Effects examination of the factors affecting choice of type of furniture with data mining technique (decision tree)

Data mining is the process of analyzing data from different perspectives and summarizing it into beneficial information. Data mining is a very important technique in determining customer behavior. However, the work done on this subject is limited. By analyzing customer behavior, consumer needs can be identified and satisfaction can be increased at the same time. In this study, factors (age, gender, marital status, child status) affecting the selection of the furniture type (classical and modern furniture) will be analyzed using decision tree which is one of the techniques of data mining. Our analysis is intended to guide future research and to assist in the accumulation of knowledge on the implementation of data mining techniques

The quality comparison of particleboards produced from heartwood and sapwood of european larch

In this paper, the impacts of heartwood and sapwood usage on the physical, mechanical, and surface properties and formaldehyde emission of particleboard are investigated. European Larch (Larix decidua) trees are chosen as a raw material. The logs are divided into three segments: sapwood, heartwood and total wood. The highest amounts of cellulose (51.54%), and hemicelluloses (22.24%) in the sapwood, followed by total wood, and the heartwood, respectively. However, the highest amount of lignin (30.54%) was found in the heartwood. The highest extractives values are obtained from heartwood, followed by total wood, and the sapwood, respectively. While the lowest pH value (3.03) is found in heartwood, the sapwood samples provide the highest values (4.95). The highest ash (0.49%) content and amount of condensed tannin (13.89%) are extracted from heartwood, followed by total wood, and sapwood, respectively. The test panels manufactured from sapwood have the smoothest surface (7.49 µm (Ra), 48.86 µm (Ry), and 35.12 µm (Rz)) and the lowest contact angles (67.8ᵒ), while the roughest surface (14.20 µm (Ra), 68.05 µm (Ry), and 50.02 µm (Rz)) and highest contact angle (96.9ᵒ) are obtained from the panels of heartwood. The thickness swelling (19.88%) and formaldehyde emission (7.28%) values of the panels manufactured from heartwood are significantly lower than the panels manufactured from the total wood and sapwood. The highest modulus of rupture (MOR), modulus of elasticity (MOE), and internal bond (IB) values are observed on sapwood, respectively, 15.60 MPa (MOR), 2201 MPa (MOE), and 0.523 MPa (IB). These mechanical strength values (MOR, MOE, and IB) are followed by total wood, and the heartwood, respectively. Surface smoothness and wettability of the particleboards manufactured from sapwood are better than those of total wood and heartwood

Possibilities of Using Sunflower Tray in Particleboard Industry

Bu çalışmada, ayçiçek üretimi sonrası tarlada atık kalan ayçiçek tablasının hammadde olarak yonga levha üretimine uygunluğu araştırılmıştır. Çalışmada belirli oranlarda kokar ağaç (Ailanthus altissima (Mill.) Swingle) odunu ve ayçiçek tablası içeren 5 farklı levha üretilmiştir. Aynı zamanda kullanılan hammaddelerin kimyasal özellikleri ve yonga levhaların çeşitli kalite özelliklerine de (fiziksel, mekanik, yüzey özellikleri ve formaldehit emisyonu) bakılmıştır. Son olarak da elde edilen veriler değerlendirilerek yonga levhaların çeşitli kullanım yerlerinde özellikle de mobilya ve genel kullanım için uygunluğu ilgili standartlara bakılarak değerlendirilmiştir. Kimyasal analizlerden elde edilen verilen verilerin değerlendirilmesi sonucunda tüm çözünürlük değerleri, pH ve kül değerlerinin ayçiçek tablasında kokar ağaca odununa göre daha yüksek olduğu belirlenmiştir. Fakat holoselüloz, selüloz, hemizelüloz ve lignin miktarlarının ise kokar ağaç odununda ayçiçek tablasına göre daha yüksek olduğu tespit edilmiştir. Yapılan çalışmalardan elde edilen verilerin istatistiksel olarak değerlendirilmesi sonucu yonga levhaların üretiminde % 10 ayçiçek kafası kullanılması yonga levhaların teknolojik özelliklerini etkilememiştir. % 20, % 30 ve % 100 ayçiçek tablası kullanımı eğilme direnci, elastikiyet modülü ve yüzeye dik çekme direncini olumsuz yönde etkilemiştir. Buna rağmen 2 ve 24 saatlik kalınlığına şişme değerleri ve formaldehit emisyonunu ise olumlu yönde etkilemiştir. Son olarak ise levhaların yüzey özelliklerine (ortalama pürüzlülük, en büyük pürüzlülük ve on nokta pürüzlülüğü) bakıldığında ayçiçek tablası kullanım oranın artmasına paralel olarak pürüzlülük değerlerinin arttığı tespit edilmiştir.In this study, the appropriateness of the remaining sunflower tray in the field after the sunflower production as raw material to the particleboard production was investigated. In the study, 5 different particleboards were produced, which included certain amounts of wood of tree of heaven (Ailanthus altissima (Mill.) Swingle) and sunflower table. At the same time, the chemical properties of the raw materials used and the various quality characteristics of the chips (physical, mechanical, surface properties and formaldehyde emission) were examined. Finally, the obtained data were evaluated and evaluated for the suitability of the chipboards in various places of use, in particular for furniture and general use, according to relevant standards. As a result of the evaluation of the data obtained from chemical analysis, it has been determined that all the solubility values, pH and ash values are higher in the sunflower tray than the wood of tree of heaven. However, the amount of holocellulose, cellulose, hemisellulose and lignin were found to be higher in the wood of tree heaven compared to the sunflower tray. The statistical evaluation of the data obtained as a result of the studies done does not affect the technological characteristics of the chips by using 10% sunflower head in the production of the particleboards. Using 20%, 30% and 100% sunflower tray affected the bending strength, modulus of elasticity, and internal bond strenght to the surface in the negative direction. Despite this, it affected positively the thickness swelling values for 2 and 24 hour immersion and formaldehyde emission..Finally, when looking at the surface properties of the boards (average roughness, maximum roughness and ten point roughness), it was determined that the roughness values increased in parallel with the increase of sunflower tray utilization rate

