The issue on variability of mechanical properties within wood has found to be increasingly prominent in recent years. On the other hand, it is known that uniformity of wood properties is essential in quality control in the timber manufacturing such as manufacturing of Glued Laminated (Glulam) timber. The AS/NZS 1328 P2 specified that the overall mechanical properties of Glulam timber can be estimated based on the MOE of the finger jointed laminates and the arrangement of the corresponding laminates. In relating to the above standard, optimisation in the arrangement of shooks’ location along the finger jointed laminate will enable determination of the overall MOE of laminates, as well as optimise the utilisation of feedstocks. In this study, a deterministic model was developed in relating the local shook’s modulus of elasticity (MOE) with the overall MOE of the corresponding finger jointed timber based on the principle of the Moment of Curvature. The projected overall MOE is calculated as a function of lengths and MOEs of individual shooks in the finger joint timber. The effect of shooks’ location can also be determined from the model. Numerical derivation of the model was addressed and the analyses of the relationships between the local shook MOEs, the overall MOE, and bending strength (MOR) were assessed. Experimental results showed that the model can effectively predicts the overall MOE, particularly on shook combinations with random and large standard deviations in shook MOEs. The errors of the predictive model were ranged from -8.17% to +0.81%. Results from the assessment on the relationships between the overall MOE and bending MOR indicated that wood failure in the combinations of small standard deviations shook MOEs was most likely to occur at the weakest point, however, wood failures may not necessarily occur in the shook with the lowest MOE in the asymmetrical MOE arrangements. This also applies to the finger jointed timber with combinations of shooks with large standard deviations for local MOEs. In addition, the relationship between dynamic MOE of shooks and the static bending overall MOE were assessed. A linear regression has been suggested for the adjusted shooks dynamic MOE at 36 mm thickness. The predictability of the model could further improve when the shook MOEs were sorted according to sawing pattern and the proposed model for quarter sawn is suggested. Lastly, economic analysis was performed based on the models available in literature and the developed model in this study. Models reported in the literature including the arithmetic mean model and model based on the shook’s minimum MOE. The results from economic analysis showed that the study’s model was most cost effective in predicting the cost of shooks based on the predicted overall finger jointed MOE using the model as compare to the arithmetic mean and the minimum shook MOE method. In conclusion, the proposed model has demonstrated to be unique, simple, effective and robust in predictive applications.

The issue on variability of mechanical properties within wood has found to be increasingly prominent in recent years. On the other hand, it is known that uniformity of wood properties is essential in quality control in the timber manufacturing such as manufacturing of Glued Laminated (Glulam) timber. The AS/NZS 1328 P2 specified that the overall mechanical properties of Glulam timber can be estimated based on the MOE of the finger jointed laminates and the arrangement of the corresponding laminates. In relating to the above standard, optimisation in the arrangement of shooks’ location along the finger jointed laminate will enable determination of the overall MOE of laminates, as well as optimise the utilisation of feedstocks. In this study, a deterministic model was developed in relating the local shook’s modulus of elasticity (MOE) with the overall MOE of the corresponding finger jointed timber based on the principle of the Moment of Curvature. The projected overall MOE is calculated as a function of lengths and MOEs of individual shooks in the finger joint timber. The effect of shooks’ location can also be determined from the model. Numerical derivation of the model was addressed and the analyses of the relationships between the local shook MOEs, the overall MOE, and bending strength (MOR) were assessed. Experimental results showed that the model can effectively predicts the overall MOE, particularly on shook combinations with random and large standard deviations in shook MOEs. The errors of the predictive model were ranged from -8.17% to +0.81%. Results from the assessment on the relationships between the overall MOE and bending MOR indicated that wood failure in the combinations of small standard deviations shook MOEs was most likely to occur at the weakest point, however, wood failures may not necessarily occur in the shook with the lowest MOE in the asymmetrical MOE arrangements. This also applies to the finger jointed timber with combinations of shooks with large standard deviations for local MOEs. In addition, the relationship between dynamic MOE of shooks and the static bending overall MOE were assessed. A linear regression has been suggested for the adjusted shooks dynamic MOE at 36 mm thickness. The predictability of the model could further improve when the shook MOEs were sorted according to sawing pattern and the proposed model for quarter sawn is suggested. Lastly, economic analysis was performed based on the models available in literature and the developed model in this study. Models reported in the literature including the arithmetic mean model and model based on the shook’s minimum MOE. The results from economic analysis showed that the study’s model was most cost effective in predicting the cost of shooks based on the predicted overall finger jointed MOE using the model as compare to the arithmetic mean and the minimum shook MOE method. In conclusion, the proposed model has demonstrated to be unique, simple, effective and robust in predictive applications.