Mechanical Properties of Rubber Mat Compound via Two Factors Modelling Using Response Surface Methodology

2015 ◽  
Vol 761 ◽  
pp. 358-363 ◽  
Author(s):  
Qumrul Ahsan ◽  
Noraiham Mohamad ◽  
Soh Tiak Chuan

Mechanical properties of an industrial based rubber mat compound were optimized via response surface methodology (RSM). Interaction between two factors: accelerators (0.04-3.50 phr) and fillers (0-18.29 phr) were investigated using a full factorial design. The accelerators consisted of a combination of mercaptobenzothiazole disulphide (MBTS) as the primary accelerator, and diphenyl guanidine (DPG) and Zn-2-mercaptobenzo thiazole (ZMBT) as the secondary accelerators. Meanwhile, silane functionalized hybrid precipitated silica/calcined clay (f-PSi/ClCy) was used as the fillers. Regression models for optimum mechanical properties against the accelerator and filler factors were generated by Design Expert software. It was recommended that the level of accelerators and fillers at 1.77 phr and 0.65 phr as the optimum parameter to achieve tensile strength of ~14 MPa and ~2 N/mm, respectively. Further, a comparison between the recommended formulation and the original rubber mat formulation affirmed that the mechanical properties via statistical design were in good agreement with the experimental results with deviations of only + 8.8 % and 0 % for tensile strength and tear strength respectively.

2017 ◽  
Vol 24 (08) ◽  
pp. 1750114 ◽  
Author(s):  
SOHAIL YASIN ◽  
MASSIMO CURTI ◽  
NEMESHWAREE BEHARY ◽  
ANNE PERWUELZ ◽  
STEPHANE GIRAUD ◽  
...  

The [Formula: see text]-methylol dimethyl phosphono propionamide (MDPA) flame retardant compounds are predominantly used for cotton fabric treatments with trimethylol melamine (TMM) to obtain better crosslinking and enhanced flame retardant properties. Nevertheless, such treatments are associated with a toxic issue of cancer-causing formaldehyde release. An eco-friendly finishing was used to get formaldehyde-free fixation of flame retardant to the cotton fabric. Citric acid as a crosslinking agent along with the sodium hypophosphite as a catalyst in the treatment was utilized. The process parameters of the treatment were enhanced for optimized flame retardant properties, in addition, low mechanical loss to the fabric by response surface methodology using Box–Behnken statistical design experiment methodology was achieved. The effects of concentrations on the fabric’s properties (flame retardancy and mechanical properties) were evaluated. The regression equations for the prediction of concentrations and mechanical properties of the fabric were also obtained for the eco-friendly treatment. The R-squared values of all the responses were above 0.95 for the reagents used, indicating the degree of relationship between the predicted values by the Box–Behnken design and the actual experimental results. It was also found that the concentration parameters (crosslinking reagents and catalysts) in the treatment formulation have a prime role in the overall performance of flame retardant cotton fabrics.


2015 ◽  
Vol 1134 ◽  
pp. 56-60 ◽  
Author(s):  
Siti Aisyah Jarkasi ◽  
Dzaraini Kamarun ◽  
Azemi Samsuri ◽  
Amir Hashim Md Yatim

Fillers play important roles in enhancing mechanical properties of NR latex films. The effect of filler dispersion and amount of dispersing agent to the tensile strength and tearing energy of NR latex films were investigated in this study. The studies were carried out by (i) varying the amount of dispersing agent (Anchoid) added which is an anionic surfactant; and (ii) varying the speed of stirring during mixing of latex with compounding ingredients. It was observed that tensile strength and tearing energy were affected by both factors listed. In the case of NR latex film filled with 10 pphr of carbon black (Super Abrasion Furnace, SAF), the optimum stirring speed was 400 rpm and the optimum amount of surfactant was in the range of 5 to 10 % by weight. High tensile strength ranging from 29 - 31 MPa and high tearing energies ranging from 90.6 - 111.0 kJ/m2were achieved from optimization of these two factors; rendering their importance.


