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Ensuring sufficient mechanical performance while enabling lightweight design is critical for utilizing paper sandwich panels in the furniture industry. To design lightweight sandwich panels that balance mechanical properties and cost, this study developed a circular core paper sandwich panel (CCPSP) and investigated its structural efficiency using multi-objective optimization. The response surface method (RSM) based on Box–Behnken design was utilized to establish mathematical models relating the paper tube spacing, inner diameter, and height to the out-of-plane compressive strength, density, and cost. The resulting models effectively revealed the coupled effects of the parameters on the responses. Subsequently, the models were optimized using the non-dominated sorting genetic algorithm II (NSGA-II) to find the Pareto optimal trade-offs between maximizing compressive strength while minimizing its density and cost. The optimization solution resulted in an optimal set of paper tube geometries that maximized the structural efficiency of CCPSP. Overall, lower tube height conferred superior structural efficiency, while tube spacing and diameter were constrained. The results highlight the potential of CCPSP as an efficient and sustainable material for furniture manufacturing, enabled by multi-objective optimization of its structure. [ABSTRACT FROM AUTHOR]

This paper focuses on the optimization of a critical operation in the furniture manufacturing process, identifying it as a key priority for improvement by applying Systems Theory. The primary objective of this study is to develop a mathematical model for optimizing the detected key process by employing artificial neural networks (ANNs) which mirror adaptive management principles. Three input and three output parameters significantly impacting the effectiveness of this key process have been systematically identified and experimentally measured. It was necessary to perform multi-objective optimization (MOO), which consisted in achieving the minimum values of cost and process time and the maximum value of the quality index through the optimal setting of the input parameters (cutting speed, feed rate, and volume of removed material). The application of ANNs in MOO in this research study is a novelty in this field. The results obtained through application of the ANN method reveal the optimal values of the examined parameters, which represent the best combination of input technical variables leading to the best results in output economic parameters. This multi-objective optimizing solution facilitates enhanced process efficiency. By integrating Systems Theory, Complexity Theory, and adaptive management, this research advances sustainable process improvements by minimizing resource use, reducing waste, and enhancing overall system efficiency. [ABSTRACT FROM AUTHOR]

Wood lumber is widely used in the construction and furniture manufacturing industries. In order to solve the problems of poor recognition, low efficiency and few detection types of manual and traditional processing methods, this paper proposes a model SGM-YOLO for the detection of surface defects in wood lumber. The SGM-YOLO model references a new backbone feature network, SL-backbone, to enhance the model’s ability to detect defects of different sizes. And, a new GVE-neck layer structure will be proposed in this paper, which reduces the parameters as well as the accuracy. In addition, the Normalized Weighted Distance Loss (NWD) small target detection algorithm is combined with the MPDIOU boundary loss function to replace the original loss function to further enhance the small target detection capability. Experiments show that SGM-YOLO achieves an average recognition accuracy of 77.4% for wood lumber defects, compared with the original model YOLOv8, the mAP is improved by 3.8% and the FPS is improved by 4.4, while the number and size of parameters are reduced, which provides better detection of several defects that are difficult to be identified. The methods presented in this paper were also applied to the YOLOv5 model, yielding positive results, to confirm its generalizability. The results demonstrate the high application value of the SGM-YOLO model in the wood lumber processing and manufacturing industry’s final product inspection. [ABSTRACT FROM AUTHOR]

Several industries deal with imperfect and perishable raw materials that need to be cut in order to assemble products. Managing the purchasing, cutting, and sequencing decisions is a challenging problem that spans both inventory control and production process management, where decisions are usually optimised separately. In this research we develop a dynamic programming model that determines these joint decisions. The inspiration comes from furniture companies where the raw material are sheets of plywood that may contain imperfections that need to be avoided when cutting pieces to build the assembled furniture. We evaluate decisions regarding the layout of pieces onto the plywood, dispatching policies of ordered furniture , and the quality of the raw material. The model is useful to perform cost analysis for different scenarios. Variations on the expected demand, purchasing, ordering, disposal, holding costs and initial inventory are considered. Experiments conclude that focusing in quality becomes more important than the age of the plywood sheet if the companies implement a production flow that cuts and sorts all pieces before assembling the furniture. Cost analysis confirms that a just-in-time policy in which little inventory is kept results in important savings when compared with the standard operation of the companies. [ABSTRACT FROM AUTHOR]

This study experimentally investigated the effects of selected factors on the bending moment capacity (BMC) of case furniture joints. The main aim was to explore mixed applications of wood-based materials and fasteners in manufacturing case furniture to reduce material costs. The study examined the effects of the face member material—particle board (PB), plywood (PL), and block board (BB)—edge member material (PB, PL, and BB), and joint shape (T-shape and L-shape) on BMC. Additionally, the study evaluated the effects of joint type (two eccentrics (TE), two dowels (TD), and one eccentric and one dowel (ED)), and material type (PB, PL, and BB) on BMC for L-shaped joints. The results showed that joint shape and face member material significantly affected the BMC of case furniture joint. The BMCs of T-shaped joints were significantly greater than those of L-shaped joints, regardless of the material of the face and edge members, except when the face member was made of PL. For L-shaped joints with PL face members, the BMCs were significantly higher compared to others. Joints constructed with TE exhibited significantly higher BMC compared to ED and TD for the same material type. For PB, TE joints exhibited an increase of approximately 3.0 Nm and 2.0 Nm compared to TD and ED, respectively. For PL, TE showed an increase of 9.1 Nm and 4.1 Nm compared to ED and TD, respectively. For BB, the increases were 7.0 Nm and 6.6 Nm compared to ED and TD. The BMC of joints made with PL and constructed with TE and ED was significantly greater than those of BB, followed by PB. However, for joints assembled with TD, there was no significant difference among the three materials. The ratios of BMC for joints constructed with ED compared to the half-sum of TE and TD were 0.73, 1.04, and 0.79 for PB, PL, and BB, respectively. These results suggest that the face member material predominantly influences the BMC of case furniture joints, indicating the potential to reduce costs by combining different materials and joint types. [ABSTRACT FROM AUTHOR]

