Details
| Original language | English |
|---|---|
| Pages (from-to) | 570-575 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 1 |
| Publication status | Published - 1998 |
| Externally published | Yes |
| Event | 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 1 (of 5) - San Diego, CA, USA Duration: 11 Oct 1998 → 14 Oct 1998 |
Abstract
In this paper we investigate the kanban assignment problem for assembly kanban systems. We use REMO, a general purpose tool for optimization. REMO includes several algorithms like hill climbing and genetic algorithms and has an easily adaptable interface to performance analysis tools. As we try to find an optimal kanban assignment with respect to certain performance measures of the system, a fast performance analysis is a crucial factor for sensible and successful application of optimization algorithms. For this purpose we introduce Petri Nets including Queueing Nets (PNiQ) as modeling formalism especially suited for optimization of arbitrary kanban systems. At modeling level, PNiQ allow the use of both the concise description of queueing nets where possible and the notation of stochastic Petri nets where needed, e.g. to model fork/join needed for the matching of kanbans and parts. Approximate performance analysis is carried out by decomposition and aggregation of the queueing net parts. This technique provides a fast numerical solution even for large systems as important requirement for the application of optimization algorithms. The optimization not only yields optimal kanban assignments for various kanban systems but also a common pattern in the set of solutions can be recognized.
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Hardware and Architecture
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Vol. 1, 1998, p. 570-575.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Modeling and optimization of kanban controlled manufacturing systems with GSPN including QN
AU - Becker, Matthias
AU - Szczerbicka, Helena
PY - 1998
Y1 - 1998
N2 - In this paper we investigate the kanban assignment problem for assembly kanban systems. We use REMO, a general purpose tool for optimization. REMO includes several algorithms like hill climbing and genetic algorithms and has an easily adaptable interface to performance analysis tools. As we try to find an optimal kanban assignment with respect to certain performance measures of the system, a fast performance analysis is a crucial factor for sensible and successful application of optimization algorithms. For this purpose we introduce Petri Nets including Queueing Nets (PNiQ) as modeling formalism especially suited for optimization of arbitrary kanban systems. At modeling level, PNiQ allow the use of both the concise description of queueing nets where possible and the notation of stochastic Petri nets where needed, e.g. to model fork/join needed for the matching of kanbans and parts. Approximate performance analysis is carried out by decomposition and aggregation of the queueing net parts. This technique provides a fast numerical solution even for large systems as important requirement for the application of optimization algorithms. The optimization not only yields optimal kanban assignments for various kanban systems but also a common pattern in the set of solutions can be recognized.
AB - In this paper we investigate the kanban assignment problem for assembly kanban systems. We use REMO, a general purpose tool for optimization. REMO includes several algorithms like hill climbing and genetic algorithms and has an easily adaptable interface to performance analysis tools. As we try to find an optimal kanban assignment with respect to certain performance measures of the system, a fast performance analysis is a crucial factor for sensible and successful application of optimization algorithms. For this purpose we introduce Petri Nets including Queueing Nets (PNiQ) as modeling formalism especially suited for optimization of arbitrary kanban systems. At modeling level, PNiQ allow the use of both the concise description of queueing nets where possible and the notation of stochastic Petri nets where needed, e.g. to model fork/join needed for the matching of kanbans and parts. Approximate performance analysis is carried out by decomposition and aggregation of the queueing net parts. This technique provides a fast numerical solution even for large systems as important requirement for the application of optimization algorithms. The optimization not only yields optimal kanban assignments for various kanban systems but also a common pattern in the set of solutions can be recognized.
UR - http://www.scopus.com/inward/record.url?scp=0032279747&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:0032279747
VL - 1
SP - 570
EP - 575
JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
SN - 0884-3627
T2 - 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 1 (of 5)
Y2 - 11 October 1998 through 14 October 1998
ER -