A Comparison of Current and Alternative Production Characteristics of a Flow Line: Case Study in a Yarn Producer’s Packaging Unit

Yıl 2019, Cilt: 7 Sayı: 1, 15 - 21, 31.03.2019

Utku Köker , Halil İbrahim Koruca , Samia Chehbi - Gamoura

Öz

Production
lines are consecutively placed machines designed to obtain short cycle times
with high speeds. This type of flow line is preferred when the demand pattern
occurs in high volumes from the same product in short production periods.  The structure of production systems is
directly related to the quantity and variety of the demand.  If the overall demand is made up of an
identical product in high amounts in a short period of time, flow lines are
designed to answer this need in a manner of consecutive linear machines,
capable of performing one or more tasks per machine.  Production with low cost and right quantity
conditions is also an obligation under timely constraints. A packaging station
of a five machine Bernoulli line is modelled in this paper. Two alternative
packaging materials are put into consideration against a readily used material
and those 3 packaging films are compared according to the performance
characteristics. A C# programme is coded to obtain the statistical performance
characteristics of an aggregation method applied to the “Bernoulli flow line”
to make a decision on which material is to be selected. Production rates,
blockages, starvations as well as work in process stocks are the performance
values calculated by the C# code developed, according to an aggregation method.
One of the two competing alternatives is selected after analyzing the outcomes
of the software.

