scholarly journals A Critique on the Foundational Response Surface Methodology for Exploring Optimal Regions

2020 ◽  
pp. 1-16
Author(s):  
John E. Usen ◽  
Essien J. Okoi ◽  
Eric M. Egomo ◽  
Ekeng N. Henshaw ◽  
Edet B. Hogan
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Canonical Transformation ◽  
Industrial Processes ◽  
Trial And Error ◽  
Initial Idea ◽  
Optimum Response ◽  
Optimal Settings

The interest of most process engineers in industries is usually to optimize the yield of their processes. Not until 1951, imprecise methodologies were used in industries for this purpose. However, in 1951, G. E. P. Box and K. B. Wilson invented the technique of Response Surface Methodology (RSM) as one used for the optimization of the yield of processes. Being an initial idea, this paper has considered RSM as a foundational idea. In particular, it criticizes this foundational idea from the angle of its intuitive approach to searching for near-optimal settings of industrial processes, should such processes fail to run at optimal settings. RSM uses the tools of canonical transformation and analysis (a trial-and-error routine) for this search. Regardless, the foundational response surface methodology is acknowledged to be primarily efficient for determining the optimum response.

Production of Activated Carbon from Ligin: Optimization Using Response Surface Methodology

2011 ◽  
Vol 213 ◽  
pp. 427-431 ◽  
Author(s):  
Li Jiang ◽  
Fei Ma ◽  
Ai Jun Gu ◽  
Li Jun Zhang
Keyword(s):  
Response Surface Methodology ◽  
Activated Carbon ◽  
Response Surface ◽  
Chemical Activation ◽  
Technological Parameters ◽  
Activation Temperature ◽  
Surface Areas ◽  
Optimum Response ◽  
Temperature Activation ◽  
Central Composite

Activated carbon（AC）were prepared from lignin by chemical activation with sodium hydroxide（NaOH）. The influence of activation temperature，activation time and impregnation ration on the BET surface areas were investigated. Based on the central composite design (CCD) and response surface methodology(RSM)，the optimized technological parameters were as follows: temperature 751°C， time 57min and impregnation ration 2.06, BET surface areas was up to 1437.20 m2/g.The adequacy of the model equation for predicting the optimum response values was verified effectively by the validation.

Vertical wind speed extrapolation: Modelling using a response surface methodology (RSM) based on unconventional designs

2021 ◽  
pp. 0309524X2110463
Author(s):  
Feriel Adli ◽  
Nawel Cheggaga ◽  
Farouk Hannane ◽  
Leila Ouzeri
Keyword(s):  
Response Surface Methodology ◽  
Wind Speed ◽  
Response Surface ◽  
Vertical Wind ◽  
Industrial Processes ◽  
Wind Speed Profile ◽  
Wind Speeds ◽  
Vertical Wind Speed ◽  
Mathematical Techniques ◽  
Rsm Model

The main objective of this paper is to develop a predictive model of vertical wind speed profile. Response surface methodology (RSM) is used for this purpose. RSM is a set of statistical and mathematical techniques useful for the development, improvement and optimisation of processes. It is mainly used in industrial processes and is successfully applied in this paper to model the wind speed at the hub height of the wind turbine. An unconventional model is adopted due to the nature of the input parameters which cannot be controlled or modified. The model validation indicators, namely correlation coefficient ([Formula: see text]) and root mean square error (RMSE = 1.02), give excellent results when comparing predicted and measured wind speeds. For the same data, the RSM model gives a better RMSE compared to the conventional power law and the artificial neural network.

scholarly journals APLIKASI LEVEL CONTROL PADA SEPARATOR (SLUG CATCHER D-2710) PADA GAS RECEIVING PT. PERTA ARUN GAS

2019 ◽  
Vol 8 (1) ◽  
pp. 83
Author(s):  
Nasrul ZA ◽  
Azhari Azhari ◽  
Rozanna Dewi ◽  
Lukman Hakim ◽  
Muthia Septiana
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Direct Action ◽  
Control Valve ◽  
Process Variable ◽  
Tuning Parameter ◽  
Trial And Error ◽  
Level Control ◽  
Control Dynamic ◽  
Bottom Product

Aplikasi kontrol PID pada tangki pemisah (separator) diteliti dengan berbagai variasi parameter seperti Kc, Ti dan Td. Kontrol level dijadikan sebagai respon dengan beberapa variasi gangguan. Sistem pengendalian level liquid pada separator dengan tuning parameter kontroler PID dengan kondisi operasi pada PT. Perta Arun Gas dengan tujuan mendapatkan bottom product yang sesuai spesifikasi dengan melakukan trial and error juga mendapatkan nilai Kc dan Ti terbaik. Control valve memiliki 2 action yaitu direct action dan reverse action. Pengontrol PID merupakan penggabungan dari pengontrol proportional integral derivative (PID) yang bertujuan untuk mempercepat reaksi sebuah sistem, menghilangkan offset. Tuning range Kc, Ti yang digunakan adalah Kc= 2-20 dan Ti 5-10 menit yang selanjutnya akan di run menggunakan response surface methodology dengan meninjau waktu PV (process variable) mendekati SP (setpoint) dan opening valve. Metode respon surface methodology digunakan untuk melihat pengaruh variabel terhadap suatu variabel respon dan untuk mengoptimalkan variabel respon tersebut. Optimasi waktu tercepat saat mengatasi gangguan dengan variasi level adalah tuning parameter Kc=17,18 dan Ti=5,6 dengan waktu 0,3 menit dan bukaan OP 26,9%. Waktu terlama saat mengatasi gangguan adalah pada Kc=4,64, Ti=9,27 menit, time=0,61 menit dengan OP=10,6%.Kata Kunci: Control dynamic, Kontrol PID, Response Surface Methodology

scholarly journals Uses of the Response Surface Methodology for the Optimization of Agro-Industrial Processes

2021 ◽  
Author(s):  
José Manuel Pais-Chanfrau ◽  
Jimmy Núñez-Pérez ◽  
Rosario del Carmen Espin-Valladares ◽  
Marco Vinicio Lara-Fiallos ◽  
Luis Enrique Trujillo-Toledo
Keyword(s):  
Response Surface Methodology ◽  
Design Of Experiments ◽  
Response Surface ◽  
Industrial Processes ◽  
General Overview

Response surface methodology is a tool for the design of experiments, widely used today to optimize industrial processes, including agro-industrial ones. Since its appearance in the last century’s fifties, hundreds of articles, chapters of books, and books attest to this. In this work, a general overview of this tool’s general practical aspects is made. This statistical tool’s usefulness and popularity, used in the optimization of agro-industrial processes and in making them more efficient and sustainable, is described through multiple examples.

Sign in / Sign up

Export Citation Format

Share Document