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Autonomous Mobile Robots in Automotive Remanufacturing: A Case Study for Intra-Logistics Support

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The article focuses on the role of modern logistics 4.0 technologies and lean management in optimizing ancillary processes in intralogistics. The literature review presents critical aspects of intralogistics, including using autonomous mobile robots (AMR) and the challenges associated with their successful implementation. The article also discusses the concepts of Industry 4.0 and Industry 5.0. highlighting the importance of synergies between workers and advanced technologies. In optimizing logistics processes, the authors emphasize the importance of lean management and tools such as 5S and Kaizen. The authors analyze the research gap related to the organization of auxiliary processes, intralogistics, and the introduction of modern technologies. The lack of good practices and strategies for implementing new technologies for ancillary processes makes this a critical issue for managers and production engineers. The article provides practical strategies that can be implemented in companies. It is a valuable resource for managers seeking to manage intralogistics and effectively improve support processes in manufacturing plants. In summary, the article provides a comprehensive look at modern approaches to optimizing support processes in internal logistics. It highlights the importance of integrating modern logistics technologies with lean management principles, which can increase companies' efficiency and competitiveness.
Twórcy
autor
  • Department of Enterprise Organization, Faculty of Management, Lublin University of Technology
  • Department of Production Computerisation and Robotisation, Faculty of Mechanical Engineering, Lublin University of Technology
  • Department of Production Computerisation and Robotisation, Faculty of Mechanical Engineering, Lublin University of Technology
  • Faculty of Economics, Maria Curie-Sklodowska University
  • Department of Materials and Production, Faculty of Engineering and Science, Aalborg University, Denmark
Bibliografia
  • 1. Bocewicz G., Nielsen I., Gola A., Banaszak Z. Reference model of milk-run traffic systems prototyping. Int J Prod Res 2021; 59: 4495–512. https://doi.org/10.1080/00207543.2020.1766717.
  • 2. Kanski L., Pizon J. The impact of selected components of Industry 4.0 on project management. Journal of Innovation & Knowledge 2023; 8: 100336. https://doi.org/10.1016/J.JIK.2023.100336.
  • 3. Pizoń J., Gola A. The meaning and directions of development of personalized production in the era of Industry 4.0 and Industry 5.0. Lecture Notes in Mechanical Engineering 2023; 1–13. https://doi.org/10.1007/978-3-031-09360-9_1/COVER.
  • 4. Demir S., Paksoy T., Kochan C.G. Logistics 4.0: SCM in Industry 4.0 Era (Changing patterns of logistics in Industry 4.0 and role of digital transformation in SCM). 2020. CRC Press
  • 5. Sloniec J. A longitudinal analysis of IT outsourcing in large Polish organizations. European Research Studies Journal 2021; XXIV: 439–52. https://doi.org/10.35808/ERSJ/2275.
  • 6. Pylak K., Majerek D.. Impact of the service sector on the creation of companies in Poland. Procedia Economics and Finance 2015; 24:523–32. https://doi.org/10.1016/S2212-5671(15)00623-1.
  • 7. Pylak K., Wojnicka-Sycz E. Transforming innovation models to change the development paths of less-developed regions. Procedia Eng 2016; 161: 2179–83. https://doi.org/10.1016/j.proeng.2016.08.812.
  • 8. Morgenstern J.M., Zadek H.U. AMR: influencing factors and potentials of cloud-robotics 2023. https://doi.org/10.25673/103490.
  • 9. Miletić S.D-, Raković K. Ranking of Autonomous Alternatives for the Realization of Intralogistics Activities in Sustainable Warehouse Systems using the TOPSIS Method. Spectrum of Engineering and Management Sciences 2023; 1: 48–57. https://doi.org/10.31181/SEMS1120234M.
  • 10. Bayrak I.T., Cebi F. Procedure Model for Industry 4.0 Realization for Operations Improvement of Manufacturing Organizations. IEEE Trans Eng Manag 2023. https://doi.org/10.1109/TEM.2023.3292337.
  • 11. Pizoń J., Gola A. The Meaning and Directions of Development of Personalized Production in the Era of Industry 4.0 and Industry 5.0. Lecture Notes in Mechanical Engineering 2023: 1–13. https://doi.org/10.1007/978-3-031-09360-9_1/COVER.
