelling [see also a short biography at Elsevier - Journals - Applied Mathematical Modelling]
since Oct 2014 and between Oct 2011 and Sep 2013: Vice Dean of the Faculty of Business and Engineering at the University of Applied Sciences Würzburg-Schweinfurt
Dec 2009: Appointment as full professor for the teaching and research areas "Technical Logistics Systems" and ‘Process Optimization’ with effect from 01.03.2010 at the Faculty of Business and Engineering at the University of Applied Sciences Würzburg- Schweinfurt
Sep 2009 - Feb 2010: Lecturer at the Faculty of Business and Engineering at the University of Applied Sciences Würzburg-Schweinfurt
Jul 2009 - Dec 2009: Head of Quality, Process and Lean Management (Head of Department). In this function responsible for the introduction, maintenance and further development of the MAN SE production system for the total area of worldwide spare parts logistics at MAN Nutzfahrzeuge AG
Oct 2008 - Jun 2009: Module Manager Distribution Logistics in the area of cross-location international spare parts supply for MAN Nutzfahrzeuge AG; responsible for the leadership of 145 employees; parallel to this, project manager for the further development of the logistics center of the central spare parts warehouse, MAN Nutzfahrzeuge AG Munich, Dachau
Jan 2008 - Sep 2008: Head of process and quality management for spare parts logistics at MAN Nutzfahrzeuge AG; responsible for the continous development and optimization of the supply chain processes, in particular warehouse logistics and their technical material flow systems; project management for the reprogramming of the S7 control of an automated miniload warehouse; introduction of Toyota Production System methods and management of various Six Sigma projects
Jul 2006 - Dec 2007: Logistics planner for plant logistics at MAN Nutzfahrzeuge AG, Munich
Jun 2005 - Jul 2006: Process and quality manager for the planning, optimization and reorganization of the spare parts supply chain of the spare part center in Munich, Dachau; responsible for organizational development, initiation and implementation of CIP projects and for change and risk management for the introduction of SAP R/3 in the spare parts logistics of MAN Nutzfahrzeuge AG, Munich, Dachau
Apr 2004 - Jun 2005: Overall project manager for the introduction of a warehouse management system (WMS) across all locations at various european locations of MAN Nutzfahrzeuge AG within its spare parts logistics environment
Mar 2004 - Feb 2005: Lecturer at the University of Applied Sciences Munich, Faculty of Business Administration, as part of a teaching assignment in the field of ‘distribution logistics and intralogistics’ and ‘Algorithms in SAP APO'
Jun 2002 - Mar 2004: Process designer and sub-project manager for supply chain management and intralogistics as part of a larger SAP R/3 implementation project in the spare parts logistics area of MAN Nutzfahrzeuge AG, Munich
Nov 1997 - May 1999: Logistics planner for a mid-sized mechanical engineering company in the field of production logistics
University eductaion
May 2003 - Jul 2009: External doctorate at the Faculty of Economic Sciences of the Westfälische Wilhelms-Universität Münster in the field of Production Control / Production and Material Flow Optimization at the Institute of Business Informatics at the Chair of Quantitative Methods, Prof. Dr. rer. nat. Ulrich Müller-Funk (supervisor)
Jun 2002: Graduation to Diplom-Kaufmann (Univ.) after studying business administration at the University of Passau with a focus on business informatics, statistics, logistics and manufacturing management; diploma thesis on the topic of "setup time optimization in series production".
Jul 1994: After studying Physical Engineering with focus on "Technical Physics" at the University of Applied Sciences Munich, graduation to Diplom-Ingenieur (FH); Diploma thesis on "Capacitive acceleration sensors with pulse amplitude modulation" with SIEMENS AG Regensburg in the field of R&D Automotive, Airbag Sensors
in a nutshell:
Dr. Kurt Schwindl is a Professor of Quantitative Methods, Industrial Analytics and Management Sciences, at the Faculty of Business and Industrial Engineering at the University of Applied Sciences Würzburg-Schweinfurt, Germany. He received M.B.A. degrees in Technical Physics and Economic Sciences from University of Applied Sciences Munich and University of Passau and a Ph.D. from the University of Münster (Westfahlen, Germany) in Operations Research and Informations Systems. He has many years of practical experience as the head of department in the logistics area at MAN SE (Munich) in Process Optimization and Organization Consultancy and is recognized as an experienced Six Sigma Master Black Belt and leading expert in Analytical Process Optimization. His main research interests focus on Material Flow Optimization, quantitative and statistical Methods for planning and optimizing logistic processes, Computational and Artificial Intelligence in Technical Logistic Systems, Production Planning and Control (PPC), Natural Analogue Methods for Process Optimization, Autonomous Controlled Logistic Systems, Econophysics, and Machine Learning, Artificial Intelligence, Data Analytics all with the emphasis on logistics and manufacturing processes.
