PERANCANGAN SISTEM PEMANTAUAN AKTIVITAS PRODUKSI BERBASIS INTERNET OF THINGS DAN CLOUD UNTUK INDUSTRI MAKE-TO-ORDER

The corona virus (Covid-19) has given significant impact which results to limit works that involves social and physical activities, so it was replaced by Working from Home (WFH) method. This condition has made it necessary for doing a performance monitoring remotely. Industry 4.0 technologies wer...

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Bibliographic Details
Main Author: C Adisasmito, Senapati
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/57713
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Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:The corona virus (Covid-19) has given significant impact which results to limit works that involves social and physical activities, so it was replaced by Working from Home (WFH) method. This condition has made it necessary for doing a performance monitoring remotely. Industry 4.0 technologies were able to fulfil these needs due to the capabilities on transmitting data through the internet. These needs can be achieved by using production activity monitoring system that uses Internet of Things (IoT) and cloud technology. This research objective is to design and evaluate solutions for production activity monitoring that uses IoT and cloud technology, which includes part tracking, operator activities, and machine utilization. The research proposed 4 (four) alternatives of solution for production activity monitoring system that uses IoT and cloud technology. The 1st alternative, which is an IoT module that uses relay, and have the most accurate data. The 2nd alternative which is an IoT module that uses current sensor as the most affordable alternative. The 3rd alternative, which is an IoT module that uses current sensor, and have more input/output port for further development of additional IoT sensors and other functionalities. The 4th alternative, which is an IoT module that integrates current sensor with the built-in WiFi connection, as the easiest alternative to be implemented. The generated data includes machining time which consists of productive and non-productive time that will be used for cost estimation, and also to track the operator activities and the part progress in the shop-floor.