  • 12. Dabic-Miletic S. Advanced Technologies in Smart Factories: A Cornerstone of Industry 4.0. Journal of Industrial Intelligence 2023; 1: 148–57. https://doi.org/10.56578/JII010302.
  • 13. Jafari N., Azarian M., Yu H. Moving from Industry 4.0 to Industry 5.0: What Are the Implications for Smart Logistics? Logistics 2022, Vol 6, Page 26 2022; 6: 26. https://doi.org/10.3390/LOGISTICS6020026.
  • 14. Olewe S., Finke M., Belke J., Dyck F., Kürpick C. Use Case Catalog and Assessment for AI Applications in Intralogistics of Manufacturing Companies. Procedia CIRP 2023; 118: 74–9. https://doi.org/10.1016/J.PROCIR.2023.06.014.
  • 15. Jafari N., Sgarbossa F., Nyland B.T., Sorheim A. An Investigation into Technological Potentials of Library Intralogistics Operations. IFIP Adv Inf Commun Technol 2023; 690 AICT: 47–60. https://doi.org/10.1007/978-3-031-43666-6_4/COVER.
  • 16. Yi H., Qu T., Zhang K., Li M., Huang G.Q., Chen Z. Production Logistics in Industry 3.X: Bibliometric Analysis, Frontier Case Study, and Future Directions 2023; 11: 371. https://doi.org/10.3390/SYSTEMS11070371.
  • 17. Kavka L., Dočkalíková I., Čujan Z., Fedorko G. Technological and Economic Analysis of Logistic Activities in Interior Parts Manufacturing. Advances in Science and Technology Research Journal 2020; 14: 204–12. https://doi.org/10.12913/22998624/122062.
  • 18. Kampf R., Hlatká M., Bartuska L. Optimization of Production Logistics. Advances in Science and Technology Research Journal 2018; 12: 151–6. https://doi.org/10.12913/22998624/100351.
  • 19. Winkelhaus S., Grosse E.H., Glock C.H. Job satisfaction: An explorative study on work characteristics changes of employees in Intralogistics 4.0. Journal of Business Logistics 2022; 43: 343–67. https://doi.org/10.1111/JBL.12296.
  • 20. Pizoń J., Cioch M., Kański Ł., García E.S. Cobots Implementation in the Era of Industry 5.0 Using Modern Business and Management Solutions. Advances in Science and Technology Research Journal 2022; 16: 166–78. https://doi.org/10.12913/22998624/156222.
  • 21. Pizoń J., Gola A., Świć A. The Role and Meaning of the Digital Twin Technology in the Process of Implementing Intelligent Collaborative Robots. Lecture Notes in Mechanical Engineering 2022: 39–49. https://doi.org/10.1007/978-3-031-00805-4_4.
  • 22. Fragapane G., de Koster R., Sgarbossa F., Strandhagen J.O. Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda. Eur J Oper Res 2021; 294: 405–26. https://doi.org/10.1016/J.EJOR.2021.01.019.
  • 23. Alatise M.B., Hancke G.P. A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods. IEEE Access 2020; 8: 39830–46. https://doi.org/10.1109/ACCESS.2020.2975643.
  • 24. Fragapane G., Ivanov D., Peron M., Sgarbossa F., Strandhagen J.O. Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics. Ann Oper Res 2022; 308: 125–43. https://doi.org/10.1007/S10479-020-03526-7/FIGURES/9.
  • 25. Li M., Guo D., Li M., Qu T., Huang G.Q. Operation twins: production-intralogistics synchronisation in Industry 4.0. Int J Prod Res 2023; 61: 5193–211. https://doi.org/10.1080/00207543.2022.2098874.
  • 26. Grover A.K., Ashraf M.H. Leveraging autonomous mobile robots for Industry 4.0 warehouses: A multiple case study analysis. International Journal of Logistics Management 2023. https://doi.org/10.1108/IJLM-09-2022-0362
  • 27. Albrecht T., Baier M.S., Gimpel H., Meierhöfer S., Röglinger M., Schlüchtermann J., et al. Leveraging digital technologies in Logistics 4.0: Insights on affordances from intralogistics processes. Information Systems Frontiers 2023; 1: 1–20. https://doi.org/10.1007/S10796-023-10394-6.
