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"Pada tahun 2015, Indonesia diproyeksikan mengalami defisit bahan bakar minyak sebesar 562.000 barrel/ hari. Untuk menutupi defisit tersebut diperlukan upaya luar biasa berupa pembangunan terminal transit bahan bakar minyak impor atau pembangunan kilang baru dan modifikasi kilang eksisting dengan kapasitas pengolahan sebesar minimal 300.000 barrel/ hari guna menjaga ketahanan energi nasional. Disain kilang yang ada harus dipasang dengan sistem pengendalian untuk menghindari gangguan pada proses yang berdampak pada keefektifan dan kestabilan operasi pabrik. Pada awalnya minyak bumi akan diproses pada bagian Crude Distillation Unit (CDU) untuk mendapatkan produk straight run. Unit ini sangat menentukan rate produk sehingga perlu diterapakan konfigurasi sistem pengendalian yang optimum. Jenis pengendali yang akan diterapkan pada penelitian ini adalah pengendali PI (Proportional - Integral) karena dapat menangani hampir setiap situasi pengendalian proses di dalam skala industri. Telah banyak rancangan kilang dengan model konfigurasi tertentu dan metode pengendali tertentu, misalnya kilang dengan dominasi produk bensin dengan pengendali PID dan kilang dengan dominasi produk kerosene dengan pengendali PI. Pengendalian proses kolom distilasi ini dilakukan dengan mensimulasikan secara dinamik pada perangkat lunak Aspen Hysys v.8. Penyetelan pengendali dilakukan untuk mendapatkan parameter kinerja alat kendali yang optimum yaitu dihitung berdasarkan metode Ziegler - Nichols, Lopez dan fine tunning. Sebagai hasilnya, pada pengendali laju alir diesel dan light naphta, pengendali tekanan pada reboiler, dan pengendali temperatur feed masukan kolom distilasi digunakan penyetelan Lopez. Sedangkan untuk pengendali laju alir AGO (atmospheric gas oil) dan level kondenser digunakan penyetelan fine tuning.

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By 2015, Indonesia is projected in deficit of fuel oil by 562.000 barrels/ day. To cover that deficit, Indonesia requires a tremendous efforts such as the construction of a transit terminal which is imported fossil fuels or the construction of new refineries and modification of the existing refinery with a processing capacity of at least 300.000 barrels/ day in order to maintain national energy security. The design of the existing refinery has to be fitted with a control system to avoid interruptions that have an impact on the effectiveness and stability of plant operations. At first, crude oil will be processed at the Crude Distillation Unit (CDU) to obtain straight run products. This unit will determine the rate of product that needs to be applied an optimum configuration of system control. PI controller (Proportional - Integral) will be applied to the system control because it can handle almost any situation in process control in industrial scale. Have many designs refineries with a particular configuration model and specific control methods, such as a refinery with a petrol product dominance with a PID controllers and refineries with kerosene product dominance with a PI controller. The distillation column of process control is done by simulating the plant dynamically in Aspen Hysys v.8 software. Adjustments made to obtain the optimum performance parameters of control device that is calculated based on Ziegler - Nichols, Lopez and fine tunning methods. As a result, the diesel and light naphtha flowrate controllers, reboiler pressure controller, and input feeds temperature of a distillation column controller used Lopez adjustment. As for the AGO (atmospheric gas oil) flowrate controller and the level of conndenser controller used fine tuning adjustment."

