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Create Heijunka 5’s Matrix to Control the Dynamic Gemba as Lean Tool

Received: 3 April 2015     Accepted: 29 April 2015     Published: 13 May 2015
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Abstract

The heijunka tracking matrix has a direct impact on turn overtimes of the inventory to revamp existing orders as well as new technique, and increase the utilization of the inventory’ labors by eliminating the waste in transportation and over-processing actions. The tracking problem is interested in rearranging the location of VSM (e.g., items, pallets and stations) in a grouping of cellular aspect using 5’S concepts, which increase performance level. One of the successful recommendations used in this context is traveler salesman technique but with periodically update (i.e., Dynamic Gemba), it may be need reformulation. Its importance is the capture of work, information, and material (WIP, setup time, process time/unit, error rates, idle time, etc.) which is essential in quantifying and determining waste in terms of cost, delivery time and transportation frequency. This paper is interest in review the dynamic Gemba model to improve the inventory handling via modifying the traveler salesman model with aided proposed heuristic procedures, which are interested in arrange the inventory in minimum time and maximum flexibility in preparing the different orders. The Gemba tasks displayed via (Gemba KPI/DOE board) which contain cost and time information (NNVA: preparing tasks, VA: traveling||tracking tasks and NNVA: unloading tasks). The optimized cost and time analysis after reducing NNVA time and total VA time were sent to the central heijunka matrix. The methodology which includes elimination movements, motion and extra actions wastes are lean, and aim to increase the ability of prepare a lot of service in minimum time.

Published in Journal of Human Resource Management (Volume 3, Issue 2)
DOI 10.11648/j.jhrm.20150302.11
Page(s) 6-16
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Lean, Manufacturing Facility Layout, Gemba, Heijunka Cellular Manufacturing, KPI in Six-sigma

References
[1] Aiello G, Enea M, Galante G,. Multi-objective approach to facility layout problem by genetic search algorithm and Electre method. Robotics and Computer-Integrated Manufacturing, 22, 447–455.(2006)
[2] Aleisha EE, Lin L. For effectiveness facilities planning: Layout optimization then simulation, or vice versa? In Proceedings of the (2005).
[3] Asef-Vaziri A, Laporte G. Loop based facility planning and material handling. European Journal of Operational Research, 164 (1), 1–11, (2005).
[4] Bazargan-Lari M., Kaebernick H. Intra-cell and inter-cell layout designs for cellular manufacturing. International Journal of Industrial Engineering ± Applications and Practice 3,139±150, (1996).
[5] Bazargan-Lari M., Kaebernick H. An approach to the machine layout problem in a cellular manufacturing environment. Production Planning and Control 8(1), 41±55, (1997).
[6] Baykasoglu, A., Dereli, T., Sabuncu, I. An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems. Omega, 34(4), 385–396, (2006).
[7] VanCamp, D.J., Carter, M.W., and Vannelli, A. Anon-linear optimization approach for solving facility layout problems. European Journal of Operational Research57, 174±189,(1992).
[8] Heragu, S. S. Group technology and cellular manufacturing. IEEE Transactions on Systems, Man, and Cybernetics 24(2), (1994).
[9] Heragu, S.S. and Kusiak, A. Efficient models for the facility layout problem. European Journal of Operational Research 53,1±13,1991.
[10] Jumpup ^ Womack, Jim. Gemba Walks. Lean Enterprise Institute, Inc.p.348.ISBN978-1-934109-15-1,(2011).
[11] Jumpup^http://www.lean.org/BookStore/ProductDetails.cfm?SelectedProductId=320
[12] Jumpup ^ http://ajm.sagepub.com/content/27/4/352.extract
[13] Jumpup ^ Andrew Castle, Rachel Harvey. "Lean information management: the use of observational data in healthcare".InternationalJournalofProductivityandPerformanceManagement, Vol. 58 Iss: 3, pp. 280-299. ISSN 1741-0401., (2009)
[14] Jumpup ^ Mann, David W. (2005). Creating a lean culture; tools to sustain lean conversions. Productivity Press. p. 211. ISBN1563273225.
[15] H. Ku, H. Wang, N. A solution to the unequal is a facilities layout problem by genetic algorithm. Computers in Industry, 56(2), 207–220, (2005).
Cite This Article
  • APA Style

