Pengendalian Kadar Air Crude Palm Oil (CPO) Pada Mesin Vacuum Dryer Menggunakan Metode Statistical Process Control (SPC) dan Kaizen Pada Pabrik Kelapa Sawit

Abstract

Penelitian ini bertujuan untuk menganalisis dan mengendalikan kadar air pada Crude Palm Oil (CPO) di salah satu perusahaan kelapa sawit dengan menggunakan metode Statistical Process Control (SPC) dan Kaizen. Kadar air merupakan parameter kritis kualitas dengan batas maksimum 0,20% yang telah di tetapkan. Data dikumpulkan melalui observasi langsung dengan pengambilan sampel CPO pada proses produksi, serta pengujian laboratorium secara berkala selama periode Juli–Agustus 2025. Penerapan metode Statistical Process Control (SPC) dilakukan secara sistematis melalui beberapa tahapan, yaitu pengumpulan data kadar air menggunakan check sheet, penentuan batas kendali atas (UCL) dan batas kendali bawah (LCL), serta penyusunan peta kendali Xbar-R untuk mengevaluasi kestabilan proses. Selanjutnya, dilakukan identifikasi titik yang berada di luar batas kendali (out of control) sebagai indikasi adanya penyimpangan proses yang memerlukan analisis lebih lanjut. Identifikasi penyebab variasi, digunakan diagram sebab-akibat berdasarkan faktor 5M+1E yang diperoleh melalui penyebaran kuesioner kepada pihak terkait. Faktor dominan meliputi ketidakoptimalan kinerja vacuum dryer, kualitas bahan baku yang tidak konsisten, serta ketidaksesuaian prosedur operasional. Selanjutnya, pendekatan Kaizen melalui 5W+1H digunakan untuk merumuskan usulan perbaikan. Usulan perbaikan mencakup optimalisasi dan perawatan rutin mesin, peningkatan kualitas serta penanganan bahan baku, penguatan kepatuhan terhadap prosedur kerja, peningkatan kompetensi operator, serta pengawasan dan pengukuran yang lebih konsisten. Implementasi perbaikan diharapkan mampu menurunkan kadar air sesuai standar serta meningkatkan stabilitas proses dan kualitas CPO.

This study aims to analyze and control the moisture content of Crude Palm Oil (CPO) in a palm oil processing company using Statistical Process Control (SPC) and Kaizen methods. Moisture content is a critical quality parameter with a maximum allowable limit of 0.20%. Data were collected through direct observation by sampling CPO during the production process, as well as periodic laboratory testing over the July–August 2025 period. The implementation of Statistical Process Control (SPC) was carried out systematically through several stages, including collecting moisture content data using a check sheet, determining the upper control limit (UCL) and lower control limit (LCL), and constructing Xbar-R control charts to evaluate process stability. Subsequently, points outside the control limits (out of control) were identified as indications of process deviations requiring further analysis. To identify the causes of variation, a cause-and-effect (fishbone) diagram based on 5M+1E factors was developed using questionnaire data obtained from relevant personnel. The dominant factors include suboptimal performance of the vacuum dryer, inconsistent raw material quality, and non-compliance with operational procedures. Furthermore, the Kaizen approach using the 5W+1H method was applied to formulate improvement actions. The proposed improvements include optimizing and performing routine maintenance of machinery, improving raw material quality and handling, strengthening adherence to operational procedures, enhancing operator competence, and ensuring more consistent monitoring and measurement. The implementation of these improvements is expected to reduce moisture content to meet the required standards and improve process stability as well as overall CPO quality.