This study assessed the occupational health and safety conditions in a furniture manufacturing facility, focusing on key environmental factors such as noise, lighting, thermal comfort, and dust exposure. Noise measurements recorded levels as high as 95.3 dB(A) during CNC machine operations, exceeding legal exposure limits of 87 dB(A), posing significant risks to workers' hearing health. Lighting assessments showed levels ranging from 134 to 247 lux in production lines, which falls below the recommended threshold of 300 lux for adequate visibility. Thermal comfort was evaluated with temperature readings at 14.2 °C and relative humidity at 43%, revealing marginal comfort conditions that could reduce worker efficiency and satisfaction. Dust exposure measurements indicated respirable dust concentrations reaching 3.69 mg/m³ in the cutting department, which is close to the permissible exposure limit of 5 mg/m³, raising concerns about long-term respiratory health. These findings suggest several measures to improve workplace safety, including enhanced engineering controls, mandatory personal protective equipment (PPE), improved lighting systems, optimised thermal conditions, and advanced ventilation to reduce dust exposure. This comprehensive evaluation provides critical insights for improving furniture factories' occupational health and safety practices. [ABSTRACT FROM AUTHOR]

In recent years, 3D printing technology has become very important in many fields of science, manufacturing, design, medicine, aviation, sports, etc. Furniture design and manufacturing are also not left out of this trend. In this study, the results of bending moments and stiffness of joints of thin structural elements connected by 3D printing with polylactic acid (PLA) connectors are given. The connectors are newly developed, and information on their strength characteristics is lacking in the literature. Ten joints were investigated, made with 9 and 12 mm plywood and 6 mm MDF. The tested joints constructed by 3D-printed connecting elements show a high strength under arm compression bending load, between 44.16 and 24.02 N·m. The stiffness coefficients of joints with 3D-printed connecting elements are between 348 and 145 N·m/rad and are higher than those of conventional detachable mitre joints but lower than those of glued ones. The type of filling of the hollow section of the connecting elements and the wall thickness influenced the joints' strength and stiffness. Reducing the width of the connecting elements from 40 to 30 mm and the inner radius between the arms from 2 to 1 mm does not significantly affect the joints' strength and stiffness coefficients. [ABSTRACT FROM AUTHOR]

In recent years, with the advancement of laser equipment and technology, several papers have documented the utilization of laser technology in the domain of plate edge sealing. However, there is currently a lack of research on suitable materials for laser edge sealing. Therefore, in our research described in this paper we mainly explored the use of a functional layer of a kind of edge sealing material used in laser edge sealing technology, namely a laser hot melt adhesive material. In this study we used polypropylene (PP) and ethylene-vinyl acetate (EVA) as matrix materials to prepare laser hot melt adhesive materials which can be activated by a 1065 nm near-infrared laser. Compared with the traditional edge sealing technology, our operation process is simpler, the beauty of the product is better and all its performances meet the relevant standards. The thermogravimetric analysis (TGA) and other thermal analysis methods demonstrated that the laser adhesive can undergo melting upon laser activation, provided an appropriate amount of inorganic laser-sensitive agent is added, without undergoing any thermal decomposition. The influence of the elastomeric EVA resin on the crystallinity of the PP was investigated using X-ray diffraction (XRD) and differential scanning calorimetry (DSC), demonstrating a significant impact on the resulting blend properties. X-ray photoelectron spectroscopy (XPS) shows a partial reduction of Cu2+ to Cu+ within the laser sensitizer after activation of the adhesive by the laser. The optimal mass ratio of PP and EVA in the laser adhesive was investigated through experimental analysis. The morphological changes of the laser adhesive before and after laser activation were observed using scanning electron microscopy (SEM). We believe the research conducted by our team has significantly advanced the progress of laser edge banding technology and expedited its application in the field of furniture manufacturing. [ABSTRACT FROM AUTHOR]

