Pemanfaatan limbah pelepah sawit dapat diolah sebagai pakan ternak, kompos, pembuatan briket, dan bahan dasar panel komposit. Pemanfaatan limbah pelepah kelapa sawit untuk berbagai tujuan tersebut diproses dengan cara mencacahnya menjadi cacahan berukuran kecil. Proses pencacahan dengan menggunakan mesin pencacah memberikan kemudahan bagi petani dan mempercepat waktu pencacahan. Beberapa penelitian telah dilakukan pada proses pencacahan pelepah daun kelapa sawit  dengan menggunakan motor penggerak yang berbeda-beda dan berbagai model pisau potong, daya motor, serta kecepatan putaran motor yang bervariasi dengan tujuan untuk mendapatkan kapasitas efektif mesin yang optimal. Metode perancangan yang digunakan dalam pembuatan mesin adalah metode Pahl Beitz, yaitu perencanaan, perancangan konsep produk, perancangan bentuk, dan perancangan detail. Parameter yang diamati dan diukur pada mesin adalah kapasitas efektif mesin, rendemen cacahan, dan ukuran panjang hasil cacahan. Uji coba dilakukan sebanyak tiga kali pengulangan dengan mencacah pelepah yang ditimbang masing-masing seberat 5 kg. Hasil uji coba terhadap mesin pencacah pelepah kelapa sawit sistem rotary menunjukkan bahwa kapasitas efektif mesin rata-rata adalah sebesar 244,06 kg/jam sehingga termasuk dalam kategori kelas A. Rendemen cacahan rata-rata pada mesin adalah sebesar 97 % dan ukuran rata-rata cacahan ? 50 mm adalah sebesar 89,5 % dan telah memenuhi syarat SNI 7580 : 2010.

Setting parameters in the injection molding machine play an important role to the quality of cable ties product. They affect not only to the number of the rejection products but also to their tensile yield strength. The goal of this study is to obtain a combination of process parameters such as nozzle temperature, injection pressure, injection flow, and switch-over to holding pressure, which results the optimal tensile yield as the observed response using Back Propagation Neural Network-Genetic Algorithm (BPNN-GA). In this study, a 4-8-8-1 BPNN model was applied to predict the tensile yield based on a random combination of process parameters. The tensile yield then was optimized by genetic algorithm through several iterations. The optimal tensile yield of 28.44 MPa has been obtained using the following combination i.e. nozzle temperature of 250 oC, injection pressure of 1400 bar, injection flow of 40 cm3/s, and switch-over to holding pressure of 13,2 cm3.

Peanut cake is one of the typical Indonesian pastries which includes the most popular cakes by Indonesian people including the people of the Province of Bangka Belitung Islands. The process of processing peanut cakes through several stages, namely the processing of peanuts, the printing of bean cake dough. The current method of printing peanut cakes is still manually using one by one as a tool to print the bean cake. The purpose of this study is to design and make a bean cake printing tool that is capable of printing 20 bean cakes in one process. The stages in making this bean cake printing device start from problem identification, planning, designing, tool making, assembling, and testing. Based on the results of the trials that have been carried out, the tool is capable of printing 20 prints in a single process and the dough is not attached to the mold.

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The benchmark for the results of the machining process can be seen from the results of the products, one of which is the level of surface smoothness. The purpose of this experimental research is to find out how much cutting speed (Vc) and depth of cutting produce a workpiece with the smoothest level of surface roughness for the turning process carried out by students at the Bangka Belitung State Manufacturing Polytechnic Workshop. This research is using experimental method. The cutting speeds (Vc) used were 23 m/min, 24 m/min, 25 m/min, the cutting depths used were 0.5 mm, 0.8 mm, and 1.0 mm and the feeding speed was set at 0.040 mm/rev. The results showed that the best turning results using a cutting speed (Vc) of 23 m/min was using a cutting depth of 0.5 mm with a roughness value (Ra) of 1.372 m, using a cutting speed (Vc) of 24 m/min using a depth of cut. 0.5 mm with a roughness value (Ra) of 1.189 m and using a cutting speed (Vc) of 25 m/min using a depth of 0.5 mm with a surface roughness value (Ra) of 3.14 m. The lowest value for the level of surface roughness of the turning process was obtained using a cutting speed (Vc) of 24 m/min with a depth of 0.5 mm with a surface roughness value (Ra) of 1.189 m.