RECOMMENDATION OF FLEXIBLE JOBSHOP SCHEDULING PROBLEM TO MINIMIZE TARDINESS IN CV. CIPTA SINERGI MANUFAKTUR

• Main Author: IZRA MIRNA , RAJA
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/23809
• Institution: Institut Teknologi Bandung

CV. Cipta Sinergi Manufaktur (CSM) is a manufacture company that engaged in the metal industry and based on CAD/CAM technology and conventional machine. CSM adopts a flexible job shop concept with a make to order system. As it seen that the usage of CNC machine that could process more that one type of operation (process flexibility) is high in CSM. A good plan in production scheduling is needed to not only increasing the utility of machines, but also makes delivery be on time to customers. Nowadays, CSM faced with a problem. It is about its inability to fulfill the due date order that has been agreed with the customer. It is because there are no production scheduling method that are clearly used by CSM, scheduling is done manually by intuition and production manager’s work experience. During January to October 2016, there were 61% of customer order delivery delay with average delay is 25,5 days. This study aims to determine and suggest a flexible job shop analytical production scheduling model that could minimize tardiness that in accordance with the characteristics of CSM. Reference model that been used in this study is analytical production scheduling model by Roshanaei (2012). This model has a decision variable to choose a machine that will work the operation in an optimal way, start time and completion time of each operations, and total tardiness value. This model’s inputs are due date of each jobs, operation routing, and process time of each operations. The computation of its model is helped by LINGO 11.0. The proposed production scheduling model is tested by using CSM historical data from February 20th to 26th, 2017 and resulted in a reduction of tardiness, from 94.8 hours to 78.1 hours or about 17.61%. This result indicates that scheduling with the proposed model is better than the current scheduling model. <br />