Strength characteristics of furniture elements with particleboard cutting waste core

Krasimira Atanasova, Dimitar Angelski, Dobriyan Dobriyanov, Tsacho Tsachev

Abstract


The circular economy principles for environmentally friendly and waste-free production can be effectively applied to furniture production by utilizing cutting particleboard waste. The aim of the presented study is to establish the influence of the laminating sheet characteristics on the bending strength and modulus of elasticity of three-layer elements with a core formed from laminated particleboard cutting waste. For lamination, medium density fibreboard (MDF) with a thickness of 2.7 and 4 mm, one-sided veneered MDF with a total thickness of 3.2 mm, and three-layer poplar plywood with a thickness of 3 and 4 mm were used. The lamination was carried out with polyvinyl acetate adhesive at a temperature of 50°C and a specific pressure of 0.075 MPa. The obtained dependencies are presented in tabular and graphical form.

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Damage identification in CFRP/plywood laminate drilling based on digital image processing

Joanna Zielińska-Szwajka, Krzysztof Szwajka

Abstract


Hybrid structures made of carbon fiber-reinforced plastics (CFRP) find many applications due to their favorable properties (high strength with low weight). In contrast to hybrid metal- based CFRP laminates, there is a lack of research on hybrid laminates consisting of CFRP and plywood. Spallings and delamination of holes are the main disadvantages when drilling CFRP and wood-based composites. The CFRP/plywood hybrid laminates are widely used in areas that benefit from the obtained properties of these materials, that is, high strength and low density, in particular as a structural material for the production of finishing components of lightweight structures. In this study, a vision-based method for recognizing and evaluating burrs and delamination generated during drilling was developed based on threshold segmentation methods and using fuzzy Takagi-Sugeno-Kang (TSK) subtractive clustering. Digital images and selected time-domain measures of cutting torque and thrust force and they were adopted as input parameters in the TSK model. The proposed method was verified by full drilling experiments on CFRP/wood-based composite samples and the results were compared based on images of the holes obtained with a stroboscopic microscope. A good agreement was found between the results of manual measurement method and developed TSK-based model.

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Optimization of the neural network structure for tool wear estimation in the drilling process of CFRP/plywood laminates

Krzysztof Szwajka, Joanna Zielińska-Szwajka

Abstract


Tool condition diagnostics system is still a missing element of advanced machining equipment. Tool condition monitoring is an important problem in furniture production and similar industries. An effective system of this type would increase machining efficiency, while increasing accuracy and reliability. It would also allow for full, flexible automation of production. This paper presents a method for estimating blade wear based on multiple measures of diagnostic signals. A typical solution to the problem of approximating blade wear based on multiple measures is the use of a neural network. The most popular network is a multilayer perceptron. The process of optimizing the structure and parameters of the network is presented

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