Methodology of evaluating finished goods warehouse performance through lean methods

Edward Michlowicz

doi:10.61089/aot2024.s9sq9q75

Authors

Edward Michlowicz AGH University of Science and Technology, Faculty of Mechanical Engineering and Robotics, Krakow, Poland Author https://orcid.org/0000-0002-7449-5080

DOI:

https://doi.org/10.61089/aot2024.s9sq9q75

Keywords:

effectiveness assessment, finished goods warehouse, lean indicators, OEE

Abstract

This paper considers the problem of evaluating the effectiveness of the finished goods warehouse of a manufacturing company, in which a modified TPM method - Total Productive Management (TPM2) - was applied to improve productivity. A multi-stage methodology was proposed, including a decision to modify the system, determination of the scope of changes, monitoring the results obtained and a multi-criteria evaluation of the changes made. The decision to make modifications to the existing system was motivated by the lower-than-expected quality of customer service (frequent delivery delays). With regard to the transport department, lean flow pillar activities were focused on analysing losses (muda) in warehouse processes (product loading and package unloading). The purpose of these activities was to minimise interruptions in warehouse processes (product loading and package unloading). "The steps for solving the problem" methodology based on Deming's PDCA cycle was used to solve the problem. The analysis covered, among other things, the information flow processes between production planning and the customer service department, the planning processes of the dispatcher, the efficiency of the loading processes, and the causes of interruptions in warehouse operations. The analyses employed the chronometry of selected works, the 5W + 1H method and the Pareto method. By using the 5S method and some characteristics of the SMED method, the organisation of loading work was decisively changed (shunting yard changes, appropriate buffers for transport equipment). The changes introduced in the system were monitored for several months. Appropriately defined OEE indicators were used to assess the behaviour of the system after the changes. The indicators consider the use of available warehouse time, the efficiency of the loading process and the quality of the tasks performed. The results that can be achieved are presented using the specific example of the finished goods warehouse of a manufacturing company in the FMCG sector.

References

Aerts B., Cornelissens T., Sörensen K., (2021). The joint order batching and picker routing problem: Modelled and solved as a clustered vehicle routing problem. Computers and Operations Research, 129, 105168. https://doi.org/10.1016/j.cor.2020.105168.

Alqahtani A., (2023). Improving order‑picking response time at retail warehouse: a case of sugar company. SN Applied Sciences, 5, 8. https://doi.org/10.1007/s42452-022-05230-6.

Andersson C., Bellgran M., (2015). On the complexity of using performance measures: Enhancing sustained production improvement capability by combining OEE and productivity. Journal of Manufacturing Systems, 35, 144–154. https://doi.org/10.1016/j.jmsy.2014.12.003.

Beker I., Jevtić V., Dobrilović D., (2012). Shortest-path algorithms as a tools for inner transportation optimization. International Journal of Industrial Engineering and Management, 3 (1), 2012, 39-45. https://doi.org/10.24867/IJIEM-2012-1-106.

Bokrantz J., Skoogh A., Berlin C., Wuest T., Stahre J., (2020 a). Smart Maintenance: an empirically grounded conceptualization. Int. J. Production Economics, 223, 107534. https://doi.org/10.1016/j.ijpe.2019.107534.

Bokrantz J., Skoogh A., Berlin C., Wuest T., Stahre J., (2020 b). Smart Maintenance: a research agenda for industrial maintenance management. Int. J. Production Economics 224, 107547. https://doi.org/10.1016/j.ijpe.2019.107547.

Bottani E., Volpi A., Montanari R., (2019). Design and optimization of order picking systems: An integrated procedure and two case studies. Computers & Industrial Engineering, 137, 106035. https://doi.org/10.1016/j.cie.2019.106035.

Buckova M., Krajcovic M., Edl M., (2017). Computer simulation and optimization of transport distances of order picking processes. Procedia Engineering, 192, 69–74. https://doi.org/10.1016/j.proeng.2017.06.012.

