Penerapan algoritma non-delay dan algoritma genetika dalam penjadwalan produksi job shop untuk meminimasi total completion time dan number of tardy job pada semi finish komponen di PT. Katsushiro Indonesia
P Persaingan perusahaan industri manufaktur di Indonesia semakin kompetitif. Terpenuhinya kepuasan pelanggan dalam pemenuhan order tepat waktu merupakan target utama setiap perusahaan. Maka dari itu, penjadwalan produksi yang tepat berperan penting dalam aktivitas produksi. PT. Katsushiro Indonesia bergerak di bidang produksi komponen alat berat berupa semi finish komponen dan fabrication parts. Pola aliran produksi perusahaan bertipe job shop karena memiliki pola aliran proses yang berbeda pada setiap job. Semi finish komponen merupakan komponen alat berat yang dihasilkan melalui proses first production dan second process (machining), sedangkan fabrication parts dilanjutkan sampai proses fabrikasi. Permasalahan yang dihadapi saat ini adalah keterlambatan dalam penyelesaian produksi semi finish komponen. Keterlambatan terjadi karena penjadwalan produksi tidak terstruktur dengan baik. Tujuan penelitian ini adalah untuk memberikan usulan penjadwalan produksi menggunakan metode Algoritma Non-Delay dan Algoritma Genetika untuk meminimasi total completion time dan number of tardy job penyelesaian produksi semi finish komponen di PT. Katsushiro Indonesia. Pertama mengidentifikasi total completion time dan number of tardy job penjadwalan perusahaan, untuk bulan Oktober 2016 21 hari dan 37 tardy job, November 2016 20 hari dan 15 tardy job, Desember 2016 20 hari dan 28 tardy job. Usulan penjadwalan produksi berdasarkan Algoritma Non-Delay, mendapatkan nilai total completion time dan number of tardy job lebih baik yaitu bulan Oktober 2016 berkurang sebanyak 9 hari dan 21 tardy job, November 2016 berkurang sebanyak 8 hari dan 10 tardy job, dan Desember 2016 berkurang sebanyak 8 hari dan 23 tardy job dari kondisi awal, menggunakan Algoritma Genetika terpilih Job-Pair Exchange Mutation pada November 2016 diperoleh total completion time dan number of tardy job berkurang sebanyak 9 hari dan 11 tardy job dari kondisi penjadwalan perusahaan.
T The competition of manufacturing industry companies in Indonesia becomes more competitive. The fulfillment of customer satisfaction in on time order fulfillment is the main target of every company. Therefore, production scheduling hold an important role in production activities. PT. Katsushiro Indonesia is engaged in the production of heavy equipment components such as semi finish components and fabrication parts. The production flow pattern of the company is job shop type because it has different process flow pattern on each job. Semi finish components is one of heavy equipment components produced through first production and second process (machining) processes, while fabrication parts are continued until fabrication process. The issues that are being faced is the tardiness in completion of semi-finished component production. The tardiness occurs because production scheduling are not well structured. The purpose of this research is to give an input on the production scheduling plan using Non-Delay Algorithm and Genetic Algorithm method to minimize total completion time and number of tardy job completion of semi finish componenst at PT. Katsushiro Indonesia. First to identify total completion time and number of tardy job of scheduling company, for October 2016 21 day and 37 tardy job, November 2016 20 day and 15 tardy job, December 2016 20 day and 28 tardy job. The proposed production scheduling based on Non-Delay Algorithm, get a better total value of completion time and number of tardy job for October 2016 decreased by 9 days and 21 tardy job, November 2016 decreased by 8 days and 10 tardy job, and December 2016 decreased as much 8 days and 23 tardy jobs from the initial conditions, using the selected Job-Pair Exchange Mutation Genetic Algorithm in November 2016 it was obtained that the total completion time and the number of tardy job were reduced by 9 days and 11 tardy jobs from the company's scheduling condition.