Redesigning the Oxygen Gas Distribution Business Process for Process Time Efficiency from Department to Shipping

Authors

  • Naufal Abdurrahman Hawari Universitas Sumatera Utara
  • Tuti Sarma Sinaga Universitas Sumatera Utara
  • Humala L. Napitupulu Universitas Sumatera Utara
  • Ukurta Ukurta Universitas Sumatera Utara

DOI:

https://doi.org/10.57152/malcom.v6i4.2781

Keywords:

BPMN, Business Process Reengineering, Root Cause Analysis, Time Study, 5W 1H Analysis

Abstract

Inefficiencies often occur in company operations due to mismatches between business processes implemented in Enterprise Resource Planning (ERP) systems and operational practices. This study aims to improve the business processes of an industrial gas manufacturer that experiences delays in meeting customer needs due to inconsistencies within its ERP system. Business Process Reengineering (BPR) is applied through fundamental rethinking and radical redesign to improve process efficiency. The fundamental rethink stage begins with developing a Business Process Model and Notation (BPMN) model to map the current business process (As-Is), followed by 5W+1H analysis, Root Cause Analysis (RCA), and time study. The radical redesign stage involves developing a proposed business process (To-Be) based on the problems. The results indicate that the main problems are concentrated in the distribution unit, particularly manual communication, duplicate data entry, and limited integration between work units. The time study shows that the initial business process requires an average of 4 hours, 41 minutes, and 39 seconds. The proposed business process reduces the processing time to 3 hours, 37 minutes, and 25 seconds. These results demonstrate that the redesigned process improves operational efficiency by 22.8% and provides an integrated, efficient, and responsive business process

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Published

2026-08-15

How to Cite

Hawari, N. A., Sinaga, T. S., Napitupulu, H. L., & Ukurta, U. (2026). Redesigning the Oxygen Gas Distribution Business Process for Process Time Efficiency from Department to Shipping. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 6(4), 1816-1826. https://doi.org/10.57152/malcom.v6i4.2781