Numerical Simulation
The team of the thematic field of numerical simulation deals with the development and implementation of reliable and efficient algorithms for the numerical treatment of innovative non-classical material laws and with the integration of such algorithms into the framework of existing general simulation software systems. The current focus of work is on memory-based material models, such as models for viscoelastic materials (polymers, biological tissue, etc.) based on differential equations of fractional order. The use of our algorithms allows users, particularly from structural mechanics and related areas, to precisely predict the behavior of the components they have designed and to optimize the design of these components.
Methods

The finite element method is an established and well-understood standard tool for simulating structural mechanical processes. In order to use the method in practice, one needs software systems that, in addition to the general mathematical framework, also incorporate the material laws of those materials that are represented in the structures to be simulated. While corresponding material algorithms exist for numerous established material classes, this is e.g. hardly the case for viscoelastic materials. An important aspect here is that proven mathematical models for such materials exhibit memory effects, i.e. the current state of deformation depends not only on the current load, but on the entire previous history. This is a significant difference to common material models which has significant software engineering implications for the algorithms to be used.
In view of this background, the Numerical Simulation team is concerned with the development and implementation of numerical methods with which such memory-based models can be treated reliably and efficiently. The current focus of work is on mathematical models based on differential equations of fractional (i.e. non-integer) order. Experience has shown that such models are particularly well suited to accurately describing the behavior of viscoelastic materials over longer periods of time. From a theoretical point of view, the so-called diffusive representation of the occurring differential and integral operators has significant advantages because, compared to traditional representations, it leads to algorithms that require less computing time, have a significantly lower memory requirement for handling the process history and can be integrated into existing, proven finite element packages with little software effort.
Projects
ProVerB
As part of the ProVerB joint project funded by the BMBF from 2018 to 2021, we developed material models for the behavior of concrete over extremely long periods of time together with the Gesellschaft für numerische Simulation mbH (Braunschweig) and the Institute for Nonlinear Mechanics at the University of Stuttgart. The background was the use of concrete as a material to produce barriers and closure systems for final storage sites for radioactive waste.
MuSiK
As part of the MuSiK joint project, which began in 2022 and is expected to run until 2025 and is also funded by the BMBF, we are once again devoting ourselves, together with the Institute for Nonlinear Mechanics at the University of Stuttgart, to the development of material models and associated numerical methods for the description of fiber-reinforced plastics and synthetic resins. The specific application here is reinforcing bars to be made from such materials for concrete in building construction and civil engineering, which are intended to serve as a replacement for the steel reinforcements previously used. Because fiber-reinforced plastics are substantially less susceptible to corrosion than structural steel, the service life of structures constructed with them can be significantly increased in this way.
Contact
Prof. Dr. Kurt Schwindl-Braun
97421 Schweinfurt
Tuesday, 15.00h – 16.00 h ( 3 p.m. - 4 p.m.)
Programme Director of Wirtschaftsingenieurwesen (Master)
Head of SYSiDAT Lab
Teaching and research activities on methods of statistics, artificial intelligence and machine learning with application to the digital environment of industry and logistics and industrial data analysis.
News
Research Topics
- Predictive Maintenance with Methods of Machine Learning and Artificial Intelligence
- Predictive Analytics
- Business Processes AI
- Industrial Analytics
"Predictive Process and Business Analytics, Artificial Intelligence and Industrial Analytics are the technologies shaping the new business world of the future." (Kurt Schwindl)
Teaching Areas
Subject Areas
- Process optimization on the basis of statistical methods
- Material Flow Systems / Technical Logistics
- Industrial Data Analysis / Business Analytics
- Machine Learning
- Application of Artificial Intelligence in Industry 4.0 Environment
- Systems Simulation
- Methods of quality assurance / quality management
- Quantitative methods
Career
Curriculum Vitae
since May 2014: Head of the laboratory for AI-based System Simulation, Machine Learning and Industrial Data Analytics (SYSiDAT). On basis of this institution, research and third-party-funded projects are performed in the fields of factory planning, material flow- and process optimization, based on AI-supported data analytics - among other things with the aid of different simulation environments in cooperation with partners from industry and universities.