  • 28. Pizoń J., Kulisz M., Lipski J., Pizon J., Kulisz M., Lipski J., et al. Matrix profile implementation perspective in Industrial Internet of Things production maintenance application. J Phys Conf Ser 2021; 1736. https://doi.org/10.1088/1742-6596/1736/1/012036.
  • 29. Maj M., Rymarczyk T., Maciura Ł., Cieplak T., Pliszczuk D. Cross-modal perception for customer service. Proceedings of the 29th Annual International Conference on Mobile Computing and Networking 2023: 1–3. https://doi.org/10.1145/3570361.3615751.
  • 30. Kłosowski G., Rymarczyk T., Niderla K., Rzemieniak M., Dmowski A., Maj M. Comparison of machine learning methods for image reconstruc-
  • tion using the LSTM classifier in industrial electrical tomography. Energies 2021; 14: 7269. https://doi.org/10.3390/EN14217269.
  • 31. Pawlik P., Kania K., Przysucha B. Fault diagnosis of machines operating in variable conditions using artificial neural network not requiring training data from a faulty machine. Eksploatacja i Niezawodnosc 2023; 25. https://doi.org/10.17531/EIN/168109.
  • 32. Jafari N., Azarian M., Yu H. Moving from Industry 4.0 to Industry 5.0: What are the implications for smart logistics? Logistics 2022; 6: 26. https://doi.org/10.3390/LOGISTICS6020026.
  • 33. Sundararajan N., Terkar R. Improving productivity in fastener manufacturing through the application of Lean-Kaizen principles. Mater Today Proc 2022; 62: 1169–78. https://doi.org/10.1016/J.MATPR.2022.04.350.
  • 34. Rossmery J., Castañeda C., Morisque G., Ayala M., Adolfo G., Cárdenas M. 5S Methodology: literature review and implementation analysis. Journal of Scientific and Technological Research Industrial 2022; 3: 47–55. https://doi.org/10.47422/JSTRI.V3I2.30.
  • 35. Thomaz J.P.C.F., Bispo H.I.N. Lean manufacturing and industry 4.0/5.0: Applied research in the Portuguese cork industry. Increasing Supply Chain Performance in Digital Society 2022: 101–130. https://doi.org/10.4018/978-1-7998-9715-6.ch006.
  • 36. Souza R., Ferenhof H., Forcellini F. Industry 4.0 and Industry 5.0 from the Lean perspective. International Journal of Management, Knowledge and Learning 2022; 11. https://doi.org/10.53615/2232-5697.11.145-155.
  • 37. Moraes A., Carvalho A.M., Sampaio P. Lean and Industry 4.0: A Review of the Relationship, Its Limitations, and the Path Ahead with Industry 5.0. Machines 2023; 11: 443. https://doi.org/10.3390/MACHINES11040443.
  • 38. Helmold M., Küçük Yılmaz A., Flouris T., Winner T., Cvetkoska V., Dathe T. Lean Management in the Automotive Industry. Management for Professionals 2022; Part F377: 183–195. https://doi.org/10.1007/978-3-031-10104-5_13/COVER.
  • 39. Helmold M., Küçük Yılmaz A., Flouris T., Winner T., Cvetkoska V., Dathe T. Toyota production system. Management for Professionals 2022; Part F377 :73–84. https://doi.org/10.1007/978-3-031-10104-5_7/COVER.
  • 40. Radin Umar R.Z., Tiong J.Y., Ahmad N., Dahalan J. Development of framework integrating ergonomics in Lean’s Muda, Muri, and Mura concepts. Production Planning & Control 2023. https://doi.org/10.1080/09537287.2023.2189640.
  • 41. Kumar N., Kaliyan M., Thilak M., Acevedo-Duque Á. Identification of specific metrics for sustainable lean manufacturing in the automobile industries. Benchmarking 2022; 29: 1957–78. https://doi.org/10.1108/BIJ-04-2021-0190/FULL/PDF.