"Laju pertumbuhan penduduk Indonesia memaksa konsumsi akan bahan bakar terus meningkat, karena saat ini bahan bakar telah menjadi salah satu kebutuhan utama masyarakat modern di Indonesia. Sebagian besar bahan bakar tersebut berasal dari minyak bumi yang dalam satu dekade ini produksinya mengalami penurunan di dalam negeri. Oleh sebab itu peluang pengembangan energi alternatif harus terus di kembangkan di Indonesia, salah satunya dengan membuat Pabrik Dimetil Eter (DME) dengan bahan baku utama gas sintesis. Gas sintesis ini diperoleh dari gas alam melalui proses autotermal reforming. Indonesia sendiri memiliki cadangan gas alam yang lebih besar ketimbang minyak bumi. DME dipilih karena merupakan bahan bakar alternatif yang ramah lingkungan. Proses pembuatan DME secara indirect melibatkan sintesis metanol, dehidrasi metanol, purifikasi DME hingga purifikasi metanol untuk di recylce. Dalam penelitian ini akan dijelaskan sistem pengendalian pada proses purifikasi DME hingga purifikasi metanol. Unit-unit yang ada pada proses purifikasi DME ialah unit heater, unit distilasi DME, unit cooler, unit flash drum dan unit storage tank, sedangkan pada proses purifikasi metanol terdapat unit distilasi metanol, unit cooler dan unit pompa. Pengendalian pada kedua proses purifikasi itu penting untuk menjaga proses tetap pada kondisi optimumnya. Proses purifikasi DME dan Metanol ini mengandalkan Unit Distilasi yang memiliki temperatur operasi hingga 190oC dan tekanan hingga 1950 kPa. Sistem pengendalian yang dipilih untuk proses ini ialah jenis pengendali Proportional Integral (PI) karena dapat menangani hampir setiap situasi kontrol proses di dalam skala industri. Penelitian ini menggunakan pemodelan penyetelan pengendali Ziegler Nichols dan Lopez, lalu dibandingkan nilai parameter kinerja pengendalinya yaitu Offset, Rise Time, Time of First Peak, Settling Time, Periode osilasi, Decay Ratio, Overshoot, Deviasi maksimum, Integral Absolute Error (IAE) dan Integral Square Error (ISE) dari kedua jenis penyetelan tersebut. Hasil penelitian ini dapat digunakan untuk penentuan variabel input dan output yang optimum pada proses purifikasi DME dan Metanol yang dapat diterapkan pada pabrik DME.

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Increases of Indonesia’s population makes consumption of fuel was high, because nowadays fuel become primary needs for modern people in Indonesia. Fuel in Indonesia is mostly from petroleum, which is has slowly production in one decade behind. Therefore, chance in alternative energy must be develop in Indonesia, one of them is making Industry of Dimethyl Ether (DME) from synthetic gas feed. Synthetic gas was get from natural gas in autothermal reforming process. Indonesia has more reserve natural gas than petroleum. The another benefit from DME is friendly for our environment as alternative fuel. Indirect process in production of DME consists of synthesis methanol, dehidration methanol, purification DME and purification methanol for recycle.

The research will explain about control system in purification DME and purification methanol. Purification DME consists of heater, distillation column of DME, cooler, flash drum and storage tank, furthermore purification methanol consists of distillation column of methanol, cooler and pump. Controlling both of purification process is really important to keep the process in optimum condition. Purification process of DME and methanol used distillation column in temperature up to 190oC and pressure up to 1950 kPa.

Type of control system in this research is Proportional Integral (PI) controller, it is because the controller can handle much process control condition in industry scale. This research used tuning model Ziegler Nichols and Lopez, then compares the performance parameter of Offset, Rise Time, Time of First Peak, Settling Time, Osilation Period, Decay Ratio, Overshoot, Maximum Deviation, Integral Absolute Error (IAE) and Integral Square Error (ISE) by both tuning model. The result of this research can be use to define optimum input and output variable in Purification process of DME and Methanol that can applied in Industry of DME."

"This applied, self-contained text provides detailed coverage of the practical aspects of multivariate statistical process control (MVSPC)based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. The authors, leading researchers in this area who have developed major software for this type of charting procedure, provide valuable insight into the T2 statistic. Intentionally including only a minimal amount of theory, they lead readers through the construction and monitoring phases of the T2 control statistic using numerous industrial examples taken primarily from the chemical and power industries. These examples are applied to the construction of historical data sets to serve as a point of reference for the control procedure and are also applied to the monitoring phase, where emphasis is placed on signal location and interpretation in terms of the process variables."