since Nov 2013: Director of the Master’s Degree Programm in Business and Industrial Engineering within the course of studies Business & Industrial Engineering at the University of Applied Sciences Würzburg-Schweinfur
Oct 2013 - Feb 2014: External lectureship for the department “Operations Research” at TU Darmstadt; representation of the former lecture of Prof. Dr. em. Wolfgang Domschke
since Jan 2013: Subject Editor of Applied Mathematical Modelling [see also a short biography at Elsevier - Journals - Applied Mathematical Modelling]
since Oct 2014 and between Oct 2011 and Sep 2013: Vice Dean of the Faculty of Business and Engineering at the University of Applied Sciences Würzburg-Schweinfurt
Dec 2009: Appointment as full professor for the teaching and research areas "Technical Logistics Systems" and ‘Process Optimization’ with effect from 01.03.2010 at the Faculty of Business and Engineering at the University of Applied Sciences Würzburg- Schweinfurt
Sep 2009 - Feb 2010: Lecturer at the Faculty of Business and Engineering at the University of Applied Sciences Würzburg-Schweinfurt
Jul 2009 - Dec 2009: Head of Quality, Process and Lean Management (Head of Department). In this function responsible for the introduction, maintenance and further development of the MAN SE production system for the total area of worldwide spare parts logistics at MAN Nutzfahrzeuge AG
Oct 2008 - Jun 2009: Module Manager Distribution Logistics in the area of cross-location international spare parts supply for MAN Nutzfahrzeuge AG; responsible for the leadership of 145 employees; parallel to this, project manager for the further development of the logistics center of the central spare parts warehouse, MAN Nutzfahrzeuge AG Munich, Dachau
Jan 2008 - Sep 2008: Head of process and quality management for spare parts logistics at MAN Nutzfahrzeuge AG; responsible for the continous development and optimization of the supply chain processes, in particular warehouse logistics and their technical material flow systems; project management for the reprogramming of the S7 control of an automated miniload warehouse; introduction of Toyota Production System methods and management of various Six Sigma projects
Jul 2006 - Dec 2007: Logistics planner for plant logistics at MAN Nutzfahrzeuge AG, Munich
Jun 2005 - Jul 2006: Process and quality manager for the planning, optimization and reorganization of the spare parts supply chain of the spare part center in Munich, Dachau; responsible for organizational development, initiation and implementation of CIP projects and for change and risk management for the introduction of SAP R/3 in the spare parts logistics of MAN Nutzfahrzeuge AG, Munich, Dachau
Apr 2004 - Jun 2005: Overall project manager for the introduction of a warehouse management system (WMS) across all locations at various european locations of MAN Nutzfahrzeuge AG within its spare parts logistics environment
Mar 2004 - Feb 2005: Lecturer at the University of Applied Sciences Munich, Faculty of Business Administration, as part of a teaching assignment in the field of ‘distribution logistics and intralogistics’ and ‘Algorithms in SAP APO'
Jun 2002 - Mar 2004: Process designer and sub-project manager for supply chain management and intralogistics as part of a larger SAP R/3 implementation project in the spare parts logistics area of MAN Nutzfahrzeuge AG, Munich
Nov 1997 - May 1999: Logistics planner for a mid-sized mechanical engineering company in the field of production logistics
University eductaion
May 2003 - Jul 2009: External doctorate at the Faculty of Economic Sciences of the Westfälische Wilhelms-Universität Münster in the field of Production Control / Production and Material Flow Optimization at the Institute of Business Informatics at the Chair of Quantitative Methods, Prof. Dr. rer. nat. Ulrich Müller-Funk (supervisor)
Jun 2002: Graduation to Diplom-Kaufmann (Univ.) after studying business administration at the University of Passau with a focus on business informatics, statistics, logistics and manufacturing management; diploma thesis on the topic of "setup time optimization in series production".
Jul 1994: After studying Physical Engineering with focus on "Technical Physics" at the University of Applied Sciences Munich, graduation to Diplom-Ingenieur (FH); Diploma thesis on "Capacitive acceleration sensors with pulse amplitude modulation" with SIEMENS AG Regensburg in the field of R&D Automotive, Airbag Sensors
in a nutshell:
Dr. Kurt Schwindl is a Professor of Quantitative Methods, Industrial Analytics and Management Sciences, at the Faculty of Business and Industrial Engineering at the University of Applied Sciences Würzburg-Schweinfurt, Germany. He received M.B.A. degrees in Technical Physics and Economic Sciences from University of Applied Sciences Munich and University of Passau and a Ph.D. from the University of Münster (Westfahlen, Germany) in Operations Research and Informations Systems. He has many years of practical experience as the head of department in the logistics area at MAN SE (Munich) in Process Optimization and Organization Consultancy and is recognized as an experienced Six Sigma Master Black Belt and leading expert in Analytical Process Optimization. His main research interests focus on Material Flow Optimization, quantitative and statistical Methods for planning and optimizing logistic processes, Computational and Artificial Intelligence in Technical Logistic Systems, Production Planning and Control (PPC), Natural Analogue Methods for Process Optimization, Autonomous Controlled Logistic Systems, Econophysics, and Machine Learning, Artificial Intelligence, Data Analytics all with the emphasis on logistics and manufacturing processes.
