REAL TIME SCHEDULING DENGAN KONSEP SISTEM PRODUKSI TERDISTRIBUSI MANDIRI (SPTM) DAN CONFIGURABLE VIRTUAL WORKSTATIONS (CVWS) UNTUK STUDI KASUS MANUFAKTUR BERBASIS DISKRET PADA SISTEM PRODUKSI SEL

Indonesia is currently undergoing the Making Indonesia 4.0 agenda, which aims to advance the manufacturing industry in line with the Industrial Revolution 4.0. One of the key factors in implementing this agenda is the digitalization of the manufacturing industry. The digitalization of manufacturing...

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Bibliographic Details
Main Author: Saraswati, Dita
Format: Final Project
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/76252
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Indonesia is currently undergoing the Making Indonesia 4.0 agenda, which aims to advance the manufacturing industry in line with the Industrial Revolution 4.0. One of the key factors in implementing this agenda is the digitalization of the manufacturing industry. The digitalization of manufacturing in Indonesia faces its own challenges due to majority of Indonesia’s manufacturing industry has labor – intensive nature. Therefore, this research aims to create real-time production scheduling as an effort for planning and monitoring the Indonesian manufacturing industry digitally, considering its labor-intensive nature. Real-time scheduling can generate a manufacturing schedule that suits the real-time condition of the shop floor. Therefore, the resulting schedule will be the most effective as a reference for the production system. In the design of this system, the theory of Autonomous Distributed Manufacturing System and Configurable Virtual Workstations will be used to obtain a flexible and responsive scheduling system to cope with disruptions that may occur on the production floor. The research was conducted through the design and testing of programs using Python language. The designed scheduling program utilizes the principle of backward iterative scheduling as its main approach. The program is designed to handle disruptions by rescheduling the system whenever triggering events occur. The program designed in this study has been proven to handle seven cases of manufacturing scheduling.