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Johannes_Fisel

M.Sc. Johannes Fisel

Akad. Mitarbeiter
Bereich: Produktionssysteme
Sprechstunden: nach Vereinbarung
Raum: 116, Geb. 50.36
Tel.: +49 721 608-44153
Fax: +49 721 608-45005
Johannes FiselDfc2∂kit edu

 Campus Süd



M.Sc. Johannes Fisel

Allgemeine Aufgaben:

  • Koordinator der Vorlesung: Integrierte Produktionsplanung
  • Vorlesungsbetreuung Production Engineering (Hector School)

 

Forschungs- und Arbeitsgebiete:

  • Wandlungsfähige Produktions- und Montagekonzepte
  • Produktionstechnik für zukünftige Antriebssysteme (u. a. Elektromobilität)

 

Projekte:

  • EFFECT 360° - Energieeffiziente und flexibel industriell herstellbare Elektrofahrzeugantriebe
  • GreenREX - Elektrofahrzeug mit regenerativ betriebenem On-Board-Energiewandler in Form eines monovalenten Erdgasmotors

Veröffentlichungen

[ 1 ] Peters, S.; Hochdörffer, J. & Fisel, J. (2015), „Estimating production costs under uncertainty using a prognosis model for stochastic input data “. Technical Presentation, Hrsg. CIRP General Assembly - STC O, S. 1-10.
Abstract:
In the early stages of product development, information is often uncertain, especially when dealing with innovative technologies in the area of electric mobility. This paper presents a stochastic model for the estimation of production costs that allows for taking uncertain information as well as correlations between various cost types into account. The model is based on the principles of Monte Carlo Simulation and is able to flexibly adapt to a given database.

[ 2 ] Fisel, J. & Lanza, G. (2016), „Planning approach for a changeable multi model assembly system“. Proceedings of 6th international Electric Drives Production Conference , Hrsg. EDPC, S. 212-216.
Abstract:
The overall market trend depicts an increasing demand for electric or hybrid vehicles. This demand cannot be predicted precisely because of volatile influencing factors. Automotive companies are therefore confronted with the challenge of rapidly adapting their production systems accordingly. An approach to handle the variety of models within final assembly is to establish mixed model assembly lines. The subsequent integration of vehicles using alternative propulsion concepts into single model assembly lines stands as a great challenge in final assembly. Within this paper, an approach for the greenfield planning of assembly lines using the concept of changeability is presented. The approach focusses on the integration of a new propulsion concept in an existing assembly line. Hereto, the line allocation problem is solved for a fixed production volume ratio using an optimization algorithm. Thereafter, the production volume ratios are varied in order to identify an optimal solution for line balancing and assembly equipment.

[ 3 ] Fisel, J.; Arslan, A. & Lanza, G. (2017), „Changeability focused planning method for multi model assembly systems in automotive industry“. Manufacturing Systems 4.0 – Proceedings of the 50th CIRP Conference on Manufacturing Systems, Hrsg. CIRP CMS, S. 515-520.
Abstract:
Series vehicle production is designed to produce effectively at a defined number of vehicles per period. Regarding market forecasts the overall market trend depicts an increasing demand for electrified vehicles within an uncertain propulsion concept vehicle mix. This demand cannot be predicted precisely because of volatile influencing factors such as governmental subsidies. Automotive companies are therefore confronted with the challenge of rapidly adapting their production systems accordingly. An approach to handle the variety of models within vehicle final assembly is to establish mixed model assembly lines. Since single model assembly lines are optimized for a specific production volume of one model, the subsequent integration of vehicles using alternative propulsion concepts into single model assembly lines stands as a great challenge in final assembly. Moreover, producing with optimal configured assembly systems after integrating an additional model is not ensured further on. To address this challenge, an approach for the greenfield planning of assembly lines using the concept of changeability is presented within this paper. The presented approach offers a new method to cover uncertainty regarding the future propulsion concept mix of assembly lines. This affects the initial setup of an assembly line concerning the line balancing and assembly equipment as possible subsequent changes to the assembly system increase costs. The target conflict is to minimize changes to the assembly system due to the integration of further propulsion concepts while ensuring cost efficient assembly. Hereto, the line balancing problem is solved for a fixed production volume ratio using a developed optimization algorithm. Thereafter, the production volume ratios are varied in order to identify an optimal solution for line balancing and assembly equipment. The uncertainty of volume ratios is considered in the integrated costs calculation module.