Christoph Roser
ABSTRACT
The performance of a manufacturing or logistic system is determined by its constraints. Therefore, in order to improve the performance, it is necessary to improve the constraints, also known as the bottlenecks. Finding the bottlenecks, however, is not easy. This paper compares the two most common bottleneck detection methods, based on the utilization and the waiting time, with the shifting bottleneck detection method developed by us, for AGV systems. We find that the two conventional methods have many shortcomings compared to the shifting bottleneck detection method. In the example presented here, conventional methods are either unable to detect the bottleneck at all or detect the bottleneck incorrectly. The shifting bottleneck detection method not only finds the bottlenecks but also determines the magnitude of the primary and secondary bottlenecks.
- Blackstone, J. H. 2001. Theory of constraints - a status report. International Journal of Production Research, 39(6): 1053--1080.Google Scholar
Cross Ref
- Bukchin, J. 1998. A comparative study of performance measures for throughput of a mixed model assembly line in a JIT environment. International Journal of Production Research, 36(10): 2669--2685.Google ScholarCross Ref
- Chiang, S. -Y., Kuo, C. -T., and Meerkov, S. M. 1998. Bottlenecks in Markovian Production Lines: A Systems Approach. IEEE Transactions on Robotics and Automation, 14(2): 352--359.Google ScholarCross Ref
- Chiang, S. -Y., Kuo, C. -T., and Meerkov, S. M. 2000. DT-Bottlenecks in Serial Production Lines: Theory and Application. IEEE Transactions on Robotics and Automation, 16(5): 567--580.Google ScholarCross Ref
- Chiang, S. -Y., Kuo, C. -T., and Meerkov, S. M. 2002. c-Bottlenecks in Serial Production Lines: Identification and Application. Mathematical Problems in Engineering, to appear 2002.Google Scholar
- Delp, D., Si, J., Hwang, Y., and Pei, B. 2003. A Dynamic System Regulation Measure for Increasing Effective Capacity: the X-Factor Theory. In IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop (ASMC), ed., Munich, Germany.Google Scholar
- Goldratt, E. M. 1992. The Goal: A Process of Ongoing Improvement. North River Press.Google Scholar
- Kuo, C. -T., Lim, J. -T., and Meerkov, S. M. 1996. Bottlenecks in Serial Production Lines: A System-Theoretic Approach. Mathematical Problems in Engineering, 2: 233--276.Google ScholarCross Ref
- Lawrence, S. R., and Buss, A. H. 1995. Economic Analysis of Production Bottlenecks. Mathematical Problems in Engineering, 1(4): 341--369.Google ScholarCross Ref
- Li, J., and Meerkov, S. M. 2000. Bottlenecks with Respect to Due-Time Performance in Pull Serial Production Lines. Mathematical Problems in Engineering, 5: 479--498.Google ScholarCross Ref
- Luthi, J. 1998. Interval Matrices for the Bottleneck Analysis of Queueing Network Models with Histogram-Based Parameters. In IEEE International Computer Performance & Dependability Symposium, 142--151, Durham, NC, USA: IEEE Computer Society Press.Google Scholar
- Luthi, J., and Haring, G. 1997. Bottleneck Analysis for Computer and Communication Systems with Workload Variabilities & Uncertainties. In Proceedings of 2nd International Symposium on Mathematical Modelling, ed. I. Troch and F. Breitenecker, 525--534, Vienna, Austria.Google Scholar
- Nakano, M., Sugiura, N., Tanaka, M., and Kuno, T. 1994. ROPSII: Agent Oriented Manufacturing Simulator on the basis of Robot Simulator. In Japan-USA Symposium on Flexible Automation, 201--208, Kobe, Japan.Google Scholar
- Roser, C., Nakano, M., and Tanaka, M. 2001. A Practical Bottleneck Detection Method. In Winter Simulation Conference, ed. B. A. Peters, J. S. Smith, D. J. Medeiros, and M. W. Rohrer, 949--953, Arlington, Virginia, USA: Institute of Electrical and Electronics Engineers. Google ScholarDigital Library
- Roser, C., Nakano, M., and Tanaka, M. 2002a. Shifting Bottleneck Detection. In Winter Simulation Conference, ed. E. Yucesan, C. -H. Chen, J. L. Snowdon, and J. M. Charnes, 1079--1086, San Diego, CA, USA. Google ScholarDigital Library
- Roser, C., Nakano, M., and Tanaka, M. 2002b. Tracking Shifting Bottlenecks. In Japan-USA Symposium on Flexible Automation, 745--750, Hiroshima, Japan.Google Scholar
Recommendations
The LRPD test: speculative run-time parallelization of loops with privatization and reduction parallelization
Current parallelizing compilers cannot identify a significant fraction of parallelizable loops because they have complex or statically insufficiently defined access patterns. As parallelizable loops arise frequently in practice, we advocate a novel ...
The I Test: An Improved Dependence Test for Automatic Parallelization and Vectorization
The I test is a subscript dependence test which extends both the range of applicability and the accuracy of the GCD and Banerjee tests (U. Banerjee, 1976), standard subscript dependence tests used to determine whether loops may be parallelized/...
The R-LRPD Test: Speculative Parallelization of Partially Parallel Loops
IPDPS '02: Proceedings of the 16th International Parallel and Distributed Processing SymposiumCurrent parallelizing compilers cannot identify a significant fraction of parallelizable loops because they have complex or statically insufficiently defined access patterns. In our previously proposed framework we have speculatively executed a loop as ...
Comments