The purpose of the study is to determine whether the presence of risk management in a warehouse requires the implementation of modern warehouse technology. On the basis of the literature analysis, it was possible to determine that there is a correlation between the presence of the highest level of risk management and the use of modern warehouse technology in individual warehousing processes. For this purpose, a statistical analysis was carried out on a sample of companies operating in the Slovenian automotive industry. The results did not reveal a tangible correlation between the presence of risk management with the use of individual modern warehouse technology, the motivation for its use and errors in its use. The results of the study therefore, highlight the problems that are present in the warehousing system of the Slovenian companies in the automotive industry, which are related to substandard technological equipment in the warehouses and to the discrepancy between the level of manufacturing automation and the level of warehousing automation. The results are important for the Slovenian automotive industry in terms of the implementation of modern warehouse technology in the high-tech automotive industry.
Jacyna-Gołda I, Lewczuk K. The method of estimating dependability of supply chain elements on the base of technical and organizational redundancy of process. Eksploatacja i Niezawodnosc – Maintenance and Reliability. 2017;19(3): 382-392.
Richards G. Warehouse management: a complete guide to improving efficiency and minimizing costs in the modern warehouse. London, Philadelphia: Kogan Page; 2011.
Habazin J, Glasnović A, Bajor I. Order Picking Process in Warehouse: Case Study of Dairy Industry in Croatia. Promet – Traffic&Transportation. 2017;29(1): 57-65.
Škerlič S, Muha R. Reducing errors in the company's warehouse process. Transport problems. 2017;12(1): 83-92.
Richards, G. Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Second Edition. New Delhi: Kogan Page Ltd.; 2014.
Tsarouchi P, Makris S, Chryssolouris G. Human–robot interaction review and challenges on task planning and programming. International Journal of Computer Integrated Manufacturing. 2016;29(8): 916-931.
Merritt SM. Affective Processes in Human–Automation Interactions. Human Factors. 2011;53(4): 356-370.
McBride SE, Rogers WA, Fisk AD. Understanding human management of automation errors. Theoretical Issues in Ergonomics Science. 2014;15(6): 545-577.
Hancock PA. Automation: how much is too much? Ergonomics. 2014;57(3): 449-454.
Everitt J, Fletcher S, Caird-Daley A. Task analysis of discrete and continuous skills: a dual methodology approach to human skills capture for automation. Theoretical Issues in Ergonomics Science. 2015;16(5): 513-532.
Reason J. Managing the risk of organizational accidents. Surrey: Ashgate cop.; 2011.
Stapleton D, Hanna JB, Yagla S, Johnson J, Markussen D. Measuring Logistics Performance Using the Strategic Profit Model. International Journal of Logistics Management. 2002;13(1): 89-107.
Škerlič S, Muha R. The importance of systems for controlling logistics costs in the supply chain : a case study from the Slovenian automotive industry. Promet – Traffic&Transportation. 2016;28(3): 299-310.
Mangan J, Lalwani C, Butcher T. Global logistics and supply chain management. Chichester: John Wiley & Sons cop.; 2012.
Dekker S. The field guide understanding human error. Aldershot, U.K: Ashgate cop; 2006.
Lam HY, Choy KL, Ho GTS, Cheng Stephen WY, Lee CKM. A knowledge-based logistics operations planning system for mitigating risk in warehouse order fulfillment. International Journal of Production Economics. 2015;170: 763-779.
Tang CS. Perspectives in supply chain risk management. International Journal of Production Economics. 2006;103(2): 451-488.
Manuj I, Mentzer JT. Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management. 2008;38(3): 192-223.
Ho W, Zheng T, Yildiz H, Talluri S. Supply chain risk management: a literature review. International Journal of Production Research. 2015;53(16): 5031-5069.
ISO, International Organization for Standardization. Available from: https://www.iso.org/iso-31000-riskmanagement.html [Accessed 15th December 2018].
Randhawa SJ, Ahuja SI. An investigation into manufacturing performance achievements accrued by Indian manufacturing organization through strategic 5S practices. International Journal of Productivity and Performance Management. 2018;67(4): 754-787.
Ohno T. Workplace Management. Cambridge, MA: Productivity Press; 1988.
Health and Safety Executive. Warehousing and storage: A guide to health and safety. Second edition, 2007. Available from: http://www.hse.gov.uk/logistics/warehousing.htm [Accessed 29th May 2019].
Yan R, Jackson LM, Dunnett SJ. Automated guided vehicle mission reliability modelling using a combined fault tree and Petri net approach. The International Journal of Advanced Manufacturing Technology. 2017;92(5-8): 1825-1837.
Choy KL, Sheng N, Lam HY, Lai Ivan KW, Chow KH, Ho GTS. Assess the effects of different operations policies on warehousing reliability. International Journal of Production Research. 2014;52(3): 662-678.
Ryu H, Kim N, Lee J, Shin D. An Affordance-Based Model of Human Action Selection in a Human–Machine Interaction System with Cognitive Interpretations. International Journal of Human–Computer Interaction. 2016;32(5): 402-414.
Cochran DS, Arinez JF, Collins MT, Bi Z. Modelling of human–machine interaction in equipment design of manufacturing cells. Enterprise Information Systems. 2017;11(7): 969-987.
Caputo AC, Pelagagge PM, Salini P. Modelling human errors and quality issues in kitting processes for assembly lines feeding. Computers & Industrial Engineering. 2017;111: 492-506.
Rajković M, Zrnić N, Kosanić N, Borovinšek M, Lerher T. A multi-objective optimization model for minimizing investment expenses, cycle times and CO2 footprint of an automated storage and retrieval systems. Transport. 2019;34(2): 275-286.
Janilionis V, Bazaras Ž. The design and investigation of two storage/retrieval mechanisms of the cylindrical automated storage and retrieval system. Transport. 2013;28(4): 352-360.
Ricrads G. Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Third Edition. New Delhi: Kogan Page Ltd.; 2017.
Stock, JR, Lambert DM. Strategic logistics management. 4th ed. Boston, etc.: McGraw-Hill Irwin; 2001.
Blanchard D. Supply chain management: Best practices. Hoboken, New Jersey: John Wiley & Sons, cop; 2010.
Son DW, Chang YS, Choi HC, Kim WR, Higuera AG. A study of building a new warehouse control system architecture. International Journal of Advanced Logistics. 2015;4(3): 145-158.
Dujmešić N, Bajor I, Rožić T. Warehouse Processes Improvement by Pick by Voice Technology. Tehnički vjesnik – Technical Gazette. 2018;25(4): 1227-1233.
Marchet G, Melacini M, Perotti S. Investigating order picking system adoption: a case-study-based approach. International Journal of Logistics Research and Applications. 2015;18(1): 82-98.
Hollnagel E. Cognitive reliability and error analysis method. Oxford: Elsevier Science Ltd; 1998.
GIZ ACS, Slovenski avtomobilski grozd. 2019. Available from: http://www.acs-giz.si/o-acs [Accessed 17th January 2019].
IFR, The International Federation of Robotics. Global industrial robot sales doubled over the past five years. 2018. Available from: https://ifr.org/ifr-press-releases/news/global-industrial-robot-sales-doubled-over-thepast-
five-years [Accessed 22nd May 2019].
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