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This paper deals with the effect of the chemical treatment, fibre ratio and fibre reinforcement structure on the flexural properties of kenaf-polyester composites. Composites were made from an unsaturated polyester matrix reinforced with an alkali-treated and virgin kenaf fibres in a loose fibres and nonwovens. Results reveal that alkali treatment improves the flexural properties of composites expect elongation. The same result was obtained when using a nonwoven structure us reinforcement. The best flexural properties were observed for 11.1% fibre weight ratio with the nonwoven structure reinforce composite. The flexural strength and the flexural modulus were 69.5 MPa and 7.11 GPa, respectively, for this composite while it was 42.24 MPa and 3.61, respectively, for polyester samples (no fibre reinforcement). A statistical study was carried out in order to study the effect of the alkali treatment, reinforcement structure and the reinforcement weight ration on the composite properties. This study pro...

The date palm, especially the variety Deglet Nour, produces some dates of high quality. The crop is increasingly attacked by insects while ripening on the palm and damaged by autumnal rains. Various forms of covers have been tried commercially. In this study we considered common materials used worldwide and tested under laboratory conditions. These products require the satisfaction of several properties at the same time. On this basis, the product’s requirements can be identified and converted into a physical element, that is, quality index “QI”, which measures the overall satisfaction of the bagging product. Its value ranges from 0 to l. Hence, “QI” can be used to detect the lack of effectiveness of one of the properties, and thus it should serve as an important measure in quality assurance. It includes the following eight parameters with their ranges: overall migration of toxicological specific substances; solar absorption coefficient; air permeability; resistance to water penetration; breaking load; tear strength; thickness; and weight. The results show that the highest quality index reached is 0.5. It is concluded that the “QI” can evaluate and classify the existing date bunch bags and it can effectively identify the property that should be improved.

This paper studies the effectiveness of lab scale ‘air laid machine’ designed in the Laboratory of Textile Engineering in ISET of Ksar Hellal, Tunisia for production of nonwoven. Three different types of fibers were used: cotton, kenaf, and polyester. The uniformity of the nonwovens made in terms of thickness, weight per unit area (g/m²), air permeability, and mechanical properties were determined through their coefficient of variation. The method used to evaluate the effectiveness is the overload contour plot. This study demonstrated that ‘Airlaid machine’ is compatible with different types of fibers especially at high values of frequency and pressure.

Agave americana L. fibers, the most abundant variety in Tunisia, have a quite important textile potential. This potential is demonstrated by studying the extraction of these fibers from leaves, their physical properties such us fineness or density and their mechanical behavior in tensile tests. In this work, results of a mechanical behavior study of fibers extracted from the Agave americana L. plant are presented. These results deal with the principal and mechanical characteristics of these fibers which are the strain at break, the elasticity modulus and the rupture facture. These results permitted to situate these fibers, compared to the other textile fibers, as materials that can be used in technical applications such as reinforcing composites or geotextile. In order to understand the mechanical properties of these fibers, a correlation study between the properties already cited and the fine structure was done. The obtained results showed that the mechanical properties of Agave americana L. fibers are c...

Mechanical properties of nonwoven alfa fiber based reinforced biocomposite were evaluated to assess the possibility of using it as a new material in engineering applications such as orthopedic application. Samples were fabricated by needle punching, thermal bonding and Hydroentanglement, by blending alfa fibers with wool fibers or Polypropylene fibers. The mechanical properties were tested and showed that the nonwoven NW3 (alfa fiber/PP/PLA, with hydroentanglement) is the best. It has a value of stress at break of 1.94 MPa, a strain of 54.2% and a young’s module of 7.95 MPa, in a production normal direction. A biocomposite has been made with NW3 mixed with PMMA matrix. The use of nonwoven based alfa fiber in reinforcing the composite material increases its rigidity and the tensile strength; the elongation was found to be 1.53%, the Young’s Module of 1.79 GPa and the tensile at break of 15.06 MPa. Results indicated that alfa fibres are of interest for low-cost engineering applications and can compete with glass fibres in orthopedic application.

This article studies the influence of the pulping conditions of Agave americana L. [temperature (100–120°C), pulping time (60–120 mn) and soda concentration (4–8%)] on the pulp yield, kappa index, brightness, viscosity, and the hand sheets breaking length, tear index, and burst index. Responses of pulp and hand sheets properties to the process variables were analyzed using statistical software (Minitab 14). Pulp has been studied using a factorial design to identify the optimum operating conditions, equations relating the dependant variables to the operational variables of the pulping process were established. Results showed that acceptable physical and mechanical properties of pulps and paper could be achieved at 107°C, for 60 mn, and 6% of soda concentration. These are the most suitable conditions for obtaining paper sheets with a high breaking length and tear and burst indexes. Test sheets made from pulped agave leaf fibers were compared to paper made from other vegetable fibers (pine, agave tequilana, ...

Measuring yarn diameter, yarn compressibility and their effect on fabric quality is important to both the fabric designer and the textile technologist. Measurement of yarn diameter is used to predict fabric structural parameters such as width and cover factor. In fact, a slight change in yarn diameter can result in a substantial change in the overall cover factor of fabric. Factors affecting yarn diameter are essentially those that affect yarn density or fibre compactness. Sixty-one different yarns (polyester, viscose, acrylic, cotton and wool) were tested to determine their real diameter by an experimental device. The obtained diameter values are close to those calculated by an established theoretical model. The determination of the real and apparent yarn diameter permits to estimate its packing fraction using his intrinsic parameters.

The influence of temperature, pulping time and soda concentration on the yield, kappa index, brightness and fiber density of Agave Americana L. pulp has been studied. Using a factorial design to identify the optimum operating conditions, equations relating the dependent variables to the operational variables of the pulping process were established. The morphology of the cellulose fibers (length distribution, diameter distribution and crystalline index), obtained from the optimum pulping already determined by the statistical study, was determined by measuring 5020 fibers with optical microscopy equipped with CCD camera and image analysis software, and FT-IR spectra. Cellulose fibers extracted from Agave Americana L. had a lower lignin content value (1.13%) and an absorption capacity of 10.5 g/g. Finally, the characteristics of the optimum Agave pulp were compared to those of other vegetable fibers.

PurposeThis paper aims to provide a rapid and accurate method to predict the amount of sewing thread required to make up a garment.Design/methodology/approachThree modeling methodologies are analyzed in this paper: theoretical model, linear regression model and artificial neural network model. The predictive power of each model is evaluated by comparing the estimated thread consumption with the actual values measured after the unstitching of the garment with regression coefficient R2 and the root mean square error.FindingsBoth the regression analysis and neural network can predict the quantity of yarn required to sew a garment. The obtained results reveal that the neural network gives the best accurate prediction.Research limitations/implicationsThis study is interesting for industrial application, where samples are taken for different fabrics and garments, thus a large body of data is available.Practical implicationsThe paper has practical implications in the clothing and other textile‐making‐up industry. Unused stocks can be reduced and stock rupture avoided.Originality/valueThe results can be used by industry to predict the amount of yarn required to sew a garment, and hence enable a reliable estimation of the garment cost and raw material required.