IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11914-d666776.html
   My bibliography  Save this article

Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems

Author

Listed:
  • Péter Dobos

    (Starters E-Components Generators Automotive Hungary Kft., 0129/96 hrsz., 3711 Szirmabesenyő, Hungary)

  • Ákos Cservenák

    (Institute of Logistics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary)

  • Róbert Skapinyecz

    (Institute of Logistics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary)

  • Béla Illés

    (Institute of Logistics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary)

  • Péter Tamás

    (Institute of Logistics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary)

Abstract

In real life situations, the material handling strategy of on-site storage systems is usually determined during the design of the storage system, which is no longer reviewed later. The strategy is typically determined by the person(s) designing the storage system, without the use of scientific methods, based on previous experience. Without a thorough periodic review of operational strategy, most companies’ warehousing systems have significant logistical losses (e.g., unnecessary material handling, waiting, operations), which also negatively affects the sustainability of the logistics operations. Therefore, eliminating these losses can increase both the competitiveness and the sustainability of companies. For this reason, the aim of this publication is to introduce a gap-filling test method that allows the selection of an optimal material handling strategy covering the total value stream in a demand-driven storage environment, using the opportunities offered by the Industry 4.0 concept, in particular in the field of big data analysis. This integrated approach has so far not emerged in the study of warehouse material handling strategies. Beyond the obvious economic benefits, the application of this method can clearly help companies to achieve a higher level of sustainability in their logistics operations, as it allows storage systems to operate more efficiently while minimizing material handling losses, ultimately resulting in a lesser demand for energy and raw materials. Moreover, this can also result in a reduction in the human and machine resources required to perform the tasks.

