Manufacturing Task Process Characterization Utilizing Response Surface Methodology

2012 ◽  
Vol 3 (2) ◽  
pp. 62-77
Author(s):  
Janet H. Sanders ◽  
Silvanus J. Udoka
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Development ◽  
High Strength ◽  
Business Culture ◽  
Process Characterization ◽  
Novel Approach ◽  
High Strength Fiber ◽  
Rapid Deployment ◽  
Operating Window

To meet today’s business culture of rapid deployment of new products and processes, engineering and manufacturing personnel must utilize efficient means for process development. This paper discusses a novel approach to characterize a task driven manufacturing process. The approach utilized Response Surface Methodology (RSM) to investigate, identify, and prioritize the key process drivers and subsequently develop quantifiable methods for setting the operating levels for the process drivers to determine if the current levels of these key process drivers result in a process response value that is near optimum. The approach identifies the improved response region, generates a mathematical model of the process and specifies an operating window that would yield consistent results for each of the process drivers. A High Strength Fiber Splicing process was used to demonstrate this approach. This study led to the identification of the region that improved the process yield from 65% to 85%.

scholarly journals Exploiting Response Surface Methodology (RSM) as a Novel Approach for the Optimization of Phenolic and Antioxidant Activity of Date Palm Fruit

2020 ◽  
Vol 14 (4) ◽  
pp. 572-582
Author(s):  
Soumaya Hachani ◽  
◽  
Sarah Boukhalkhal ◽  
Ziyad Ben Ahmed ◽  
Mohamed Harrat ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Phenolic Compounds ◽  
Response Surface ◽  
Antioxidant Activities ◽  
Palm Fruit ◽  
Ultrasound Extraction ◽  
Solid Ratio ◽  
Methanolic Extracts ◽  
Novel Approach ◽  
Dpph Scavenging

The Box-Behnken design was used to investigate the effect of three independent variables – time, temperature and solvent-to-solid ratio on the responses of total phenolics, total flavonoids, 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity and cupric ion reducing antioxidant capacity (CUPRAC) of date fruit methanolic extracts. Response surface analysis showed that the optimal ultrasound extraction parameters that maximized the responses were 30 min, 298 K and 74.4 ml/g. Under optimum conditions, UHPLC-DAD-MS/MS was used to tentatively characterize 11 phenolic compounds. The experimental values for the quantification of phenolic compounds and antioxidant activities are in accordance with the predicted values, indicating the suitability of the model and the success of response surface methodology in optimizing the ultrasound extraction conditions.

Multi-Objective Optimization for High Strength Steel Sheet Metal Forming Process Based on Response Surface Methodology

2010 ◽  
Vol 154-155 ◽  
pp. 1223-1227 ◽  
Author(s):  
Zhi Guo An ◽  
Yu Zhang
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
High Strength Steel ◽  
High Strength ◽  
Forming Process ◽  
Multi Objective ◽  
Metal Forming Process

In sheet metal forming process, the input process parameters scatter and considerably result in unreliablity in practical production. Optimization for sheet metal forming process is often considered as a multi-objective problem. An optimizition strategy for high strength steel (HSS) sheet metal forming process was suggested based on response surface methodology (RSM). Latin Hypercube Sampling (LHS) method was introduced to design the rational experimental samples; the objective function was defined based on cracking factor wrinkle factor and severe thinning factor; the accurate response surface for sheet metal forming problem was built by Least Square Method; Multi-objective Genetic Algorithm(MOGA) was adoped in optimization and Pareto solution was selected. The strategy was applied to analyze a HSS auto-part, the result has proved this method suitable for optimization design of HSS sheet metal forming process.

scholarly journals Application of response surface methodology to optimize the COD removal efficiency of an EGSB reactor treating poultry slaughterhouse wastewater

2019 ◽  
Vol 14 (3) ◽  
pp. 507-514 ◽  
Author(s):  
Y. Williams ◽  
M. Basitere ◽  
S. K. O. Ntwampe ◽  
M. Ngongang ◽  
M. Njoya ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Efficiency ◽  
Treatment Process ◽  
High Strength ◽  
Cod Removal ◽  
Organic Loading Rate ◽  
Wastewater Treatment Process ◽  
Slaughterhouse Wastewater ◽  
Cod Removal Efficiency

Abstract The poultry slaughterhouse industry consumes a large volume of potable water for bird processing and equipment cleaning, which culminates in the generation of high strength poultry slaughterhouse wastewater (PSW). The wastewater contains high concentrations of organic matter, suspended solids, nitrogen and nutrients. Most poultry slaughterhouses in South Africa (SA) discharge their wastewater into the municipal sewer system after primary treatment. Due to its high strength, PSW does not meet SA's industrial discharge standards. Discharge of untreated PSW to the environment raises environmental health concerns due to pollution of local rivers and fresh water sources, leading to odour generation and the spread of diseases. Thus, the development of a suitable wastewater treatment process for safe PSW discharge to the environment is a necessity. In this study, a biological PSW treatment process using an Expanded Granular Sludge Bed (EGSB) was evaluated. Response surface methodology coupled with central composite design was used to optimize the performance of the EGSB reactor. The dependant variable used for optimization was chemical oxygen demand (COD) removal as a function of two independent variables, hydraulic retention time (HRT) and organic loading rate (OLR). The interactions between HRT, OLR and COD removal were analysed, and a two factorial (2FI) regression was determined as suitable for COD removal modelling. The optimum COD removal of 93% was achieved at an OLR of 2 g-COD/L/d and HRT of 4.8 days. The model correlation coefficient (R2) of 0.980 indicates that it is a good fit and is suitable for predicting the EGSB's COD removal efficiency.

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