Abstract

Industry 4.0 (I 4.0) is a major transformation in manufacturing that is driven by the use of digital technologies. Furniture and board businesses are one of the subsectors of the forest products sector that can benefit from I 4.0. In this study, a survey was administered to 206 employees working in furniture and board businesses to understand their awareness of I 4.0, their perceptions regarding its obstacles and potential benefits and practices. The most widely recognized I 4.0 technology by employees is digital connectivity. Employees also see the potential for I 4.0 to help them implement new business models. However, the main obstacles to implementing I 4.0 are a lack of skilled workers and high costs. Employees of furniture businesses are less aware of I 4.0 than are employees of board businesses. Additionally, only a small percentage of businesses in both sectors have an I 4.0 or smart manufacturing strategy. The results of this study suggest that furniture and board businesses need to do more to raise awareness of I 4.0 and to develop strategies for implementing it. By doing so, they can improve their productivity and competitiveness in the global marketplace. This study was conducted on a relatively small sample in a limited area, so the generalizability of the results is low.

Abstract

In the aftermath of events such as hurricanes, the economic impact of downed timber can reach billions of dollars. Accurate forecasting of stumpage prices after such events is crucial for maximizing recovery value while minimizing salvage costs. However, this poses challenges because of the inherent nature of the data. This study addresses these challenges by exploring the application of wavelet analysis, a novel approach in the field of forestry economic analysis. Wavelet analysis offers a unique framework for studying periodic phenomena in time series data, particularly when frequency changes over time are present. By leveraging wavelet analysis, this study uncovers relationships between timber market indices and hurricane seasons. The combination of traditional correlation analysis and wavelet coherence analysis enhances the statistical analysis in this study, offering a comprehensive examination of the relationship between the Timber Market Survey data and market indices. This innovative analytical approach enables a deeper understanding of the dynamics of the timber market and the potential effects of hurricanes on timber prices. Furthermore, this research highlights the recent advancements in wavelet methodology and the availability of open-source packages in the programming language R, such as WaveletComp and WaveletArima, that facilitate wavelet analysis and time series forecasting. The Wavelet-ARIMA model used in this study demonstrates its effectiveness in reducing noise and improving prediction accuracy. The study incorporates an extensive data set consisting of 10 Consumer Price Indices, 7 Producer Price Indices, 30 state-wide Timber Market Survey indices, 54 TMS subregions, and 6 open market series.

Abstract

The axial compression test was carried out on the basis of three different-size specimens of white wax (Fraxinus chinensis), fir (Abies fabri), and Yunnan pine (Pinus yunnanensis) to explore the influence of specimen length on the compression strength parallel to grain, peak strain, and elastic modulus of wood. Weibull’s weakest-link theory, Bazant’s law of size effect, and Carpinteri’s multiple fractal size effect were used for the analysis. The results showed significant size effects on theses parameters of wood along the grain. Using the three theories to predict the compressive strength of 100-mm-length specimens, the predicted value of Bazant’s law of size effect has the smallest error with the measured value, followed by Weibull’s weakest-link theory and Carpinteri’s law of multiple fractal size effect. The size-effect coefficients of the down-grain compressive strength of the three woods obtained using the slope method were 0.06, 0.11, and 0.09, respectively, which were consistent with the values of m in the Weibull fitting function.

Abstract

The integrity of melamine formaldehyde bonds in prototype cross-laminated timber (CLT) specimens was tested as part of a project on utilization of ponderosa pine (Pinus ponderosa) from forest restoration programs in the western United States. Bond integrity tests, block shear, and cyclic delamination are prescribed by ANSI/APA PRG-320 (ANSI/APA 2019) and ANSI 405 (ANSI 2018) to qualify new products. Of these, the cyclic delamination criterion is particularly challenging for layups developed in research labs and pilot plants. Delamination is often blamed on poor compatibility between adhesive and wood species, clamping pressure, or distribution of adhesive, neglecting other potential factors. One of the study objectives was to separate the effect of adhesive compatibility from other potential factors affecting bond integrity in CLT. Bonding integrity tests were conducted on prototype specimens bonded with melamine formaldehyde adhesive. Three types of specimens were studied: (1) specimens harvested from panels fabricated in an industrial CLT plant, (2) specimens harvested from panels fabricated in a pilot-line, and (3) short blocks cross-laminated from 102 by 102-mm sections. The short blocks included sections with juvenile wood and blue stain on bonded surfaces. All samples passed the PRG-320 block shear criteria. All short blocks passed the delamination criterion, demonstrating sufficient adhesive compatibility with the surfaces regardless of heavy presence of blue stain and juvenile wood. Specimens harvested from panels did not meet the delamination criterion. Delaminations developed near preexisting interlaminar gaps observed in prototype panels, which may be related to thickness variation or to inconsistent clamping pressure.

Abstract

Sustainable low-carbon design is actively guiding the public's green consumption and use of forest resources. With the slogan of replacing plastic with bamboo and the optimization of bamboo's organizational structure and processing form, bamboo is becoming more and more designable. However, we found that there are still many views expressing dissatisfaction with bamboo products, among which homogeneity and insufficient design differentiation are the most frequent. On the basis of this, we obtained attributes for measuring bamboo product satisfaction through literature review, conducted a questionnaire survey of 463 customers to obtain data, and empirically analyzed attributes such as product creativity (PC), product quality (PQ), product fashion (PF), soft added value (SV), and shopping convenience (SC). We assessed the impact on consumer satisfaction (CS), as well as the impact on satisfaction under the moderating effect of brand image (BI). The results show that PF, BI, PC, and PQ positively affect CS; PF, PQ, and SV positively affect the BI; PF, SV, and PQ positively affect CS through the intermediary effect of BI. SV has an insignificant effect on CS, but can positively affect CS through BI, indicating that there is a partial mediating effect of BI. However, the mediating effect of BI on PC, SC, and CS has not been verified. Finally, on the basis of the conclusions, several countermeasures and suggestions for bamboo product innovation are put forward.

