Studi Literatur Konsep dan Implementasi Sains Data untuk Memaksimalkan Kinerja Industri Manufaktur

Abstract

The manufacturing industry is currently faced with increasingly complex and diverse challenges. To address this challenge, companies need an approach based on data science to improve production performance and efficiency. This paper proposes the concept and implementation of data science in the manufacturing industry. Several important concepts in data science, including predictive analysis, prescriptive analysis, and optimization, are introduced. It also highlights the algorithms and data analysis techniques used to maximize production performance and reduce costs. Implementing data science in the manufacturing industry involves steps such as data collection, data processing, data analysis, and decision-making. Several use cases of data science in the manufacturing industry, including predictive analytics to forecast machine failures, prescriptive analysis to increase productivity, and optimization to optimize production schedules, are discussed here. The results of this scientific paper show that implementing data science in the manufacturing industry can significantly improve production performance and efficiency. This scientific paper provides useful insights for practitioners, researchers, and policymakers in the manufacturing industry who are interested in applying data science to production processes