    Ahmed M. Abed. (2015). Create Heijunka 5’s Matrix to Control the Dynamic Gemba as Lean Tool. Journal of Human Resource Management, 3(2), 6-16. https://doi.org/10.11648/j.jhrm.20150302.11

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    ACS Style

    Ahmed M. Abed. Create Heijunka 5’s Matrix to Control the Dynamic Gemba as Lean Tool. J. Hum. Resour. Manag. 2015, 3(2), 6-16. doi: 10.11648/j.jhrm.20150302.11

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    AMA Style

    Ahmed M. Abed. Create Heijunka 5’s Matrix to Control the Dynamic Gemba as Lean Tool. J Hum Resour Manag. 2015;3(2):6-16. doi: 10.11648/j.jhrm.20150302.11

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  • @article{10.11648/j.jhrm.20150302.11,
      author = {Ahmed M. Abed},
      title = {Create Heijunka 5’s Matrix to Control the Dynamic Gemba as Lean Tool},
      journal = {Journal of Human Resource Management},
      volume = {3},
      number = {2},
      pages = {6-16},
      doi = {10.11648/j.jhrm.20150302.11},
      url = {https://doi.org/10.11648/j.jhrm.20150302.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jhrm.20150302.11},
      abstract = {The heijunka tracking matrix has a direct impact on turn overtimes of the inventory to revamp existing orders as well as new technique, and increase the utilization of the inventory’ labors by eliminating the waste in transportation and over-processing actions. The tracking problem is interested in rearranging the location of VSM (e.g., items, pallets and stations) in a grouping of cellular aspect using 5’S concepts, which increase performance level. One of the successful recommendations used in this context is traveler salesman technique but with periodically update (i.e., Dynamic Gemba), it may be need reformulation. Its importance is the capture of work, information, and material (WIP, setup time, process time/unit, error rates, idle time, etc.) which is essential in quantifying and determining waste in terms of cost, delivery time and transportation frequency. This paper is interest in review the dynamic Gemba model to improve the inventory handling via modifying the traveler salesman model with aided proposed heuristic procedures, which are interested in arrange the inventory in minimum time and maximum flexibility in preparing the different orders. The Gemba tasks displayed via (Gemba KPI/DOE board) which contain cost and time information (NNVA: preparing tasks, VA: traveling||tracking tasks and NNVA: unloading tasks). The optimized cost and time analysis after reducing NNVA time and total VA time were sent to the central heijunka matrix. The methodology which includes elimination movements, motion and extra actions wastes are lean, and aim to increase the ability of prepare a lot of service in minimum time.},
     year = {2015}
    }
    

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    AB  - The heijunka tracking matrix has a direct impact on turn overtimes of the inventory to revamp existing orders as well as new technique, and increase the utilization of the inventory’ labors by eliminating the waste in transportation and over-processing actions. The tracking problem is interested in rearranging the location of VSM (e.g., items, pallets and stations) in a grouping of cellular aspect using 5’S concepts, which increase performance level. One of the successful recommendations used in this context is traveler salesman technique but with periodically update (i.e., Dynamic Gemba), it may be need reformulation. Its importance is the capture of work, information, and material (WIP, setup time, process time/unit, error rates, idle time, etc.) which is essential in quantifying and determining waste in terms of cost, delivery time and transportation frequency. This paper is interest in review the dynamic Gemba model to improve the inventory handling via modifying the traveler salesman model with aided proposed heuristic procedures, which are interested in arrange the inventory in minimum time and maximum flexibility in preparing the different orders. The Gemba tasks displayed via (Gemba KPI/DOE board) which contain cost and time information (NNVA: preparing tasks, VA: traveling||tracking tasks and NNVA: unloading tasks). The optimized cost and time analysis after reducing NNVA time and total VA time were sent to the central heijunka matrix. The methodology which includes elimination movements, motion and extra actions wastes are lean, and aim to increase the ability of prepare a lot of service in minimum time.
    VL  - 3
    IS  - 2
    ER  - 

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Author Information
  • Industrial Engineering Department, Zagazig University, Zagazig, Egypt

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