The furniture manufacturing sector faces significant challenges in machining composite materials, where quality issues such as delamination can lead to substandard products. This study aims to improve the classification of drilled holes in melamine-faced chipboard using Explainable AI (XAI) techniques to better understand and interpret Convolutional Neural Network (CNN) models' decisions. We evaluated three CNN architectures (VGG16, VGG19, and ResNet101) pretrained on the ImageNet dataset and fine-tuned on our dataset of drilled holes. The data consisted of 8526 images, divided into three categories (Green, Yellow, Red) based on the drill's condition. We used 5-fold cross-validation for model evaluation and applied LIME and Grad-CAM as XAI techniques to interpret the model decisions. The VGG19 model achieved the highest accuracy of 67.03% and the lowest critical error rate among the evaluated models. LIME and Grad-CAM provided complementary insights into the decision-making process of the model, emphasizing the significance of certain features and regions in the images that influenced the classifications. The integration of XAI techniques with CNN models significantly enhances the interpretability and reliability of automated systems for tool condition monitoring in the wood industry. The VGG19 model, combined with LIME and Grad-CAM, offers a robust solution for classifying drilled holes, ensuring better quality control in manufacturing processes. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The object of the study is the performance of the furniture manufacturing sector in Kenya. The paper utilized descriptive and explanatory research design. The study targeted a population of 686 managerial staff and 195 CEOs in the furniture manufacturing sector. Structured questionnaires were distributed to the senior managers and a factor analysis was used to reduce the number of variables and establish the underlying constructs while analysis of moments of structures was applied to develop the theory. Technology capability was found to explain 49 % of the variance in the firm performance. The fit indices suggested that the data was an adequate fit of the hypothesized model relating to technology capability and firm performance NFI = 0.604, RFI = 0.501, IFI = 0.639, TLI = 0.539 and CFI = 0.634 with a p-value>0.05. In addition, the study found out that technology capability and firm performance had a positive and statistically significant contribution at 0.05 level of significance. This was depicted by the significance of the standardized regression coefficient of technology capability hypothesized path (β = 0.878, S.E. = 0.75, C.R. = 11.743, and p-value<0.05). The findings also revealed that the size and age of the firm do not moderate technology capability in strategy implementation on firm performance. This was depicted by the significance of the standardized regression coefficient of firm size and firm age hypothesized path (β = –0.171, S.E. = 2.015, C.R. = –0.085 and p-value>0.05). Therefore, the alternative hypothesis that size and age have a negative moderating contribution on firm performance was rejected at 0.05 level of significance. To enhance a firm’s performance in terms of profitability and growth, it is crucial to manage and sustain technology capabilities through an effective strategy implementation process. The study not only adds value to the existing body of knowledge in strategic management practice but points out that when implementing strategy, CEOs and senior managers should consider technology capability factors to improve the firm performance. [ABSTRACT FROM AUTHOR]

Making a Master Production Schedule (MPS) is a very important activity for a manufacturing industry. This is due to the fact that MPS serves as an input for material and production planning. Between the years 2020 and 2022, there were significant fluctuations observed in container freight rates. As response, a lot of manufacturing industry focus on optimizing their container delivery schedule. Hence, there is a need for aligning the master production schedule with the delivery schedule. This paper presents the development of a novel heuristic approach to address problems with the creation of MPS. Specifically, the focus is on the situation where container delivery schedules are prearranged and serve as a main input for creating the MPS. There are two objective functions that are going to be reached: 1) minimize the total number of product variations or Stock Keeping Units (SKU) per month; and 2) minimize the number of SKU per container. The proposed heuristic approach uses the similarity concept to group objects in a clustering technique. It is then implemented in a real-world case of a furniture manufacturing company. Further results were obtained and then compared to the heuristic technology that had previously been used by business entities. The results show that the number of product variations (SKU) that must be performed per month is 10% lower than that of the existing heuristic. In addition, the ratio of SKU variations per container is 9% lower than that of the existing heuristic. The time required to complete the task of creating MPS is less than one minute, as opposed to the one working day required by the company's existing heuristic. [ABSTRACT FROM AUTHOR]

Objectives. Work-related musculoskeletal disorders (MSDs) of the shoulder may manifest subclinically. By combining risk assessment and clinical instruments, it may be advisable to recognize workers who may develop more complex MSDs early. This study aimed to evaluate the relationship between biomechanical risk factors and subacromial pain provocation in healthy manufacturing workers. Methods. A cross-sectional descriptive observational study was carried out with workers in the furniture manufacturing industry. The occupational repetitive action (OCRA) checklist was applied to detect risk factors and three clinical tests used to detect subacromial tissue reactivity: the supraspinatus test, the painful arc test and the Hawkins–Kennedy test. Results. The positivity of the clinical tests is higher in the supraspinatus test, followed by the Hawkins–Kennedy test, and lowest in the painful arc test, for both the right and left shoulders. No significant associations were found with the overall OCRA checklist index or specific biomechanical factors. Conclusion. The biomechanical risk factors and the provocation of subacromial pain reviewed in this study were not found to be related. Other physical tests that are more sensitive and adapted to workers at risk of developing musculoskeletal shoulder disorders should be explored. [ABSTRACT FROM AUTHOR]

Facility location selection and internal layout planning are critical strategic decisions for long-term sustainability. This study identified the most feasible location and optimal layout for a commercial bedroom furniture manufacturing facility through a seven-phase evaluation of Istanbul, Ankara, Izmir, and Bursa. The Analytical Hierarchy Process (AHP) and PROMETHEE were used for city and district selection, with AHP calculating criteria weights and PROMETHEE ranking alternatives. The Borda Count Method aggregated MCDM results, selecting Istanbul as the optimal city and Dudullu Organized Industrial Zone (O.I.Z.) as the most favorable district. The CORELAP method developed an optimal singlestory layout for a 2688 m² production and assembly facility, enhancing production flow, reducing material handling costs, and improving efficiency. These findings underscore the importance of strategic facility location and layout planning in improving the furniture industry's competitiveness and sustainability. The practical implications of this research are significant, as the findings can be directly applied to improve the competitiveness of the furniture industry. The study offers a comprehensive framework for strategic decision-making, providing valuable insights and a systematic approach applicable to similar problems in various sectors. [ABSTRACT FROM AUTHOR]

