ANALYSIS OF DELIVERY DELAYS USING STATISTICAL PROCESS CONTROL AT 3PL COMPANY
DOI:
https://doi.org/10.53866/jimi.v4i4.654Keywords:
Statistical Process Control, Delay, Shipment, OperationalAbstract
This study aims to analyze the causes of delivery delays at PT XYZ. Delivery delays have become a critical issue as they can affect customer trust and result in potential losses for the company. The study identifies two main causes of delivery delays: shipping schedules and the aging (storage time) of goods in the warehouse. The method used in this research is Statistical Process Control, which involves several analytical tools such as P-chart, Pareto diagram, fishbone diagram, histogram, and scatter plot. The analysis results show that shipping schedules have a significant impact on delivery delays, with several delivery periods falling outside the upper control limit and lower control limit. Additionally, goods aging exceeding seven days also contribute to delays. Other influencing factors include human aspects (data entry errors), environmental factors (bad weather and changes in shipping schedules), methods (schedule mismatches), and measurements (inaccurate stock data). The study recommends several improvements to enhance delivery efficiency, including optimizing stock recording processes, strengthening work discipline, and improving human resource quality through operational training.
References
Aini, N., Kusumaningrum, R., Mustafid, & Hidayat, E. (2017). Statistical Process Control Systems in Apparel Production. IEEE.
Alifka, K. P., & Apriliani, F. (2024). Analisis Pengendalian Kualitas Produk Menggunakan Metode Statistical Process Control (SPC) dan Failure Mode and Effect Analysis (FMEA). Factory Jurnal Industri, Manajemen Dan Rekayasa Sistem Industri, 2(3), 97–118. https://doi.org/10.56211/factory.v2i3.486
Attaqwa, Y., Hamidiyah, A., Firman, R., Ekoanindyo, A., & Semarang, U. S. (2021). Product Quality Control Analysis with Statistical Process Control (SPC) Method in Weaving Section (Case Study PT.I). In International Journal of Computer and Information System (IJCIS) Peer Reviewed-International Journal (Vol. 02, Issue 03). https://ijcis.net/index.php/ijcis/index
Evant, I., Fayaqun, R., & Sutisna, E. (2023). ANALISIS KETERLAMBATAN PENGIRIMAN BARANG MENGGUNAKAN METODE FAILURE MODE AND EFFECTS ANALYSIS (FMEA). In Jurnal Mahasiswa Teknik Informatika (Vol. 7, Issue 4).
Holifahtus Sakdiyah, S., Eltivia, N., & Afandi, A. (2022). Root Cause Analysis Using Fishbone Diagram: Company Management Decision Making. Journal of Applied Business, Taxation and Economics Research, 1(6), 566–576. https://doi.org/10.54408/jabter.v1i6.103
Kurnia, H., Setiawan, S., & Hamsal, M. (2021). Implementation of statistical process control for quality control cycle in the various industry in Indonesia: A systematic literature review. Operations Excellence: Journal of Applied Industrial Engineering, 13(2), 194. https://doi.org/10.22441/oe.2021.v13.i2.018
Palupi Robustin, T., Latifa Isnaini Putri, N., Hakim, I., Lumajang, G., & Author, C. (2024). Service Delivery System and Satisfaction in influencing Customer Loyalty at Balung Regional Hospital. Jurnal Ilmu Manajemen Advantage, 8(1). https://doi.org/10.30741/adv.v8i1.1315
Panayides, P. M., & So, M. (2005). Logistics service provider–client relationships. Transportation Research Part E: Logistics and Transportation Review, 41(3), 179–200.
Santhanakrishnan, D. (2017). A STUDY ON THE EFFICIENCY OF 3PL LOGISTICS. www.dvpublication.com
Tanaka, R., Ishigaki, A., Suzuki, T., Hamada, M., & Kawai, W. (2019). Determination of shipping timing in logistics warehouse considering shortage and disposal in textile industry. Procedia Manufacturing, 39, 1567–1576. https://doi.org/10.1016/j.promfg.2020.01.285
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Copyright (c) 2024 Jenni Br Tarigan, Syarif Hidayatuloh, Nabila Noor Qisthani, Yulinda Uswatun Kasanah
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