Moisture content prediction of wood drying process using fuzzy logic

The abstract of the studies was published electronically in the Proceeding Book of the International Forestry Symposium organized between December 7–10, 2016 in Kastamonu, TurkeyThe fuzzy logic method might be used with various applications, for example, timber production, air conditioners, washing machines, and molecular biology. Fuzzy logic systems are trusted. At the same time easy to use and flexible. Temperatures and relative humidity vary depending on the room where the wood is used. Moisture in wood-based products is one of the key points. Because it directly affects the usage area and production. In the present study, the effects of temperature and drying time on moisture content were modeled and predicted in the wood drying process. For this purpose, the wood test materials were prepared, and their moisture contents were measured. The fuzzy logic model was established by taking references of the observed values. With this fuzzy logic model, the moisture contents of the wood were predicted in relation to drying temperature and time. Then, experimental results were compared with modeling data. 97.16% accuracy was observed with the fuzzy logic model

Türkiye'de Twitter verilerinden faydalanarak ahşap malzeme üzerine eğilimlerin belirlenmesi

Dünyadaki veri miktarı büyük bir hızla artmaktadır. Günümüzde veriler bilim insanları tarafından en değerli hammadde olarak düşünülmektedir. Veri madenciliği çalışmaları gelişmiş ülkeler için kritik bir konudur. Bu nedenle her alanda veri çalışmalarına büyük yatırımlar yapılmaktadır. Twitter ülkemizde oldukça popular ve büyük miktarda verinin saklandığı bir sosyal medya ağıdır. Bu ağ kullanıcılarının belli başlıkları ne sıklıkta bahsettikleri farklı konulara olan ilgisini göstermektedir. Twitter verilerinin analizi ile toplumların fikir değişimleri belirlenebilmektedir. Aynı zamanda firmalar sosyal medyaya markalaşmak için giderek ilgi göstermektedir. Veriler tüketicilerin beklentilerini ve şikayetlerini anlamak için değerli bir kaynaktır. Anketler ile veri toplamak ve gerçek düşüncelere ulaşmak genellikle zordur. Bu durumda sosyal medya ağlarındaki kullanıcı verileri iyi bir alternatiftir. Bu çalışmada içinde ahşap kelimesi geçen tweetlerin coğrafi bölgelere göre dağılımı belirlenmiştir. Bu amaç doğrultusunda düzenli olarak tweetlerin paylaşıldığı koordinat verileri toplanmıştır. Çalışmada dünyada yaygın olarak kullanılan Rapidminer yazılımından faydalanılmıştır. Rapidminer güçlü bir veri madenciliği ve analiz platformudur. Çalışma sonucunda, twitter kullanıcılarının hangi coğrafik bölgelerde daha yoğun ahşap malzemeye ilgi duyulduğu belirlenmiştir

The determination of mechanical performance and digital image analysis of furniture joints constructed with polyvinyl acetate (pvac) adhesive reinforced with nanoparticle