Reverse design and additive manufacturing technologies are fast ways to develop customised products. In this study, furniture protective foot covers were taken as the design object. Using flexible filaments of polylactic acid (PLA) and the development process of reverse design to additive manufacturing, the protective foot covers were designed and manufactured to fit the shape of the chair feet. Furniture protective foot covers have high practical value. They have a certain buffering effect, avoiding the damage caused by the collision of furniture feet with the ground when moving furniture; secondly, they reduce the noise generated by the collision of furniture feet with the ground, creating a quiet and comfortable home environment. According to the finite element simulation results, the maximum stress value of the European-style chair installed with protective foot covers was decreased by 90.8% in the case of vertical fall, which verifies that the protective foot covers have an obvious buffering effect. Noise test results show that the noise of the European-style chair installed with protective foot covers was decreased by 51.0%, which verifies that the protective foot covers have an obvious quieting effect. [ABSTRACT FROM AUTHOR]

Timber industries make an essential contribution to economies worldwide, while the sustainable supply of timber generates revenue, supports employment, and contributes to economic activity. The strategic choice of wood species using specific criteria can have substantial economic outcomes for the timber industry in Greece. This study assessed the suitability of hardwood species most commonly used by Greek timber industries. The assessment was conducted with the use of a Multiple-Criteria Decision Analysis approach, taking into consideration specific criteria that affect the quality of timber. According to the findings, walnut was the optimal alternative that outranked the other examined species. Chestnut, oak, beech, ash, and hornbeam also achieved positive scores, and therefore, they are also acceptable alternatives as broadleaved species suitable for furniture manufacturing and sawn timber production. Greek timber industries can enhance their products' value and market appeal by focusing on species that meet high-quality standards and consumer preferences. [ABSTRACT FROM AUTHOR]

Copyright of Revista Producao Online is the property of Associacao Brasileira de Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The effective and comprehensive utilization of forest resources has become the theme of the global "dual-carbon strategy". Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material in the field of construction, furniture manufacturing, as well as derivative processing for its excellent physical and mechanical properties, decorative properties, and processing performance. Taking Medium Density Fiberboard (MDF) as the recombinant material as the research object, an event-triggered synergetic control mechanism based on interventional three-way decision making is proposed for the viscoelastic multi-field coupling-distributed agile control of the "fixed thickness section" in the MDF continuous flat-pressing process, where some typical quality control problems of complex plate shape deviations including thickness, slope, depression, and bump tend to occur. Firstly, the idea of constructing the industrial event information of continuous hot pressing based on information granulation is proposed, and the information granulation model of the viscoelastic plate shape process mechanism is established by combining the multi-field coupling effect. Secondly, an FMEA-based cyber granular method for diagnosing and controlling the plate thickness diagnosis and control failure information expression of continuous flat pressing is proposed for the problems of plate thickness control failure and plate thickness deviation defect elimination that are prone to occur in the continuous flat-pressing process. The precise control of the plate thickness in the production process is realized based on event-triggered control to achieve the intelligent identification and processing of the various types of faults. The application test is conducted in the international mainstream production line of a certain type of continuous hot-pressing equipment for the production of 18 mm plate thickness; the synergistic effect is basically synchronized after 3 s, the control accuracy reaches 30%, and the average value of the internal bond strength is 1.40, which ensures the integrity of the slab. Practical tests show that the method in the actual production is feasible and effective, with detection and control accuracy of up to ±0.05 mm, indicating that in the production of E0- and E1-level products, the rate of superior products can reach more than 95%. [ABSTRACT FROM AUTHOR]

Thermosetting polymers offer a wide range of applications in modern industries, including coatings, the automotive and aerospace industries, and furniture manufacturing. The curing process, which is a key step in the application of such materials, has become a research hotspot. More specifically, significant research efforts have been devoted toward shortening the curing cycle and reducing curing energy consumption without affecting product quality. Two common curing methods, namely, infrared (IR) curing and hot air convection curing, have been commonly employed. IR curing technology demonstrates certain advantages, such as high energy efficiency and adaptability, compared to traditional convection curing technology. Moreover, it has achieved desirable results in engineering applications and research. In this review, the current research on IR curing technology is presented in detail based on two fundamental aspects: the heat transfer process and the curing process. This article provides a comprehensive overview of the IR curing heat transfer process in terms of IR heating equipment, heat transfer monitoring devices, heat transfer models, and heat transfer simulation methods. Moreover, it summarizes and compares the basic research methods, equipment, and theoretical models involved in the curing process. In addition, it describes the non-thermal effect and its impact on the properties of cured products. This study describes the author's perspective and opinions on the research direction in IR radiation-based curing technology. This literature review concludes that IR curing technology has strong research value and application prospects, particularly in fields requiring low-temperature rapid curing of thermosetting polymers. [ABSTRACT FROM AUTHOR]

With the integration and advancement of new generation information technology and manufacturing processes, big data in manufacturing presents solutions for transforming manufacturing model today. In order to mine the hidden knowledge value and potential capabilities of big data and facilitate the intelligent decision-making of business managers in complex dynamic manufacturing environments, a comprehensive study of intelligent manufacturing management driven by big data technologies was hereby carried out. Firstly, sources and characteristics of big data in the workshop were explored, providing an overview of the enabled big data technology including data collection, transmission, storage, computation, processing, visualization, and big data mining algorithms. Then, big data application scenarios were reviewed using the intelligent manufacturing workshop as the research context, and applications of big data in furniture workshops were discussed from four major aspects, job shop scheduling, quality control, prediction maintenance, energy management, and supply chain planning. Afterwards, data challenges for furniture intelligent manufacturing in the workshop were clarified, and a conceptual framework for furniture intelligent manufacturing was finally proposed based on big data technologies. Overall, the present research offers valuable insights and ideas for furniture workshops and future research directions. [ABSTRACT FROM AUTHOR]

