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"This research is for one of the pharmaceutical companies in Indonesia. The company's production area is composed of two parts, namely a Black Area and a Grey Area for processing and packaging. There are four types of packaging in the Secondary Packaging Area. Each type of packaging uses different processes, but there are also some processes that are used by all types of packaging. Based on these observations, the layout of the production area for secondary packaging in the pharmaceutical company is not optimal because the material handling distances are still quite long and there are some similar processes for same packaging type that are not adjacent, so that the production process is inefficient. This study aims to redesign the layout in the area with the Computerized Relationship Layout Planning (CORELAP) method. Data such as the name of the process, the order of the process, and the relationship between processes into the Activity Relationship Chart (ARC), are subsequently processed to obtain the Total Closeness Rating (TCR) values for each process iterated with the CORELAP method. From the calculations, the proposed layout has material handling distances that are shortened by 9.017% compared with the current layout. The same type of packaging processes are located in adjacent positions."

"PT. XYZ merupakan salah satu perusahaan yang bergerak di bidang farmasi di Indonesia. Area produksi perusahaan ini terdiri dari dua bagian, yaitu Black Area dan Grey Area (Secondary Packaging). Terdapat empat jenis pengemasan pada area secondary packaging. Setiap jenis kemasan menggunakan proses yang berbeda-beda, tetapi ada juga beberapa proses yang dipakai oleh semua jenis kemasan. Berdasarkan pengamatan, tata letak area produksi secondary packaging atau grey area PT. XYZ dirasa masih kurang baik karena jarak perpindahan material yang masih cukup panjang dan terdapat beberapa proses dari kemasan yang sejenis yang belum berdekatan sehingga kurang mendukung kelancaran proses produksi. Penelitian ini betujuan untuk memperoleh rancangan ulang tata letak pada area tersebut dengan metode CORELAP. Data berupa nama proses, urutan proses, dan hubungan antar proses diolah menjadi ARC yang selanjutnya diolah untuk mendapat nilai TCR masing-masing proses untuk diiterasi dengan metode CORELAP. Dari hasil perhitungan diperoleh bahwa tata letak usulan hasil perhitungan metode CORELAP memiliki jarak perpindahan material yang lebih pendek 9,017% dibanding tata letak saat ini dan proses dari pengemasan yang sejenis posisinya menjadi lebih berdekatan dan lebih teratur.

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PT. XYZ is a pharmaceutical company in Indonesia. The company's production area is composed of two parts, namely Black Area and Grey Area Area (Secondary Packaging). There are four types of packaging in the area of secondary packaging. Each type of packaging uses different processes, but there are also some processes that is used by all types of packaging. Based on the observations, the layout of the production area of secondary packaging of PT. XYZ is still not optimal because the material handling distance is still quite long and there are some similar process of same packaging type that is not adjacent, so that the production process is less smooth.

This study aims to obtain redesign the layout in the area with CORELAP method. Data such as the name of the process, the order process, and the relationship between process processed into ARC, subsequently processed to obtain TCR values for each process to iterated with CORELAP method. From the calculations, the proposed layout has a material handling distance is shorter 9.017% compared to the current layout and also the process of same type packaging become more adjacent."

"Focused manuscript on the potential use/role of miRNAs in bioprocessing, specifically the production of complex proteins in mammalian cells. With that in mind I propose a draft list of topics/chapters along the following lines, intro on CHO/bioprocessing/engineering challenges to set scene, genomic organization, biogenesis and mode of action, Identifying miRNA targets, computational prediction, transcriptomics, proteomices, UTR analysis, etc., miRNA expression in Chinese hamster ovary cells, miRNAs as engineering targets: pathway manipulation to impact bioprocess phenotypes, miRNAs as biomarkers, detection methods : northern, PCR, hybridization arrays, next gen seq, manipulation of expression in cultured cells : transient/stable disregulation, knockout."

"ABSTRAKFormaldehida merupakan senyawa kimia yang populer dengan banyak kegunaan, dengan jumlah kebutuhan yang cenderung terus bertambah. PT X merupakan salah satu produsen formaldehida yang masih memiliki permasalahan terkait kapasitas produksinya. PT X masih menggunakan pengendali Proportional-Integral (PI) yang masih mempunyai ruang untuk peningkatan produksinya. Model Predictive Control (MPC) digunakan untuk mengoptimalisasikan parameter pengendalian proses produksi formaldehida di PT X. Model empiris dibuat untuk diterapkan pada pengendali MPC berdasarkan Process Reaction Curve (PRC) dengan menggunakan pendekatan First Order Plus Dead Time (FOPDT). Kinerja pengendali diuji menggunakan set point (SP) tracking dan disturbance rejection. Ada empat pengendali yang diuji, yaitu pengendali laju alir steam (FIC-102), pengendali temperatur udara (TIC-101), pengendali level evaporator (LIC-101), dan pengendali tekanan evaporator (PIC-101). Didapatkan hasil model empirik FOPDT untuk masing-masing pengendali, dengan nilai parameter pengendalian Prediction Horizon (P), Control Horizon (M), dan Sampling Time (T) yang optimal secara berurutan: (1, 2, dan 1) pada FIC-102, (62, 21, dan 1) pada TIC-101, (50, 10, dan 6) pada PIC-101, dan (70, 21, dan13) untuk LIC-101. Terjadi perbaikan kinerja berdasarkan uji perubahan nilai set point baik dihitung melalui IAE maupun ISE sebesar 26,9% dan 8,03% untuk FIC-102, 15,37% dan 32,51% untuk TIC-101, 13,37% dan 25,9% pada PIC-101, serta 23,35% dan 6,71% pada LIC-101. Pada uji disturbance rejection juga terjadi perbaikan kinerja baik dihitung melalui IAE maupun ISE sebesar 96,4% dam 99.74% untuk FIC-102, 13,37% dan 25,9% untuk TIC-101, 54,25% dan 76,67% pada PIC-101, serta 15,96% dan 4,4% pada LIC-101.

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ABSTRACT

Formaldehyde is a chemical compound known for its many uses, with the increase of its demand. PT X is one of the producers of formaldehyde that has problems related to its production capacity. PT X right now still uses Proportional-Integral (PI) that still have rooms of improvements. Model Predictive Control (MPC) is used to optimize the process control parameters of formaldehyde production in PT X. The empirical model is made for the MPC based on the Process Reaction Curve (PRC) using First Order Plus Dead Time (FOPDT). The control performance is tested using set point (SP) tracking and disturbance rejection. There are four controls that were tested, which are steam flow control (FIC-102), air temperature control (TIC-101), evaporator level control (LIC-101), and evaporator pressure control (PIC-101). Thus, the results of the empirical FOPDT model for each control is obtained, with the value of Prediction Horizon (P), Control Horizon (M), and Sampling Time (T) parameters are optimal and its value respectively are: (1, 2, and 1) for FIC-102 , (62, 21, and 1) for TIC-101, (50, 10, and 6) for PIC-101, and (70, 21, and 13) for LIC-101. The performance improvement based on the set point change test calculated through the IAE and ISE are 26.9% and 8.03% for FIC-102, 15.37% and 32.51% for TIC-101, 13.37% and 25, 9% for PIC-101, and 23.35% and 6.71% for LIC-101. Based on the disturbance rejection test it is also improvements on the performance both calculated through the IAE and ISE of 96.4% and 99.74% for FIC-102, 13.37% and 25.9% for TIC-101, 54.25% and 76.67% for PIC-101, and 15,96% and 4.4% on the LIC-101."