DEVELOPMENT OF PRODUCTION DATA MONITORING AND MANAGEMENT SYSTEM BASED ON CONFIGURABLE VIRTUAL WORKSTATION (CVWS): CASE STUDY OF FLAT WAGON ASSEMBLY

In general, the rollingstock assembly process is a process that has the characteristics of manual-based assembly, has strict quality control, low production volume, and has a lot of variety. In this assembly process, data for each product must be collected, organized, and managed properly, so tha...

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Bibliographic Details
Main Author: Arif Isyanto, Andi
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/68340
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:In general, the rollingstock assembly process is a process that has the characteristics of manual-based assembly, has strict quality control, low production volume, and has a lot of variety. In this assembly process, data for each product must be collected, organized, and managed properly, so that the entire production process can be monitored and traced properly. Management of production data that is and varied is difficult to do manually, so we need a system that can be used to monitor the production process during the process. This study proposes a design of framework for monitoring and managing production data based on Configurable Virtual Workstation (CVWs) in the rollingstock industry in Indonesia, with a case study of the flat wagon assembly process. The methodology used in this framework is by creating a virtual model of assembly elements according to real conditions on the shopfloor. Each of these virtual elements will be connected to each other to get the update information on the shopfloor accurately and transparently to build a cyber physical system as the first step towards Industry 4.0. Some of the information that can be obtained from the implementations of this system includes: 1) operator working hours; 2) ongoing operation; 3) product completion status; 3) material supply status; 4) product traceability. Based on this information, the actual conditions on the shopfloor can be known and monitored easily and accurately.