Product design and manufacturing leverage 3D scanning for various applications. This study aims to investigate the effectiveness of 3D scanning in furniture production by surveying the literature and showcasing four real-world case studies. The literature review reveals that 3D data acquired from real-world objects have applications in research, rapid prototyping, restoration, and preservation of antique furniture, optimizing CNC machining processes, and measuring furniture components for quality control. The case study descriptions demonstrated the circumstances, rationale, and methodology for 3D scanning. All the case studies analyzed stem from the collaboration between the Laboratory for Product Development and Design at the Faculty of Mechanical Engineering at the University of Sarajevo and various furniture production enterprises from Bosnia and Herzegovina. The conclusions highlight that 3D scanning in the furniture sector is advantageous for developing computer-aided design models from early-stage design prototypes, validating the dimensional accuracy of manufactured components by comparing with CAD models, safeguarding and reconstructing vintage furniture, and remanufacturing formerly produced goods that lack complete technical records (reverse engineering). [ABSTRACT FROM AUTHOR]

The study evaluated the challenges Tanzania's small-scale furniture industry faced. The resource-based view and resource dependency theory were used as the study's guiding concepts. From the nation's commercial centre of Dar es Salaam, 154 furniture carpenters were chosen at random. The information was gathered via the questionnaire. The collected data was examined using a descriptive analysis. According to the findings, carpenters faced several difficulties, including a shortage of modern machine tools, inadequate working capital, low labour skills, a lack of formal workspaces, and fierce competition from imported furniture. The lack of modern machine tools prevented small and medium enterprises from producing goods of the kind needed to enter growing markets. To boost productivity, furniture production must make use of current machinery. Insufficient availability of suitable financial services had led to insufficient operating capital for investments in furniture manufacturing. The study concludes that the furniture business has a significant role in generating income and jobs. The study recommends that Governments should promote a business-friendly environment in addition to creating financial and non-financial services as well as supportive institutional infrastructure. [ABSTRACT FROM AUTHOR]

The furniture-manufacturing industry is pressured to improve quality, productivity, and profitability, particularly within increasingly volatile market conditions. This study is focused on the development of methods for optimizing production processes in a furniture-manufacturing company through the application of an integrated risk management framework. By integrating Failure Mode and Effects Analysis (FMEA) with advanced multi-criteria decision-making (MCDM) techniques, specifically fuzzy AHP, fuzzy TOPSIS, and fuzzy WINGS, a hybrid model is developed to identify, prioritize, and address critical failure points while accounting for complex interdependencies. Significant failure modes, such as order inaccuracies and delivery delays, are revealed as key findings and are found to notably affect productivity and customer satisfaction. The proposed model’s ability to capture cascading effects and a nuanced prioritization enables a more precise risk assessment, thereby supporting resilience and process efficiency in the furniture-manufacturing sector. This approach is shown to not only optimize production but also provide a foundation for applying such hybrid models in other industries to manage sector-specific interdependencies effectively.

This paper focuses on the optimization of a critical operation in the furniture manufacturing process, identifying it as a key priority for improvement by applying Systems Theory. The primary objective of this study is to develop a mathematical model for optimizing the detected key process by employing artificial neural networks (ANNs) which mirror adaptive management principles. Three input and three output parameters significantly impacting the effectiveness of this key process have been systematically identified and experimentally measured. It was necessary to perform multi-objective optimization (MOO), which consisted in achieving the minimum values of cost and process time and the maximum value of the quality index through the optimal setting of the input parameters (cutting speed, feed rate, and volume of removed material). The application of ANNs in MOO in this research study is a novelty in this field. The results obtained through application of the ANN method reveal the optimal values of the examined parameters, which represent the best combination of input technical variables leading to the best results in output economic parameters. This multi-objective optimizing solution facilitates enhanced process efficiency. By integrating Systems Theory, Complexity Theory, and adaptive management, this research advances sustainable process improvements by minimizing resource use, reducing waste, and enhancing overall system efficiency.

Distributed flexible flowshop scheduling is getting more important in the large-scale panel furniture industry. It is vital for a higher manufacturing efficiency and economic profit. The distributed scheduling problem with lot-streaming in a flexible flow shop environment is investigated in this work. Furthermore, the actual constraints of packaging collaborative and machine setup times are considered in the proposed approach. The average order waiting time for packaging and average order delay rate is used as objectives. Non-dominated sorting method is used to handle this bi-objective optimization problem. An improved encoding method was proposed to address the large-scale orders that need to be divided into sub-lots based on genetic algorithm. The proposed approach is firstly validated by benchmark with other multi-objectives evolutionary algorithms. The results found that the proposed approach had a good convergence and diversity. Besides, the influence of the proportion of large-scale orders priority level and sub-lot size was investigated in a panel furniture manufacturing scenario. The results can be concluded that the enterprise could obtain shorter order average waiting time and delay rate when the sub-lot sizes were set as two and the order priority level was allocated in the proportion of 1:2:3:4:5. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this study is to analyze the technical feasibility of adopting I4.0 technologies in a large furniture industry located in the southern region of Brazil. Design/methodology/approach: Strategy research is a single case study, qualitative approach, collecting empirical data through in-depth interviews, participant observation, and a documental survey submitted to content analysis. Findings: Results evidenced that technologies I4.0 were considered technically viable for adoption in the company, and some of these technologies have already been adopted in some of its operations, such as IoT, big data, Cyber-physical Systems (CPS), Additive Manufacturing (AM)/3D printing, cloud computing, and vertical integration. On the other hand, RFID, collaborative robots, digital twins, augmented reality, and AI present technical feasibility but have not yet been adopted. Research limitations/implication: The limitation of the research stems from the strategy option for the case study, which restricts the possibility of generalizing the results obtained. Practical implications: The results of the study provide a review of the operational processes of the furniture industry, with the aim of identifying industry 4.0 technologies that can be adopted from the perspective of cost-benefit ratio. Originality/value: The increasing integration of the Internet of Things (IoT) in the industrial segment enables a new industrial era. However, furniture manufacturing is in the initial stages of adopting these technologies. The study addresses a topic that still represents a taboo in the corporate environment of the industrial sector in question and therefore offers elements for debate. [ABSTRACT FROM AUTHOR]

