PRE-ORDER SCHEDULING THAT CONSIDERING READY TIME MACHINE BY USING INTERNET OF THINGS
CV Cipta Sinergi Manufacturing (CSM) is a Make-to-Order (MTO) company who engaged in production of machinery products. Currently, the company has problems with on time delivery, which is 76% with a target of 80%. One of the causes of the delay is the poor production scheduling system at CV CSM. When...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/70221 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | CV Cipta Sinergi Manufacturing (CSM) is a Make-to-Order (MTO) company who engaged in production of machinery products. Currently, the company has problems with on time delivery, which is 76% with a target of 80%. One of the causes of the delay is the poor production scheduling system at CV CSM. When there is a new pre-order to be scheduled, the operator cannot estimate exactly when the pre-order will be completed because they do not know the real time of the machining process and do not know whether the machines are currently busy or not. Beside that, operators also need to insert new pre-orders into production schedule manually with the objective of minimizing makespan with the completion time according to the due date for all jobs. Manual scheduling makes the results not accurate and the products are not completed according to the estimated time. Therefore, this study aims to schedule IoT-based pre-orders considering the ready time of the machines.
Scheduling is automatically done by using a non-delay algorithm to schedule weekly orders and a job insertion algorithm to schedule new pre-order. These scheduling algorithms are programmed in Pyhton programming language. Then, machine’s ready time status in real time is obtained using Internet of Things (IoT) prototype with ESP8266 as hardware and Google Firebase as NoSQL database. Input data in the form of routing and processing time are done by product similarity research which is carried out parallel with this research. These data are sent with cloud in the form of Notepad (.txt) and connected to the scheduling algorithm. In addition, Executeable File (.exe) is used to run the program and view the scheduling output.
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