Suggested Citation

  • Péter Dobos & Ákos Cservenák & Róbert Skapinyecz & Béla Illés & Péter Tamás, 2021. "Development of an Industry 4.0-Based Analytical Method for the Value Stream Centered Optimization of Demand-Driven Warehousing Systems," Sustainability, MDPI, vol. 13(21), pages 1-33, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11914-:d:666776
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11914/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/21/11914/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nadia Preghenella & Cinzia Battistella, 2021. "Exploring business models for sustainability: A bibliographic investigation of the literature and future research directions," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2505-2522, July.
    2. Zahra Mohammadnazari & Seyed Farid Ghannadpour, 2021. "Sustainable construction supply chain management with the spotlight of inventory optimization under uncertainty," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10937-10972, July.
    3. Tortorella, Guilherme Luz & Saurin, Tarcísio Abreu & Filho, Moacir Godinho & Samson, Daniel & Kumar, Maneesh, 2021. "Bundles of Lean Automation practices and principles and their impact on operational performance," International Journal of Production Economics, Elsevier, vol. 235(C).
    4. Ang, Marcus & Lim, Yun Fong, 2019. "How to optimize storage classes in a unit-load warehouse," European Journal of Operational Research, Elsevier, vol. 278(1), pages 186-201.
    5. Vlado Popović & Milorad Kilibarda & Milan Andrejić & Borut Jereb & Dejan Dragan, 2021. "A New Sustainable Warehouse Management Approach for Workforce and Activities Scheduling," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    6. Massimo Ceraolo & Valentina Consolo & Mauro Di Monaco & Giovanni Lutzemberger & Antonino Musolino & Rocco Rizzo & Giuseppe Tomasso, 2021. "Design and Realization of an Inductive Power Transfer for Shuttles in Automated Warehouses," Energies, MDPI, vol. 14(18), pages 1-20, September.
    7. Ashayeri, J. & Gelders, L. F., 1985. "Warehouse design optimization," European Journal of Operational Research, Elsevier, vol. 21(3), pages 285-294, September.
    8. Omar Alhawari & Usama Awan & M. Khurrum S. Bhutta & M. Ali Ülkü, 2021. "Insights from Circular Economy Literature: A Review of Extant Definitions and Unravelling Paths to Future Research," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    9. Gray, Ann E. & Karmarkar, Uday S. & Seidmann, Abraham, 1992. "Design and operation of an order-consolidation warehouse: Models and application," European Journal of Operational Research, Elsevier, vol. 58(1), pages 14-36, April.
    10. Rouwenhorst, B. & Reuter, B. & Stockrahm, V. & van Houtum, G. J. & Mantel, R. J. & Zijm, W. H. M., 2000. "Warehouse design and control: Framework and literature review," European Journal of Operational Research, Elsevier, vol. 122(3), pages 515-533, May.
    11. Baker, Peter & Canessa, Marco, 2009. "Warehouse design: A structured approach," European Journal of Operational Research, Elsevier, vol. 193(2), pages 425-436, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gu, Jinxiang & Goetschalckx, Marc & McGinnis, Leon F., 2010. "Research on warehouse design and performance evaluation: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 203(3), pages 539-549, June.
    2. Rakesh Venkitasubramony & Gajendra K. Adil, 2021. "Modeling the effect of imperfect staggering in product inflow using queuing theory: revisiting block stacking layout," Flexible Services and Manufacturing Journal, Springer, vol. 33(3), pages 689-716, September.
    3. Janka Saderova & Andrea Rosova & Marian Sofranko & Peter Kacmary, 2021. "Example of Warehouse System Design Based on the Principle of Logistics," Sustainability, MDPI, vol. 13(8), pages 1-16, April.
    4. Shiva Abdoli & Sami Kara, 2017. "A Modelling Framework to Design Executable Logical Architecture of Engineering Systems," Modern Applied Science, Canadian Center of Science and Education, vol. 11(9), pages 1-75, September.
    5. Derhami, Shahab & Smith, Jeffrey S. & Gue, Kevin R., 2020. "A simulation-based optimization approach to design optimal layouts for block stacking warehouses," International Journal of Production Economics, Elsevier, vol. 223(C).
    6. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    7. Zhi Li & Ali Vatankhah Barenji & Jiazhi Jiang & Ray Y. Zhong & Gangyan Xu, 2020. "A mechanism for scheduling multi robot intelligent warehouse system face with dynamic demand," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 469-480, February.
    8. Gabriel Fedorko & Vieroslav Molnár & Nikoleta Mikušová, 2020. "The Use of a Simulation Model for High-Runner Strategy Implementation in Warehouse Logistics," Sustainability, MDPI, vol. 12(23), pages 1-17, November.
    9. Tian Liu & Xianhao Xu & Hu Qin & Andrew Lim, 2016. "Travel time analysis of the dual command cycle in the split-platform AS/RS with I/O dwell point policy," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 442-460, September.
    10. Shuyu Zhou & Yeming (Yale) Gong & René de Koster, 2016. "Designing self-storage warehouses with customer choice," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3080-3104, May.
    11. Baker, Peter & Canessa, Marco, 2009. "Warehouse design: A structured approach," European Journal of Operational Research, Elsevier, vol. 193(2), pages 425-436, March.
    12. de Koster, M.B.M. & Le-Duc, T. & Roodbergen, K.J., 2006. "Design and Control of Warehouse Order Picking: a literature review," ERIM Report Series Research in Management ERS-2006-005-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    13. Nikola Pavlov & Dragan Đurdjević & Milan Andrejić, 2023. "A Novel Two-Stage Methodological Approach for Storage Technology Selection: An Engineering–FAHP–WASPAS Approach," Sustainability, MDPI, vol. 15(17), pages 1-20, August.
    14. Vidal Vieira, José Geraldo & Ramos Toso, Milton & da Silva, João Eduardo Azevedo Ramos & Cabral Ribeiro, Priscilla Cristina, 2017. "An AHP-based framework for logistics operations in distribution centres," International Journal of Production Economics, Elsevier, vol. 187(C), pages 246-259.
    15. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    16. de Koster, Rene & Le-Duc, Tho & Roodbergen, Kees Jan, 2007. "Design and control of warehouse order picking: A literature review," European Journal of Operational Research, Elsevier, vol. 182(2), pages 481-501, October.
    17. Mital, Pratik & Goetschalckx, Marc & Huang, Edward, 2015. "Robust material handling system design with standard deviation, variance and downside risk as risk measures," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 815-824.
    18. Dragan Djurdjević & Nenad Bjelić & Dražen Popović & Milan Andrejić, 2022. "A Combined Dynamic Programming and Simulation Approach to the Sizing of the Low-Level Order-Picking Area," Mathematics, MDPI, vol. 10(20), pages 1-23, October.
    19. Rouwenhorst, B. & Reuter, B. & Stockrahm, V. & van Houtum, G. J. & Mantel, R. J. & Zijm, W. H. M., 2000. "Warehouse design and control: Framework and literature review," European Journal of Operational Research, Elsevier, vol. 122(3), pages 515-533, May.
    20. Liu, Tian & Gong, Yeming & De Koster, René B.M., 2018. "Travel time models for split-platform automated storage and retrieval systems," International Journal of Production Economics, Elsevier, vol. 197(C), pages 197-214.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11914-:d:666776. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.