Variability in physical properties of plantation-grown progenies of Melia composita and determination of a kiln-drying schedule

Kumar, Shailendra; Kelkar, Bhushan U.; Mishra, Ajit; Jena, S. K.

doi:10.1007/s11676-017-0527-z

Cited by 9 publications

(7 citation statements)

References 3 publications

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“…A rating factor of zero (Table 7) indicates that M. dubia is not at all suitable for the boring operation. This can be attributed to the relatively low density of this species as reported by Kumar et al (2018). The common defects that were noticed during mortising were raised, torn, chipped and fuzzy grains.…”

Section: Resultsmentioning

confidence: 66%

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Machining properties of Melia dubia wood

Gupta

Singh

Kishan-Kumar

et al. 2019

Maderas, Cienc. tecnol.

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In this paper result of working quality of Melia dubia is reported after testing them under six major wood working operations namely-planing, sanding, turning, shaping, boring and mortising based on Indian Standard. The wood performed extremely well under planing. In shaping, the performance was good enough. Though all the other operations yielded poor results, the composite rating factor which is an overall performance indicator was 35 % more than that of Tectona grandis. The ease of working is only 93 % compared to teak. The working quality index which was based on the composite rating factor and ease of working worked out to 107 taking Tectona grandis as 100 mainly because of the high performance under planing and shaping and good performance under sanding.

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Section: Resultsmentioning

confidence: 66%

“…The planks were sawn out from the main stem of the tree. The mean density of the wood thus obtained was 0,39 kg/m 3 (Kumar et al 2018). From these planks, samples of sizes mentioned in Table 1 were prepared for various tests and wood working tests were carried out as per methods given in IS-8292 (BIS IS-8292 1992).…”

Section: Methodsmentioning

confidence: 99%

Machining properties of Melia dubia wood

Gupta

Singh

Kishan-Kumar

et al. 2019

Maderas, Cienc. tecnol.

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“…The density of the Malabar neem (Melia dubia Cav.) wood ranges between 390 kg/m 3 to 460 kg/m 3 (Kumar et al 2018, Sharma et al 2019. The higher density of hybrid composite is attributed to the high density of WPC sheet (≈ 1010 kg/m 3 ) instead of a thin layer of formaldehyde-based resins.…”

Section: Physical Testmentioning

confidence: 99%

Wood polymer composite bonded veneer based hybrid composites

Arya,

Chauhan,

Kumar

et al. 2023

Maderas, Cienc. tecnol.

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Wood veneer based composites have a great demand in present market as the material can utilize small diameter plantation timbers grown at short rotation cycle. This paper presents preparation and characterization of hybrid composites made of wood veneer and wood polymer composite. The study explored utilization of wood polymer composite as an adhesive for bonding veneers replacing formaldehyde-based adhesives. Wood polymer composite containing 40 % bamboo particles embedded in the matrix of polypropylene was used in sheet form to bind the veneers of Melia dubia (Malabar neem) wood. The composites were prepared in both laminated veneer lumber and plywood configurations. The assessment of physical and mechanical properties indicated that the properties of wood polymer composite contribute significantly to the properties of the hybrid composites. The density of the resultant composites was significantly higher (690 kg/m 3 -750 kg/m 3 ) than conventional plywood or laminated veneer lumber. Among mechanical properties, there was no statistical difference in tensile and flexural strength of plywood and laminated veneer lumber configuration. Modulus of elasticity and compressive strength of laminated veneer lumber configuration were significantly higher than plywood. Glue shear strength and internal bond strength of the composites indicated acceptable bonding properties of wood polymer composite which suggests the potential application of these composites as a binding agent for wood veneers. These composites could be a special class of laminated composites with no formaldehyde emission hazards.

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“…Studies examining the collapse and recovery during the drying process [ 26 , 27 ], cracking occurrence during the drying process [ 28 ], and numerical simulations of coupled moisture and heat transfer in wood during kiln drying [ 29 ] were also reported in the literature. Kiln-drying scheduling is also covered in some studies [ 30 , 31 ] as an important factor impacting the final moisture content and drying defects [ 32 ]. In addition, previous studies focused on characterizing and modeling final moisture and its spread in air-dried [ 33 ], radio-frequency kiln-dried [ 34 , 35 , 36 ], heat treated [ 37 ], and heat-and-vent kiln-dried batches [ 38 , 39 , 40 ].…”

Section: Introductionmentioning

confidence: 99%

The Role of Drying Schedule and Conditioning in Moisture Uniformity in Wood: A Machine Learning Approach

et al. 2023

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Monitoring the moisture content (MC) of wood and avoiding large MC variation is a crucial task as a large moisture spread after drying significantly devalues the product, especially in species with high green MC spread. Therefore, this research aims to optimize kiln-drying and provides a predictive approach to estimate and classify target timber moisture, using a gradient-boosting machine learning model. Inputs include three wood attributes (initial moisture, initial weight, and basic density) and three drying parameters (schedule, conditioning, and post-storage). Results show that initial weight has the highest correlation with the final moisture and possesses the highest relative importance in both predictive and classifier models. This model demonstrated a drop in training accuracy after removing schedule, conditioning, and post-storage from inputs, emphasizing that the drying parameters are significant in the robustness of the model. However, the regression-based model failed to satisfactorily predict the moisture after kiln-drying. In contrast, the classifying model is capable of classifying dried wood into acceptable, over-, and under-dried groups, which could apply to timber pre- and post-sorting. Overall, the gradient-boosting model successfully classified the moisture in kiln-dried western hemlock timber.

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Variability in physical properties of plantation-grown progenies of Melia composita and determination of a kiln-drying schedule

Cited by 9 publications

References 3 publications

Machining properties of Melia dubia wood

Machining properties of Melia dubia wood

Wood polymer composite bonded veneer based hybrid composites

The Role of Drying Schedule and Conditioning in Moisture Uniformity in Wood: A Machine Learning Approach

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