Curving woodworks exhibit wide applications in wooden furniture manufacturing due to the conformable visual and tactile experience, are welcome among consumers. However, the corresponding long-term shape stability facing the stress relaxation is an attention-worthy issue with the fundamental insights about the mesoscopic behaviors of vessels have not been provided. Here, we proposed the investigation into the effect of vessels on stress relaxation behavior of white oak (Quercus alba L.). Results demonstrated that stress relaxation modulus of specimen decreased with the elevation in MC and temperature, and vessel-containing specimens displayed more evident stress relaxation. Providing more physical connotation, Zener model is more suitable for the numerically investigation into the stress relaxation than logarithmic model. The time-temperature-moisture superposition principle (TTMSP) allows us to predict the~10 d and ~1 d stress relaxation behavior of white oak facing different temperatures and MCs. Additionally, stress relaxation of white oak with vessels is more evident, which can be attributed to the stress concentration and resultant deformation around the vessel. We believe that this work is beneficial for obtaining a mesoscopic understanding of vessels on stress relaxation behaviors of wood. It thus paves a way to exploit the methodologies to improve the shape-stability of curving woodworks. [ABSTRACT FROM AUTHOR]

Castanopsis orthacantha Franch. 1899 is one representative tree species distributed in the evergreen broad-leaved forests of southwestern China. This species is an important source of timber for manufacturing furniture, floors, and paper. It also plays a significant role in maintaining ecological balance and stability. To help with the genetic diversity assessment of C. orthacantha, we sequenced and assembled the first complete chloroplast genome. The length of the chloroplast genome was 160,588 bp, with a typical quadripartite structure (GenBank accession no. OR900101). The large single-copy (LSC), small single-copy (SSC), and two inverted repeats (IRs) were 90,237 bp, 18,953 bp, and 25,699 bp in length, respectively. We annotated one hundred and thirty genes across the chloroplast genome, including 86 protein-coding genes (79 are unique), 37 tRNA genes (29 are unique), and eight rRNA genes (four are unique). Seventeen genes had one intron, and four were detected with two introns. The maximum likelihood phylogeny suggested that C. orthacantha, C. lamontii, C. sclerophylla, and C. hainanensis formed a clade with a high bootstrap value. This newly sequenced chloroplast genome assembly will aid in the population genetic and phylogenetic studies of Castanopsis species in the future. [ABSTRACT FROM AUTHOR]

This paper tackles the issue of moisture variation in wood-based materials, explicitly focusing on melamine-coated particleboard (hereafter referred to as melamine) and medium-density fiberboard (MDF) used in the third phase of wood industry transformation. The approach involves a comprehensive strategy for predicting moisture content variation, incorporating numerical simulation, experimental testing, and the application of artificial neural network (ANN) technology to enhance accuracy in furniture manufacturing. The developed ANN models are tailored to predict moisture content changes under specific thermal comfort conditions. Remarkably, these models demonstrate high precision, with an average error margin of only 1.40% for 8% moisture content (MC) and 2.85% for 12% MC in melamine, as well as 1.42% for 8% MC and 2.25% for 12% MC in MDF. These levels of precision surpass traditional models, emphasizing this study's novelty and practical relevance to the industrial context. The findings indicate that ANN models adapt to diverse environmental conditions, presenting a robust tool for optimizing moisture management in wood-based materials. This research contributes valuable insights for improving the reliability and efficiency of moisture content predictions in the wood industry. [ABSTRACT FROM AUTHOR]

As an agroforestry resource willow species (Salix spp.) becoming increasingly important in the protection of riverbanks, recovery of floodable lands, soil bioremediation, biomass production, and wicker furniture manufacture, Babylon willow (Salix babylonica) is widely planted all over the world and is found throughout Iran as part of the rural landscape and is mostly planted for ornamental or bioremediation purposes. Rust fungi in the genus Melampsora usually cause disease on Salix species. Identification of Melampsora species is often complicated because there are few differences in spore morphology and little is publicly available in comparative sequence data. Willow trees in Iran have been reported to be infected by 15 Melampsora species; however, most of these records are based on morphological characterization. During surveillance activities carried out in June 2007, a rust species was detected on isolated Babylon willow trees in an area in Northern Iran. Both the rust fungus and the host plant were identified on the basis of morphological features and DNA sequencing. Based on a combination of morphology, large subunit (LSU) rDNA sequencing and phylogenetic analyses, our rust specimen was identified as Melampsora ferrinii, which is newly reported from Iran on Salix babylonica. Melampsora ferrinii was originally described from the Americas and this is the first time that this rust has been observed on its telial host, Babylon willow, in Asia. The documentation of the rust fungus was performed using both scanning electron microscopy (SEM) and light microscopy. Additionally, an identification key for Melampsora species reported on Salix spp. in Iran is included. [ABSTRACT FROM AUTHOR]