Abstract

Using crushed hickory husks as raw materials, a single factor test was carried out on a hydraulic-plunger forming machine with different moisture contents and length–diameter ratios (LDRs) of forming mould in order to obtain biomass moulding fuel (BMF) briquettes. The moulding pressure in the forming mould was measured by the sensor, and the microstructures of the BMF briquettes were observed via stereomicroscope. Results showed that hickory husks could be compressed and formed into BMF briquettes at room temperature. When the moisture content of the raw materials was 14 percent and LDR of the forming mould was 4.5, the quality of BMF was best, and relaxation density of the BMF briquette was 0.98 g/cm³. When the moisture content stayed same, the forming pressure increased correspondingly with the increase of the LDR of the forming mould. When the LDR of the forming mould stayed the same, the moulding pressure increased first and then decreased with increase of moisture content. This study is of great significance because it demonstrates improvement in the utilization range of hickory husks, with the potential for reducing environmental pollution and increasing farmers’ income.

Abstract

The demand for wood in construction has led to shortages of strong wood types, causing a shift to costlier alternatives like concrete and nonbiodegradable materials, prompting the investigation of modifying softwoods for better engineering properties. This study investigates the optimization of a multistep impregnation process utilizing functionalized cellulose nanocrystals (f-CNCs) to enhance softwood properties. The process involves alkali delignification, ultrasonication, and vacuum pressure treatment to improve wood porosity and in turn improve CNC impregnation with uniform dispersion. Microstructural analyses through field emission scanning electron microscopy and atomic force microscopy (AFM) offer detailed insights into cell wall morphology and surface topography, whereas Fourier transform infrared spectroscopy highlights compositional shifts resulting from f-CNC impregnation. Mechanical testing demonstrates significant improvements for treated woods, particularly a 67 percent increase in modulus of elasticity for the 2 percent CNC-treated group compared with the control group; a 71 percent increase in modulus of rupture was observed for 2 percent CNC-, 3 percent NaOH-, and 2 percent acetic acid-treated group compared with the control sample. The sample delignified with 3 percent NaOH and impregnated by 2 percent f-CNC emerged as particularly effective. This research sets the stage for potential advancements in strengthening softwood using CNC, including a novel AFM method and alternative impregnation techniques like the Lowry method, inviting further exploration.

Abstract

In the era of a digital economy, business model innovation takes on a critical significance to the transformation of conventional manufacturing enterprises. Factors for the innovation originate from both inside and outside the manufacturing enterprises. Previous studies focused on external factors, and few on the main factors of innovation. With Chinese wooden furniture manufacturing enterprises as an example, the paper focuses on the effect of innovation subject factors on the formation and practice of business model innovation planning. It was found that employees of all ages and levels have different ideas about business model innovation practice, and learning and absorptive abilities of employees, entrepreneurship, and factors at all dimensions of enterprise culture at the organizational level play an active promoting role at different stages of business model innovation, among which enterprise culture has a regulatory effect. This study enriches the research field about the effect of innovation subjects on business model innovation behaviors, and provides reference for wooden furniture manufacturing enterprises and even conventional manufacturing enterprises to facilitate the realization of business model innovation.

Abstract

The use of cross-laminated timber (CLT) has significantly grown in North America, but hardwood species have not yet been deemed a viable raw material for manufacturing CLT panels. Therefore, softwood species continue to serve as the only approved material for CLT in structural applications according to ANSI/APA PRG-320. Nonstructural CLT products that utilize low-grade lumber from hardwood species, are a good option for introducing hardwoods into the CLT market.

Of the hardwood species located within Appalachia, northern red oak (Quercus rubra) is readily available. The purpose of this research was to develop hardwood cross-laminated timber mats utilizing low-grade red oak lumber. In order to manufacture red oak CLT mats, the best adhesive and bonding parameters had to be identified. Overall, sample CLT panels were made using three adhesives with nine different setups for each adhesive. The sample panels were processed into smaller blocks and separated for cyclic delamination and shear-block tests following the ANSI/APA PRG-320 standards.

This research determined that a phenol–resorcinol formaldehyde (PRF) adhesive produced the lowest percentage of delamination, satisfying the delamination requirements. The PRF adhesive also produced the largest percentage of wood failure in shear-block testing, however, the results fell short of meeting the requirements. A Taguchi statistical analysis was used to predict the optimal bonding parameters for each adhesive. The optimized bonding parameters for the polyurethane (PUR) adhesive produced favorable results, indicating the delamination results have the potential to nearly meet the standard requirements, while the predicted shear results would exceed the requirements.

Abstract

The packaging process in panel furniture manufacturing enterprises is the final process in production. However, there exists a lack of effective interaction and integration between the manufacturing processes and the information system. This challenge becomes more significant in the context of intelligent manufacturing. To address this, we propose a generalized digital twin workshop model for the packaging process in panel furniture manufacturing enterprises. Using this model, we establish a digital twin workshop for Company W’s packaging process, which improves interaction and integration with the information system. By analyzing the data from the workshop service system and the workshop twin data, we identify inefficiencies in the automatic packaging line and propose an optimization scheme using the digital twin workshop model. Through simulation in the virtual workshop and actual verification, we demonstrate that the proposed scheme improves the production efficiency of the automatic packaging line by approximately 20 percent and reduces the need for 5 to 6 packaging workers. Our study presents a new solution for upgrading the information system in the packaging process of panel furniture, contributing to the development and optimization of the furniture industry in the era of intelligent manufacturing.