Duffuaa S.O., Raouf A., (2015). Planning and Control of Maintenance Systems. Modelling and Analysis. Cham Heidelberg New York Dordrecht London: Springer International Publishing. https://doi.org/10.1007/978-3-319-19803-3.

Freitas A.,. Silva F., Ferreira L., Sá S., Pereira M., Pereira J., (2019). Improving efficiency in a hybrid warehouse: a case study. Procedia Manufacturing, 38, 1074–1084. https://doi.org/10.1016/j.promfg.2020.01.195.

Habidin N., Hashim S., Fuzi N., Salleh M., (2018). Total productive maintenance, kaizen event, and performance. International Journal of Quality & Reliability Management , 35 (9), 1853-1867. https://doi.org/10.1108/IJQRM-11-2017-0234.

Hung Y-H., Li L., Cheng T.C.E., (2021). Uncovering hidden capacity in overall equipment effectiveness management. Int. J. Production Economics, 248, 108494. https://doi.org 10.1016/j.ijpe.2022.108494.

Jachimowski R., Gołębiowski P., Izdebski M., Pyza D., Szczepański E., (2017). Designing and efficiency of database for simulation of processes in systems. Case study for the simulation of warehouse processes. Archives of Transport, 41 (1), 31-42. https://doi.org/10.5604/01.3001.0009.7380.

Jacyna-Gołda I., Kłodawski M., Lewczuk K., Łajszczak M., Chojnacki T., Siedlecka-Wójcikowska T., (2019). Elements of perfect order rate research in logistics chains. Archives of Transport, 49(1), 25-35. https://doi.org/10.5604/01.3001.0013.2771.

Jain A., Bhatti R., Singh H., (2015). OEE enhancement in SMEs through mobile maintenance: a TPM concept. International Journal of Quality & Reliability Management, 32 (5), 503-516. http://doi.org/10.1108/IJQRM-05-2013-0088.

Jain A., Bhatti R., Singh H., (2014). Total productive maintenance (TPM) implementation practice: A literature review and directions. International Journal of Lean Six Sigma, 5 (3), 293-323. http://doi.org//10.1108/IJLSS-06-2013-0032.

Kim T., Dekker R., Cheij Ch., (2018). Improving warehouse labour efficiency by intentional forecast bias. International Journal of Physical Distribution & Logistics Management, 48 (1), 93-110. https://doi.org/10.1108/IJPDLM-10-2017-0313.

Kłodawski M, Jacyna M, Lewczuk K, Wasiak M., (2017). The issues of selection warehouse process strategies. Procedia Engineering, 187, 451 – 457. https://doi.org/10.1016/j.proeng.2017.04.399.

Kudelska, I., Niedbał, R., (2020). Technological and Organizational Innovation in Warehousing Process – Research over Workload of Staff and Efficiency of Picking Stations. E&M Economics and Management, 23(3), 67-81. https://doi.org/ 10.15240/tul/001/2020-3-005.

Lee J., Chang Y., Shim H., Cho S., (2015). A study on the picking process time. Procedia Manufacturing, 3, 731–738. https://doi.org/10.1016/j.promfg.2015.07.316.

Masae M., Glock Ch., Grosse E., (2020). Order picker routing in warehouses: A systematic literature review. Int. J. Production Economics, 224, 107564. https://doi.org/10.1016/j.ijpe.2019.107564.

Melinda T., Nazaruddin, Ginting R., (2020). Design of warehousing system in order picking process: literature review. IOP Conf. Series: Materials Science and Engineering 801, 012126 IOP. https://doi.org/10.1088/1757-899X/801/1/012126.

Michlowicz E., (2021). Logistics engineering and Industry 4.0 and Digital Factory. Archives of Transport, 57 (1), 59-72. https://doi.org/10.5604/01.3001.0014.7484.

Michlowicz E., (2013). Logistics in production processes. Journal of Machine Engineering, 13 (4), 5-17. ISSN 1895-7595X.