It is not uncommon to see start-ups suddenly fail. Often, startups try to follow the example of other, successful companies, but they don’t always succeed, so this article looks at KPIs for startups in the furniture industry. The furniture industry in the Baltic States is reviewed and their development at different stages of the company’s growth is analyzed. The product factors and interrelationships of a successful furniture company have been identified. The article presents the results of the surveyed companies engaged in the development of products for the furniture industry. The reasons and the main factors influencing the success of the company are given. Based on the results of the study, a model for the development of KPIs for start-ups in the furniture industry is presented and conclusions and suggestions are presented. The model consisted of 10 different spheres (success factors, fail factors, inbound logistics, outbound logistics, marketing & sales, procurement, operation, service, HRM, technology development, sustainability) for 5 different companies size (1–9 employees, 10–49 employees, 50–99 employees, 100–249 employees and 250 and more employees). In the model were overwide main KPIs blocks and suggested considerate of companies size. [ABSTRACT FROM AUTHOR]

Superior surface finishing in furniture manufacturing requires an understanding of varnish product rheology. The rheological properties of acrylic primer, basecoat and topcoat, intended for roller varnishing and UV curing are examined in the study. Two methods were used to measure viscosity: Brookfield rheoviscometer and Ford cup. The results discuss the effect of increasing temperature on a decrease in viscosity. Rheological modeling using the Ostwald de Waele power law model explained the non-Newtonian, shear-thinning, rheostable behavior of liquid. It was shown that the flow index of some varnish products in Standard Conditions for Temperature was close to the Newtonian fluid. However increasing consistency index parameter indicates the pseudoplastic behavior of the fluid. The findings highlight the importance of controlling viscosity and temperature during varnish product application processes to ensure optimal coating quality. This research provides valuable insight into the rheological properties of industrial coatings, facilitating advances in coating technology and quality control practices. [ABSTRACT FROM AUTHOR]

• The species profile of VOCs from abundant sources were presented. • The potential tracers of VOCs in different sources were identified. • Abundant α-pinene were found in solid wood furniture manufacturing. • T/X ratio can distinguish painting (<2) from printing (>2) sources. A survey was conducted of the volatile organic compounds (VOCs) released from sources of solvent use, industry activities and vehicle emissions in Guiyang, a capital city of China. Samples were collected by canisters and analyzed by GC-MS-FID. The species profiles of VOCs emitted from sources were obtained. Results showed that xylenes, ethylbenzene, acetone and dichloromethane were the characteristics species for painting, 2-propanol and ethyl acetate for printing, α-pinene for solid wood furniture manufacturing, and 2-butanone for biscuit baking. These characteristics species could be as tracers for the sources respectively. In most of samples from the solvent use, the benzene/toluene (B/T) ratio was less than 0.3, indicating that the ratio could be as the indicator for tracing the solvent use related sources. The results also suggested that the toluene/xylene (T/X) ratio be as the indicator to distinguish the VOCs sources of painting (<2) from the printing (>2). Aromatics contributed the most to ozone formation potential (OFP) of most painting and non-paper printing sources, and oxygen-containing VOCs (OVOCs) were major species contributing to OFP of the sources from food production and paper printing. The OFP of the VOCs emissions from vehicle in tunnels and from other manufactures were dominated by both aromatics and alkenes. The α-pinene could explain 56.94% and 32.54% of total OFP of the VOCs sources from filing cabinet and solid wood furniture manufacturing, which was rarely been involved in previous studies of VOCs source profiles, indicating that the species of concern for VOCs sources are still insufficient at present. [ABSTRACT FROM AUTHOR]

In today's world, a situational awareness of sustainability is becoming increasingly important. Leaving a better world for future generations is becoming the main interest of many studies. It also puts pressure on managers to change production methods in most industries. Reducing carbon emissions in industry today is crucial to saving our planet. Theoretical research and practical industry requirements diverge, even though numerous researchers have tackled various strategies to handle carbon emission problems. Therefore, this work considers the carbon emission problem of the furniture manufacturing industry in Hosur, Tamilnadu, India. The case study company has a manufacturing system that resembles a hybrid flow shop (HFS) environment. As the HFS scheduling problems are NP-hard in nature, exact solution techniques could not be used to solve the problems. Hence, a sequential hybrid optimization algorithm (SHOA) has been developed in this paper to minimize the carbon footprint. In the SHOA, the pigeon-inspired optimization algorithm (PIOA) is hybridized sequentially with the firefly algorithm (FA). A computational experimental design is proposed to analyze the efficiency of the introduced strategy, and the solutions indicate that the developed approach could reduce the carbon footprint by up to 9.82%. The results motivate us to implement the proposed algorithm in the manufacturing industry to reduce the carbon footprint. [ABSTRACT FROM AUTHOR]

The paper presents different types of materials and methods for wood finishing, used to reproduce an antique appearance of wood. The aim of this research is to develop new recipes useful for furniture restoration or to manufacture new furniture with antique look. The experimental study presents a selection of recipes for transparent and opaque finishes. The special aging effects and imitations of finishes discovered on furniture belonging to cultural heritage were highlighted. All the substances and methods can be further used in the furniture restoration process, but also valorised on new pieces of antique-looking furniture. [ABSTRACT FROM AUTHOR]

