IMPLEMENTASI PERBAIKAN LEAD TIME PROSES PRODUKSI CUTTING MENGGUNAKAN CLUSTERING DATA MINING DAN LEAN MANUFACTURING PADA PERUSAHAAN BAJA

STEVEN, EDWARD (2021) IMPLEMENTASI PERBAIKAN LEAD TIME PROSES PRODUKSI CUTTING MENGGUNAKAN CLUSTERING DATA MINING DAN LEAN MANUFACTURING PADA PERUSAHAAN BAJA. S2 thesis, Universitas Mercu Buana Jakarta.

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Abstract

In steel companies, there are some processes in the production such as cutting, machining and heat treatment. Production process begins with cutting process and then machining process and the last one is heat treatment process. It becomes background that gives challenge and needs continuous improvement on all aspects, mainly in the cutting process. The research is conducted at one of steel companies located in Pulogadung Industrial Estate. Purpose of the research is to know the factors which cause process lead time cannot be achieved. The methods used are clustering data mining and lean manufacturing. Clustering method can be used to focus on big data and find out clusters or same pattern. Those clusters are processed with weka software and using K-means algorithme. From the formed clusters, thus will be conducted the improvement idea using lean manufacturing such as Single Minute Exchange of Dies (SMED) ad Value Stream Mapping. By using those methods, cutting process lead time could be decreased. Cutting process lead time is affected by material dimension which is processed in the production. The thicker material's diameters, the longer time needed for the production process; as well as the preparation activities conducted while production process. With the methods used, lead time of cutting process increased from 3449 minutes to 2165 minutes (3 days to be 2 days). Meanwhile using the SMED activities cutting process lead time increased from 187 minutes to 136 minutes. Keywords: Clustering, SMED, Lean Manufacturing, Lead Time, Value Stream Mapping Pada sebuah industri baja, terdapat beberapa proses produksi yaitu produksi cutting, machining dan heat treatment. Proses produksi industri baja dimulai terlebih dahulu dari proses cutting kemudian proses machining dan yang yang terakhir heat treatment. Dengan latar belakang tersebut menjadikan tantangan dan perbaikan terus menerus di segala aspek proses terutama pada produksi cutting. Penelitian ini dilakukan di salah satu perusahaan baja yang berlokasi di daerah kawasan industri pulogadung. Penelitian ini bertujuan untuk mengetahui faktor yang menyebabkan lead time proses cutting tidak tercapai. Adapun metode yang digunakan adalah clustering data mining dan lean manufacturing. Dari metode clustering yang digunakan bertujuan untuk memfokuskan big data dan menemukan cluster atau kesamaan data yang terbentuk. Cluster tersebut diolah menggunakan software Weka serta algoritma K-means yang akan digunakan. Dari cluster yang terbentuk maka akan dilakukan ide perbaikan menggunakan lean manufacturing seperti Single Minute Exchange of Dies (SMED) dan value stream mapping. Dengan menggunakan metode tersebut dapat menurunkan lead time proses cutting. Lead time proses cutting tersebut dipengaruhi oleh dimensi material yang diproses saat produksi. Dimana semakin tebal diameter material proses produksi membutuhkan waktu yang akan makin lama juga serta aktivitas persiapan yang dilakukan selama proses produksi. Dari hasil perbaikan tersebut dapat meningkatkan lead time proses cutting dari 3449 menit menjadi 2165 menit yang dimana berawal dari 3 hari menjadi 2 hari, sedangkan dengan metode Single Minute Exchange of Dies dari 187 menit menjadi 136 menit dari aktivitas yang dilakukan pada proses produksi cutting. Kata Kunci: Clustering, SMED, Lean Manufacturing, Lead Time, Value Stream Mapping

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