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M.Sc. Sina Helming

Research Associate
Production Systems
office hours: To be agreed
room: 107, Geb. 50.36
phone: +49 721 608-44297
fax: +49 721 608-45005
Sina HelmingSzb1∂kit edu

76131 Karlsruhe
Kaiserstraße 12


M.Sc. Sina Helming

Area of Research:

  • Global Production Strategies
  • Design of Global Production Networks
  • Integrated Production and Logistics Planning

 

General Tasks:

  • Coordinaiton of lecture „Globale Produktion“
  • Coordination of workshop series „Working Methods in Mechanical Engineering“ at Carl Benz School of Engineering
  • Coordination of lecture „Global Production“ at Hector School

 

Projects:

  • ProRegio – Customer-driven design of product-services and production networks to adapt to regional market requirements
  • FlexPLN – Research into modeling and software technology for flexible and integrated production and logistics planning in dynamic networks


Curriculum Vitae:

10/2010 - 03/2017 Study of Industrial Engineering & Management at Karlsruhe Institute of Technology (KIT)
Since 04/2017 Research Associate at the Institute of Production Science (wbk) at Karlsruhe Institute of Technology (KIT)

Publications

[ 1 ] Lux, E.; Adam, M.; Dorner, V.; Helming, S.; Knierim, M. & Weinhardt, C. (2018), "Live Biofeedback as a User Interface Design Element: A Review of the Literature", Communications of the Association for Information Systems, pp. 257-296. 10.17705/1CAIS.04318
Abstract:
With the advances in sensor technology and real-time processing of neurophysiological data, a growing body of academic literature has begun to explore how live biofeedback can be integrated into information systems for everyday use. While researchers have traditionally studied live biofeedback in the clinical domain, the proliferation of affordable mobile sensor technology enables researchers and practitioners to consider live biofeedback as a user interface element in contexts such as decision support, education, and gaming. In order to establish the current state of research on live biofeedback, we conducted a literature review on studies that examine self and foreign live biofeedback based on neurophysiological data for healthy subjects in an information systems context. By integrating a body of highly fragmented work from computer science, engineering and technology, information systems, medical science, and psychology, this paper synthesizes results from existing research, identifies knowledge gaps, and suggests directions for future research. In this vein, this review can serve as a reference guide for researchers and practitioners on how to integrate self and foreign live biofeedback into information systems for everyday use.

[ 2 ] Buergin, J.; Helming, S.; Blaettchen, P.; Schweizer, Y.; Bitte, F.; Haefner, B. & Lanza, G. (2018), "Local order scheduling for mixed-model assembly lines in the aircraft manufacturing industry", Production Engineering Research and Development, pp. 1-9.
Abstract:
Multi-variant products to be assembled on mixed-model assembly lines at locations within a production network need to be scheduled locally. Scheduling is a highly complex task especially if it simultaneously covers the assignment of orders, which are product variants to be assembled within a production period, to assembly lines as well as their sequencing on the lines. However, this is required if workers can flexibly fulfill tasks across stations of several lines and, thus, capacity of workers is shared among the lines. As this is the case for final assembly of the Airbus A320 Family, this paper introduces an optimization model for local order scheduling for mixed-model assembly lines covering both assignment to lines as well as sequencing. The model integrates the planning approaches mixed-model sequencing and level scheduling in order to minimize work overload in final assembly and to level material demand with regard to suppliers. The presented model is validated in the industrial application of the final assembly of the Airbus A320 Family. The results demonstrate significant improvement in terms of less work overload and a more even material demand compared to current planning.