2021 ◽  
pp. 009524432110153
Author(s):  
Jaber Mirzaei ◽  
Abdolhossein Fereidoon ◽  
Ahmad Ghasemi-Ghalebahman

In this study, the mechanical properties of polypropylene (PP)-based nanocomposites reinforced with graphene nanosheets, kenaf fiber, and polypropylene-grafted maleic anhydride (PP-g-MA) were investigated. Response surface methodology (RSM) based on Box–Behnken design (BBD) was used as the experimental design. The blends fabricated in three levels of parameters include 0, 0.75, and 1.5 wt% graphene nanosheets, 0, 7.5, and 15 wt% kenaf fiber, and 0, 3, and 6 wt% PP-g-MA, prepared by an internal mixer and a hot press machine. The fiber length was 5 mm and was being constant for all samples. Tensile, flexural, and impact tests were conducted to determine the blend properties. The purpose of this research is to achieve the highest mechanical properties of the considered nanocomposite blend. The addition of graphene nanosheets to 1 wt% increased the tensile, flexural, and impact strengths by 16%, 24%, and 19%, respectively, and an addition up to 1.5 wt% reduced them. With further addition of graphene nanosheets until 1.5 wt%, the elastic modulus was increased by 70%. Adding the kenaf fiber up to 15 wt% increased the elastic modulus, tensile, flexural, and impact strength by 24%, 84%, 18%, and 11%, respectively. The addition of PP-g-MA has increased the adhesion, dispersion and compatibility of graphene nanosheets and kenaf fibers with matrix. With 6 wt% PP-g-MA, the tensile strength and elastic modulus were increased by 18% and 75%, respectively. The addition of PP-g-MA to 5 wt% increased the flexural and impact strengths by 10% and 5%, respectively. From the entire experimental data, the optimum values for elastic modulus, as well as, tensile, flexural, and impact strengths in the blends were obtained to be 4 GPa, 33.7896 MPa, 57.6306 MPa, and 100.1421 J/m, respectively. Finally, samples were studied by FE-SEM to check the dispersion of graphene nanosheets, PP-g-MA and kenaf fibers in the polymeric matrix.


2021 ◽  
pp. 095745652110307
Author(s):  
Hara P Mishra ◽  
Arun Jalan

This article presents the experimental and statistical methodology for localized fault analysis in the rotor-bearing system. These defects on outer race, on inner race, and on a combination of ball and outer race are considered. In this study speed, load and defects were considered as the essential process variables to understand their significance and effects on vibration response for the rotor-bearing system. Three factors at three levels were considered for experimentation, and the experiment was designed for L27 based on design of experiments (DOE) methodology. From the experiments, the vibration response results are recorded in terms of root mean square value for the analysis. Response surface methodology (RSM) is used for identifying the interaction effect of varying process parameters upon the response of vibrations by response surface plot. The rotor-bearing test setup is used for experimentation and is analyzed by using DOE. This study establishes the prediction of fault in the rotor-bearing system in combined parametric effect analysis and its influence with DOE and RSM.


2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.


2016 ◽  
Vol 53 ◽  
pp. 283-292 ◽  
Author(s):  
Faramarz Ashenai Ghasemi ◽  
Ismail Ghasemi ◽  
Saman Menbari ◽  
Mohsen Ayaz ◽  
Alireza Ashori

2019 ◽  
Vol 6 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Abdul Aziz Hamidi ◽  
Syed Zainal Sharifah Farah Fariza ◽  
Alazaiza Motasem Y.D

Landfill leachate is highly polluted and generated as a result of water infiltration through solid waste produced domestically and industrially. This study investigated the applicability of the response surface methodology (RSM) to optimize the removal performances of chemical oxygen demand (COD), color, and suspended solids (SS) from landfill leachate by coagulation process using Tin tetrachloride pentahydrate. The leachate samples were collected from Alor Pongsu Landfill (APLS) in Perak, Malaysia. Before starting the experiments, general characterization was carried out for raw leachate samples to investigate their physical and chemical properties. The effects of the dosage and pH of SnCl4 on the removal performances were evaluated as well. An ideal experimental design was performed based on the central composite design (CCD) by RSM. In addition, this RSM was used to evaluate the effects of process variables and their interaction toward the attainment of their optimum conditions. The statistical design of the experiments and data analysis was resolved using the Design-Expert software. Further, the range of coagulant dosage and pH was selected based on a batch study which was conducted at 13000 mg/L to 17000 mg/L of SnCl4 and pH ranged from 6 to 10. The results showed that the optimum pH and dosage of SnCl4 were 7.17 and 15 g/L, respectively, where the maximum removal efficiency was 67.7% for COD and 100% for color and SS. The results were in agreement with the experimental data with a maximum removal efficiency of 67.84 %, 98.6 %, and 99.3%, for COD, color, and SS, respectively. Overall, this study verified that the RSM method was viable for optimizing the operational condition of the coagulation-flocculation process.


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