  • 42. Suarez-Barraza M.F., Miguel-Dávila J.A., Morales Contreras MF. KAIZEN: An ancestral strategy for operational improvement: literature review and trends. Lecture Notes in Mechanical Engineering 2022: 154–168. https://doi.org/10.1007/978-3-031-00218-2_13/COVER.
  • 43. Bharat A., Chand D., Dahiya P., Rathore S.S. Implementation of Kaizen in automotive industry: A case study 2023: 337–344. https://doi.org/10.1007/978-981-99-1308-4_27/COVER.
  • 44. Mrabti A., Bouajaja S., Hachicha H.K., Nouri K. Digital 5S: a case study of an Automotive wiring industry. ITM Web of Conferences 2023; 52: 01005. https://doi.org/10.1051/ITMCONF/20235201005.
  • 45. Naugolnova I.A. Cost management in economic Instability: A primary enterprise task 2023: 274–279. https://doi.org/10.1007/978-3-031-38122-5_38/COVER.
  • 46. Ciccarelli M., Papetti A., Cappelletti F., Brunzini A., Germani M. Combining world class manufacturing system and Industry 4.0 technologies to design ergonomic manufacturing equipment. International
  • Journal on Interactive Design and Manufacturing 2022; 16: 263–279. https://doi.org/10.1007/S12008-021-00832-7/FIGURES/9.
  • 47. Kaizen and 5S: Productivity improvement tools for automotive assembly line. Nolegein Journal of Operations Research & Management 2022; 5.
  • 48. Nunes I., Costa A., Gonçalves J., Bernardo G., Rocha A., Almeida T., et al. Pull and push applied to a just in time supply chain-case study Jerónimo Martins. American Journal of Industrial and Business Management 2014; 12: 1204–12. https://doi.org/10.4236/ajibm.2022.127065.
  • 49. Elattar S., Mohamed H.G., Hussien S.A. A multiobjective optimization of secure pull manufacturing systems. Applied Sciences 2022; 12: 5937. https://doi.org/10.3390/APP12125937. 50. Mofolasayo A., Young S., Martinez P., Ahmad R. How to adapt lean practices in SMEs to support Industry 4.0 in manufacturing. Procedia Comput Sci 2022; 200: 934–943. https://doi.org/10.1016/J.PROCS.2022.01.291.
  • 51. Lara A.C., Menegon E.M.P., Sehnem S., Kuzma E. Relationship between Just in Time, Lean Manufacturing, and Performance Practices: a meta-analysis. Gestão & Produção 2022; 29: e9021. https://doi.org/10.1590/1806-9649-2022V29E9021.
  • 52. Kumar N., Shahzeb Hasan S., Srivastava K., Akhtar R., Kumar Yadav R., Choubey V.K. Lean manufacturing techniques and its implementation: A review. Mater Today Proc 2022; 64: 1188–92. https://doi.org/10.1016/J.MATPR.2022.03.481.
  • 53. Madsen D.Ø., Berg T., Di Nardo M. Bibliometric trends in Industry 5.0 research: An updated overview. Applied System Innovation 2023; 6: 63. https://doi.org/10.3390/ASI6040063.
  • 54. Ruiz-de-la-Torre A., Rio-Belver R.M., GuevaraRamirez W., Merlo C. Industry 5.0 and humancentered approach. bibliometric review. Lecture Notes on Data Engineering and Communications Technologies 2023; 160: 402–408. https://doi.org/10.1007/978-3-031-27915-7_71/COVER.
  • 55. Maddikunta P.K.R., Pham Q.V., B P, Deepa N., Dev K., Gadekallu T.R,. et al. Industry 5.0: A survey on enabling technologies and potential applications. J Ind Inf Integr 2022; 26: 100257. https://doi.org/10.1016/J.JII.2021.100257.
  • 56. Bielecki M. Logistics 4.0: Challenges, opportunities and threats. Tehnički Glasnik 2023; 17: 455–61. https://doi.org/10.31803/TG-20230505142802.
  • 57. Fragapane G., de Koster R., Sgarbossa F., Strandhagen J.O. Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda. Eur J Oper Res 2021; 294: 405–246. https://doi.org/10.1016/J.EJOR.2021.01.019.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5c1ddf94-a444-4e2f-acbe-89b994800bc7
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