Mohamud I., Kafi Md., Shahron S., Zainuddin N., Musa S., (2023). The Role of Warehouse Layout and Operations in Warehouse Efficiency: A Literature Review. Journal Européen des Systèmes Automatisés, 56 (1), 61- 68. https://doi.org/10.18280/jesa.560109.

Mohanty, S., Rath, K.C., Jena, O.P., (2022). Implementation of Total Productive Maintenance (TPM) in the Manufacturing Industry for Improving Production Effectiveness. In: Industrial Transformation, Boca Raton: CRC Press, 45–60. https://doi.org/10.1201/9781003229018-3

Mouzani I., Bouami D., (2019). The Integration of Lean Manufacturing and Lean Maintenance to Improve Production Efficiency. International Journal of Mechanical and Production Engineering Research and Development, 9(1), 593-604. https://doi.org/ 10.24247/ijmperdfeb201957.

Nurprihatin, F., Angely, M., Tannady, H., (2019). Total Productive Maintenance policy to increase effectiveness and maintenance performance using overall equipment effectiveness. J. Appl. Res. Ind. Eng., 6 (3), 184–199. https://doi.org/ 10.22105/jarie.2019.199037. 1104.

Purba H., Mukhlisin, Aisyah S., (2018). Productivity improvement picking order by appropriate method, value stream mapping analysis, and storage design: a case study in automotive part center. Management and Production Engineering Review, 9 (1), 71–81. https://doi.org/10.24425/119402.

Rahman N., Karim N., Hanafiah R., Hamid S., Mohammed A., (2023). Decision analysis of warehouse productivity performance indicators to enhance logistics operational efficiency. International Journal of Productivity and Performance Management, 72 (4), 962-985. https://doi.org/10.1108/IJPPM-06-2021-0373.

Sahoo S., Yadav S., (2020). Influences of TPM and TQM Practices on Performance of Engineering Product and Component Manufacturers. Procedia Manufacturing, 43, 728–735. https://doi.org/10.1016/j.promfg.2020.02.111.

Salwin, M., Nehring, K., Jacyna-Gołda, I., Kraslawski, A., (2022). Product-Service System design – an example of the logistics industry. Archives of Transport, 63(3), 159-180. https://doi.org/10.5604/01.3001.0016.0820.

Sangwa, N.R. and Sangwan, K.S., (2018). Development of an integrated performance measurement framework for lean organizations. Journal of Manufacturing Technology Management, 29 (1), 41-84. https://doi.org/10.1108/JMTM-06-2017-0098.

Tarczyński G., (2019). Optymalizacja procesów magazynowych. Wybrane modele i metody. Wrocław: Wydawnictwo Uniwersytetu Ekonomicznego. ISBN: 978-83-7695-743-2.

Taylor G. D., (2008). Logistics Engineering Handbook. Boca Raton: CRC Press Taylor & Francis Group. https://doi.org/10.1201/9780849330537.

Tekez E.,Tasdeviren G., (2020). Measuring the influence values of lean criteria on leanness. Journal of Manufacturing Technology Management, 31(7), 1391-1416. https://doi.org/10.1108/JMTM-09-2019-0321.

Ulewicz R., Mazur M., (2015). Doskonalenie transportu wewnętrznego z wykorzystaniem koncepcji lean – studium przypadku. Przegląd Organizacji, 7 (906), 2015, 6-13. https://doi.org/10.33141/po.2015.07.01.

Vanheusden S., Van Gils T., Ramaekers K., Cornelissens T., Caris A., (2023). Practical factors in order picking planning: state-of-the-art classification and review. International Journal of Production Research, 61 (6), 2032-2056. https://doi.org/ 10.1080/00207543.2022.2053223.

Womack J.P., Jones D.T., (2008). Lean Thinking. Banish waste and create wealth in your corporation. Wrocław: ProdPress.com. https://doi.org/10.1038/sj.jors.2600967.