Tez, 20.06.2019 tarihine kadar yazarı tarafından kısıtlanmıştırBu çalışmada; çeşitli nano partiküller (SiO2, TiO2) belirli oranlarda (%1, %2, %4) Polivinil Asetat (PVAc) tutkalına karıştırılmıştır. Hazırlanan nanopartikül takviyeli tutkalların yapışma performansları üzerine, nanopartikül tipinin ve oranın etkileri araştırılmıştır. Transmisyon Elektron Mikroskobu (TEM) kullanarak çeşitli partiküllerin farklı oranlarda fotoğrafları çekilmiş ve mikro yapıda dağılımı gözlenmiştir. Aynı zaman X-Işını Kırınım Analizleri (XRD) gerçekleştirilmiştir. Daha sonra Doğu kayını (Fagus orientalis L.), Saplı Meşe (Quercus robur) ve Lamine ağaç malzeme ile çeşitli nanopartikül takviyeli tutkal kullanılarak oluşturulan mobilya birleştirmelerinin mekanik özellikleri değerlendirilmiş ve görüntü yöntemlerinden yararlanarak deformasyon özellikleri belirlenmiştir. Nanopartikül takviyeli tutkalların performans sonuçlarına göre, düşük oranlarda (%1, %2) nanopartiküllerin PVAc tutkalına eklenmesi ile yapışma performansında artış görülmüştür. Bununla birlikte TEM ve XRD sonuçları incelendiğinde, düşük oranlarda nanopartiküllerin daha iyi dağıldığı gözlenmiştir. Nanopartikül tipinin, nanopartikül oranın ve malzeme türünün mobilya birleştirmelerin eğilme direnci, çekme direnci ve yorulma dayanımı üzerine etkilerini belirlemek için yapılan test sonuçlarına göre, düşük oranlarda SiO2 ve TiO2 nanopartiküllerin ilavesi ile kayın ve meşe odunu kullanılarak oluşturulan birleştirmelerde en yüksek değerler görülmüştür. Deformasyon sonuçları değerlendirildiğinde ise görüntü analizi yönteminden faydalanılarak yapılan ölçümlerin, klasik yöntemler ile hesaplanan değerlere yakın olduğu belirlenmiştir. Sonuç olarak, nanopartiküller PVAc tutkalının geliştirilmesinde ve mobilya birleştirmelerinin güçlendirilmesinde etkin bir madde olarak kullanılabilir.In this study, various nanoparticles (SiO2, TiO2) were mixed in a specific ratio (1%, 2%, 4%) to polyvinyl acetate adhesive. The effects of the nanoparticle type and rate on nanoparticles reinforced adhesives of bonding performance were investigated. Determination of particle dispersion and adhesive structure will be analyzed by Transmission Electron Microscopy (TEM). Besides, X-Ray Diffraction (XRD) Analyses will be done. Then the mechanical properties of furniture joints of Beech (Fagus orientalis L) wood, Oak (Quercus robur) wood, and laminated wood materials bonded with nanoparticle filled PVAc manufactured, evaluated and the deformation analysis of the joints were conducted with helping image analysis. According to nanoparticles filled PVAc performance results, the low loading of nanoparticle (%1, %2) to PVAc matrix increased the bonding performance. At the same time, XRD and TEM results proofed more homogenously dispersed in the low loadings (%1,%2) of the nanoparticles. According to test results done to determine the effect of nanoparticle type, nanoparticle rate and material type on the bending strength, tension strength, and fatigue strength of the furniture joints, the maximum values were obtained in the joints of Beech and Oak prepared with low loading of SiO2 and TiO2 nanoparticles. In the deformation analysis, the measurements were conducted with image analysis were found to be similar to the results obtained with the clasical methods. As a result, nanoparticles can be used to improve the PVAc adhesives and the reinforcement of the furniture joints

Odun yoğunluğu tahmini için veri madenciliği ve piksel dağılımı yaklaşımı

The wood material has strategic importance in economic development. Innovations are the basic premise of commercial success in the wood industry, as in all industries. The density of wood provides valuable information about the physical and mechanical properties of the wood, and it is also directly related to the productivity in the forest industry. Many non-destructive test studies have been conducted to evaluate the physical properties of wood structures. This study was conducted to predict the density of wood in the species of oak (Quercus robur) and beech (Fagus orientalis L.) using the number of pixels in a grayscale image and data mining. To this purpose, pixel density of data was processed with the data collected from the images of wood specimens. This data was used as descriptor variables in artificial neural networks and random forest algorithm. The designed artificial neural network model and random forest algorithm allowed the prediction of density with an accuracy of 95.19% and 96.36%, respectively for the testing phase. As a result, this study showed that pixel density and data mining have the potential to be used as an instrument for predicting the density of wood

Experimental investigation and prediction of bonding strength of Oriental beech (Fagus orientalis Lipsky) bonded with polyvinyl acetate adhesive

Adhesive bond strength of solid wood plays a key role in the efficient use of wood in a large number of engineering applications. In this study, the effects of amount of adhesive, pressing pressure, and pressing time on bonding strength of beech wood bonded with polyvinyl acetate adhesive were investigated and predicted by developing an artificial neural network (ANN) model. Experimental results have showed that bonding strength of wood samples increased generally by increasing amount of adhesive, pressing pressure, and pressing time. Besides, ANN analysis has yielded highly satisfactory results. The designed neural network model allows predicting the bonding strength of wood samples with mean absolute percentage error of 2.454\% and correlation coefficient of 97.8\% for testing phase. It is clear from the results that the model has a good learning and generalization ability. This model therefore can be used to predict bonding strength of beech samples bonded with polyvinyl acetate adhesive under given conditions. Consequently, this study provides beneficial insights for practitioners in terms of the safe and efficient use of wood as an engineering material in applications related to the strength of the bond between wood and adhesive