Engineering changes (ECs) are inevitable for businesses due to increasing innovation, shorter lifecycles, technology and process improvements and cost reduction initiatives. The ECs could propagate and cause further changes due to existing system dependencies, which can be challenging. Hence, change management (CM) is a relevant discipline, which aims to reduce the impact of changes. EC assessment methods form the basis of CM that support in assessing system dependencies and the impact of changes. However, understanding of which factors influence the changeability across value chains (VCs) is limited. This research adopted a VC approach to EC assessment. Dependencies in products and processes were captured, followed by risk (i.e. likelihood x impact) assessment of ECs using change prediction method (CPM). Four industrial case studies were conducted (3x automotive, 1x furniture manufacturing) to identify design (product) and manufacturing (process) elements with high risk to be affected by ECs. Based on the case results, characteristics were identified that influence changeability across VC. This contributed to the CM domain while businesses could also use the results to assess ECs across VC, and improve the design of products and processes by increasing their changeability across VC e.g. by proactive decoupling or reactive handling of system dependencies. [ABSTRACT FROM AUTHOR]

Plywood is a wood-based composite with many applications in construction, shipbuilding, and furniture production. One of the basic plywood processing and mandatory operations is drilling. Up to now, considerable and very diverse thematic research has been recently carried out on drilling, but little of that deals with modeling of the drilling process of plywood. Therefore, in this work, the artificial neural network modeling technique and response surface methodology were applied to model and optimize the drilling process of plywood. Two artificial neural network models were developed to predict the thrust force and the drilling torque based on drill tip angle, tooth bite, and drill type. The developed ANN models were used to complete the value of responses in the experimental design, which was requested by the response surface methodology. The trust force during the drilling of plywood is significantly influenced by the drill type (helical or flat). The most significant factor that affects the drilling torque during the drilling of plywood is the tooth bite. A helical drill assures a lower minimum thrust force and drilling torque than a flat drill. The proposed method could be used as an optimization tool during the design phase of the furniture manufacturing process. [ABSTRACT FROM AUTHOR]

Corporate image represents the positive or negative perceptions of internal and external stakeholders about a company. Corporate commercials play an important role in creating a good corporate image, which is essential for furniture manufacturing businesses to compete in the global market. In this regard, the aim of this study is to examine the corporate image of different furniture manufacturing businesses from the perspective of commercial films through personification analogies. The sample of the research consisted of the corporate commercial films of 10 furniture manufacturers with dealership systems in Türkiye. The Corporate Character Scale developed by Davies et al. (2004), which measures the image evaluations of both internal and external stakeholders through personification, was used in the study. The visuals generally used in these commercials portray similar themes, such as "Agreeableness", "Chic" and "Enterprise". In this regard, it was observed that image-building practices in the commercials of furniture manufacturing businesses were neither distinctive nor remarkable. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency and success rate of RV furniture manufacturing, the study of RV furniture CMF design database provided new design ideas and methods. Based on the CMF design theory, the analysis and interpretation of the design elements were carried out to assist the designer to better determine the design direction from the perspective of color, material and process, and to focus on the database structure and application of the RV furniture CMF design by establishing key technologies for the database strategy analysis. The effects of CMF design elements on product perceived quality, product aesthetics and emotional attributes, user needs and perception were obtained, and a caravan furniture database including CMF semantic library, theme style, business data and index data was constructed. The database included four levels of models, which provided accurate, reliable, clear and objective data support for the design of RV furniture, greatly shortened the design cycle of target furniture, improved the satisfaction rate of users and the actual production efficiency of the enterprise, from the direction of scientificity and feasibility. Meanwhile, this study provided applied strategies for database research and application. [ABSTRACT FROM AUTHOR]

Although China's bamboo resources rank first in the world, the added value of the industry has not yet reached the world's advanced level. By studying the current situation of China's bamboo industry and seeking breakthroughs in processing technology and design methods, the development of China's bamboo industry can be promoted. In order to meet the more innovative design scheme of the bamboo furniture market, thin bamboo winding technology was introduced as the technical support of new bamboo furniture. The raw material was green and environmental-friendly, which could also increase the production efficiency. Meanwhile, the parametric plug-in Grassshopper with Rinoceros as the carrier were chosen as the design platform, which were then used to generate bamboo furniture shapes. On this basis, the preliminary methods of manufacturing the thin bamboo wrapping process in the field of furniture and combined with parameterized design were summarized, and the production and design of the "ENTANGLED BAMBOO" seat was completed. Practice has proved that the combination of thin bamboo winding technology and parametric modeling technology can expand the use of parametric design in the design and manufacturing of bamboo furniture. [ABSTRACT FROM AUTHOR]

The relationship between the sustainable supply chain practice and firm performance has attracted interest from scholars and industry owners in recent years. On this basis, a model for sustainable supply chain management (SCM) in Iranian Wood Furniture Industry was developed and used to improve the performance of home and office furniture manufacturing companies. The statistical population of the qualitative part consisted of experts and specialists of sustainable SCM, and purposive non-random sampling was used. A structural equation modeling was used in the inferential and quantitative part through Lisrel-v8.8 software. The study identified economic, environmental, and social factors as underlying dimensions of SSCM. It also identified the components of customer satisfaction, financial and market performance as performance components. The results revealed that the path coefficient of SSCM to performance was 0.90. As the t-statistic was 18.07, it was confirmed at 99% level. So, in Iranian wood furniture industry, SSCM has a statistically significant impact on firm performance. Several factors such as strategies, backgrounds, and intervening factors were considered in the final model. The study has significant practical implications for industrial managers and government policy makers in the furniture industry. [ABSTRACT FROM AUTHOR]