INTELLIGENT AUTOMATION-BASED MANUFACTURING SYSTEM OPTIMIZATION IMPROVES THE PRODUCTION EFFICIENCY OF MEDIUM-SCALE INDUSTRIES

Abstract

This study aims to analyze the role of intelligent automation-based manufacturing system optimization in improving production efficiency in medium-scale industries. The research uses a qualitative method with a case study design as this approach allows for an in-depth understanding of processes, system dynamics, as well as decision-making mechanisms in the actual manufacturing environment. The case study design was chosen to capture automation implementation holistically, especially in industries that are in the transition phase from manual systems to adaptive automation. The research location was carried out in the medium-scale manufacturing industry of the discrete manufacturing sector located in the Jababeka Industrial Estate, Bekasi Regency, West Java. The research informants consisted of five people consisting of production managers, engineering and automation supervisors, heads of information technology divisions, senior production operators, and quality control managers. The selection of informants is carried out purposively with consideration of direct involvement in the manufacturing system and operational decision-making. The results show that intelligent automation optimization integrated with information systems and the use of operational data can improve production efficiency, reduce process variability, and improve the quality of decision-making. This study recommends the systemic and gradual implementation of intelligent automation and the strengthening of data-driven decision-making in medium-scale industries.