Optimization of sawing in wood transformation primary industries

Abstract

Purpose: The loss of raw materials in wood cutting industries has reached high proportions (30 to 36% of volume yield, Ngolle Ngolle, 2009). The purpose of this paper is to solve the problem of optimising the production on the basis of the commercial value of the cuts.

Design/methodology/approach: In order to tackle this problem, we started with the generalities on the exploitation and the primary conversion of wood in Cameroon. After that, we studied the various methods of cutting and the different products obtained. We then proceeded with the formulation of the log cutting optimisation problem based on a real shape model of the logs, objective of research works presented in (Danwé, Bindzi, Meva’a & Nola, 2011). We finally completed our work with the design and the presentation of a software package called cutting optimiser.

Findings: We start by having some knowledge on the geometry of the logs, cutting strategies and classification of cuts. This classification enables us to determine the quality and quantity of the production, and to estimate the commercial value of the log. The solution to this problem then led to the design of a software package.

Research limitations/implications: In this paper, the optimisation problem concerns problems where the objective function is non-explicit, the variables discreet, and the constraints non-explicit.

Practical implications: The solution to this problem then led to the design of a software package to be used as a cutting optimiser. The automation of the cutting operation leads to an accelerated work and an increase in the volume of the cuts produced daily.

Originality/value: This research is among the few to solve discrete optimization problems with constraints. Some constraints concerning the mechanical characteristics of the logs are taken into account. The constraints can equally be non-explicit. Moreover the market standards impose technological constraints which render the problem of optimisation even more complex.