Anahtar Kelimeler

Automatic production systems, inventory management, maintenance and repair times

Kaynakça

• S.M. Meerkov and J. Li, Production Systems Engineering, Springer, pp. 80-87, 545-587, 2008.
• H.T. Papadopoulos, C. Heavy and J. Browne, Queueing Theory in Manufacturing Systems Analysis and Design, Chapman & Hill, London, UK, 1993.
• T. Altiok, Performance Analysis of Manufacturing Systems, Springer-Verlag, New York, 1997
• M.J. Smith and B. Tan. Handbook of Stochastic Models and Analysis of Manufacturing System Operations, Springer-Verlag New York, pp. 73. 2013.
• Groover, Mikell P., Automation production systems and computer-integrated manufacturing, Fourth edition, Pearson Higher Education, Upper Saddle River, New Jersey, pp.441, 2015.
• S. Mocanu, “Numerical algorithms for transient analysis of fluid queues”, Fifth International Conference on the Analysis of Manufacturing Systems, Zakymthos, Greece, 2005.
• S. Biller, S.P. Marin, S.M. Meerkov. and L. Zhang, “Closed Bernoulli production lines: analysis, continuous improvement, and leaness”. IEEE Transactions on Automation Science and Engineering, vol. 6, no. 1, pp. 168-180, 2009.
• P.R. Kumar, “Re-entrant lines,” Queueing Syst. Theory Appl., vol. 13,no. 1–3, pp. 87–110, 1993.
• S. Kumar and P.R. Kumar, “Fluctuation smoothing policies are stable for stochastic re-entrant lines,” Discrete Event Dyn. Syst., Theory Applicat., vol. 6, no. 4, pp. 361–370, 1996.
• P. Fernandes, M.E.J. O’Kelly and A. Sales, “Analysis of exponential unreliable production lines using Kronecker descriptors”, Stochastic Models Of Manufacturing And Service Operations, 2013.
• J.A. Buzacott, “The effect of station breakdowns and random processing times on the capacity of flow lines with in-process storage”, AIIE Transactions, vol. 4, no. 4, pp. 308-313, 1972.
• S.B. Gershwin and O. Berman, “Analysis of transfer lines consisting of two unreliable machines with random processing times and _nite storage buffers”, AIIE Transactions, vol. 13, no. 1, pp. 2-11, 1981.
• S.B. Gershwin and I.C. Schick, “Modeling and analysis of three-stage transfer lines with unreliable machines and finite buffers”, Operations Research, vol. 3, no. 2, pp. 354-380, 1983.
• T. Altiok, “Production lines with phase-type operations and repair times and finite buffers”, International Journal of Production Research 23(3), pp. 489-498, 1985.
• C. Heavey, H.T. Papadopoulos and J. Browne, “The throughput rate of multistation unreliable production lines”, European Journal of Operational Research, Vol. 68, pp. 69-89 S.B. Gershwin (1987), “An efficient decomposition method for the approximate evaluation of tandem queues with finite storage space and blocking”, Operations Research, vol. 35, no. 2, pp. 291-305., 1993.
• F.C. Hillier and K.C. So, “On the simultaneous optimization of server and work allocations in production line systems with variable processing times”, Operations Research, vol. 44, no. 3, pp. 435-443, 1996.
• S.B. Gershwin, “An efficient decomposition method for the approximate evaluation of tandem queues with finite storage space and blocking”, Operations Research, vol. 35, no. 2, pp. 291-305, 1987.
• T. Tolio, A. Matta, F. Jovane, “A Method For Performance Evaluation of Automated Flow Lines”, CIRP Annals vol. 47, no. 1, pp. 373-376, 1998.
• H. Kuhn, “Analysis of automated flow line systems with repair crew interference”, In S.B. Gershwin, Y. Dallery, C.T. Papadopoulos and J. MacGregor Smith, Editors, Analysis and Modeling of Manufacturing Systems, Kluwer Academic Publishers, pp. 155-179, 2003.
• J.T. Lim, S.M. Meerkov and F. Top, “Homogeneous, asymptotically reliable serial production lines: theory and a case study”, IEEE Transactions on Automatic Control, vol. 35, no. 5, pp. 534-534, 1990.
• Patchong and D. Willaeys, “Modeling and Analysis of an Unreliable Flow Line Composed Of Parallel-Machine Stages”, IIE Transactions, vol. 33, pp. 559-568, 2001.
• Ancelin and A. Semery, “Calcul de la productivite d’une ligne integree de fabrication: CALIF, une methode”, RAIRO APII 21 (3), pp. 209-238 analytique industrielle, 1987.
• M.H. Burman, New Results in Flow Line Analysis. Thesis (PhD). OR Center, MIT, 1995
• A.C. Diamantidis, C.T. Papadopoulos and C. Heavey, Approximate analysis of serial flow lines with multiple parallel machine stations, IIE Transactions, vol. 39, no. 4, pp. 361-375, 2007.
• R. Levantesi, A. Matta and T. Tolio, “Performance evaluation of production lines with random processing times, multiple failure modes and finite buffer capacity- Part 1: the building block”, In S.B. Gershwin, Y. Dallery, C.T. Papadopoulos and J. MacGregor Smith, Editors, Analysis and Modeling of Manufacturing Systems, pp. 85-121, Kluwer Academic Publishers, 2003a..
• R. Levantesi, A. Matta and T. Tolio, “Performance evaluation of production lines with random processing times, multiple failure modes and finite buffer capacity- Part 1: decomposition”, In S.B. Gershwin, Y. Dallery, C.T. Papadopoulos and J. MacGregor Smith, Editors, Analysis and Modeling of Manufacturing Systems, pp. 85-121, Kluwer Academic Publishers, 2003b.
• T. Tolio, A. Matta and S.B. Gershwin, “Analysis of two-machine lines with multiple failure modes”, IIE Transactions, vol. 34, pp. 51-62, 2002.
• A.C. Diamantidis, C.T. Papadopoulos and M.I. Vidalis, “Exact analysis of a discrete material three station one buffer merge system with unreliable machines”, International Journal of Production Research, vol. 42, no. 4, pp. 651-675, 2004.
• S. Helber, “Performance Analysis of Flow Lines with Non-Linear Flow of Material”, Lecture Notes, Economics and Mathematical Systems, Springer-Verlag, vol. 473, 1999.
• B. Tan, “A three-station merge system with unreliable stations and a shared buffer”, Mathematical and Computer Modeling, vol. 33, pp. 1011-1026, 2001.
• S. Helber and N. Mehrtens, “Exact analysis of a continuous material merge system with limited buffer capacity and three stations”, In S.B. Gershwin, Y. Dallery, C.T. Papadopoulos and J. MacGregor Smith, Editors, Analysis and Modeling of Manufacturing Systems, pp. 85-121, Kluwer Academic Publishers, 2003.
• P. Buchholz, “Structured analysis approaches for large Markov chains”, Applied Numerical Mathematics, vol. 31, no. 4, 1999.
• D. Jacobs and S.M. Meerkov, “A system theoretic property of serial production lines: improvability”. International Journal of Systems Science, vol. 26, no. 4, pp. 755-785, 1995.
• Y. Liu and J. Li, “Modelling and analysis of split and merge production systems with Bernoulli reliability machines”, International Journal of Production Research, vol. 47, no. 16, pp. 4373-4397, 2009.
• J.A. Buzacott and J.G. Shanthikumar, Stochastic Models of Manufacturing Systems, Prentice Hall, Englewood Cliffs, NJ, 1993.
• Y. Dallery and S.B. Gershwin. “Manufacturing Flow Line Systems: a Review of Models and Analytical Results.” Queueing Syst vol. 12, no. 1–2, pp. 3–94, March 1992.