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Paper dusting has recently been recognized as a significant issue in the hygiene tissue industry. This review considers the factors that may contribute to dusting and linting, as well as the challenges of evaluating dusting propensity. Examining both the paper and textile industries, several methods of dusting and linting assessment exist. This review describes the equipment, methodologies, targeted paper grades or materials, advantages, and disadvantages. Standards (if applicable) are also covered for each of the major methods. These existing methods were found to have various drawbacks, suggesting a need for an improved, standardized method and device. In conclusion, and to motivate future research, mechanisms of dust release are reviewed along with existing and possible solutions to combat the tissue-dusting problem. This paper outlines the importance of creating a repeatable, standard, and accurate testing procedure and methodology for dust particle characterization in the hygiene tissue industry. [ABSTRACT FROM AUTHOR]

Manual repair tasks in the industry of maintenance, repair, and overhaul require experience and object-specific information. Today, many of these repair tasks are still performed and documented with inefficient paper documents. Cognitive assistance systems have the potential to reduce costs, errors, and mental workload by providing all required information digitally. In this case study, we present an assistance system for object-specific repair tasks for turbine blades. The assistance system provides digital work instructions and uses augmented reality to display spatial information. In a user study with ten experienced metalworkers performing a familiar repair task, we compare time to task completion, subjective workload, and system usability of the new assistance system to their established paper-based workflow. All participants stated that they preferred the assistance system over the paper documents. The results of the study show that the manual repair task can be completed 21% faster and with a 26% lower perceived workload using the assistance system. [ABSTRACT FROM AUTHOR]

Origami techniques derived from antique paper folding arts have been applied to solve engineering problems such as weight/space-saving structures and their rapid deployment for foldability. Recently, origami techniques' potential in mechanical reinforcement for structural designs has also been discussed. For example, the mechanical performance of origami tubular structures can be significantly improved compared with the circular and hexagonal tubes under lateral loading. In this paper, an origami-inspired tubular structure was applied as the infill pattern for additive manufacturing, and energy absorption performance under dynamic and static loadings was investigated. Fused filament fabrication was selected as the testbed for the origami-inspired infill pattern investigation. The samples with the origami infill pattern presented higher dynamic and quasi-static energy absorption performance than samples with grid or honeycomb infill patterns. The proposed structural reinforcement method can be expanded to crash-worthy structures, thin-wall structures, functional structures, and the design of lightweight, high-strength parts. [ABSTRACT FROM AUTHOR]

In the present analysis, a new experimental pilot plant system for exploring resin-impregnated paper (RIP) bushing technology was conducted. Experimental and numerical studies were carried out on the resin infusion and impregnation processes in the paper condenser core of a RIP bushing. An innovative approach for the molding process (named molding method B) of a commercial RIP bushing was implemented. For this method, the homogeneity of the paper winding process was controlled precisely. The filling process was conducted by gravity due to the difference of heights between two vacuumed chambers and from bottom to top in the mold. The flow front position and infusion time were measured experimentally and used to obtain the axial permeability of the paper condenser core analytically and numerically. The results indicate that the molding methods have a significant effect on the RIP bushing quality, homogeneous filling, and impregnating process time. Also, it was found that homogeneity of the paper winding process and, consequently, uniform axial velocity of resin flow in the radial direction is the most effective factor to eject the air. Finally, it was recognized that the determination of axial permeability in the case of transient flow is novel in comparison with conventional procedures such as Darcy relation of steady flows. By decreasing the paper thickness from 0.3 to 0.2 mm, the permeability decreased from 8.84 × 10−10 to 4.52 × 10−10 m2. The microstructure of the core illustrates that the axial permeability of the crepe paper condenser core is considerably affected by the variation of the paper thickness. [ABSTRACT FROM AUTHOR]

The paper industry manufactures corrugated cardboard packaging, which is unassembled and stacked on pallets to be supplied to its customers. Human operators usually classify these pallets according to the physical features of the cardboard packaging. This process can be slow, causing congestion on the production line. To optimise the logistics of this process, we propose a visual recognition and tracking pipeline that monitors the palletised packaging while it is moving inside the factory on roller conveyors. Our pipeline has a two-stage architecture composed of Convolutional Neural Networks, one for oriented pallet detection and recognition, and another with which to track identified pallets. We carried out an extensive study using different methods for the pallet detection and tracking tasks and discovered that the oriented object detection approach was the most suitable. Our proposal recognises and tracks different configurations and visual appearance of palletised packaging, providing statistical data in real time with which to assist human operators in decision-making. We tested the precision-performance of the system at the Smurfit Kappa facilities. Our proposal attained an Average Precision (AP) of 0.93 at 14 Frames Per Second (FPS), losing only 1% of detections. Our system is, therefore, able to optimise and speed up the process of logistic distribution. [ABSTRACT FROM AUTHOR]

In high-speed milling, the machining system is affected by a chatter resulting from the dynamic interaction between the tool and the part, which can cause harmful effects on the tool and the machined surface of the part. Chatter occurs more frequently for the milling of thin-walled parts due to their low stiffness. In addition, the dynamic characteristics of thin-walled parts vary along the tool path. The dynamics of the part are therefore the dominant factor that should be considered in the modeling and the study of the milling process and must be performed in 3D, where the third dimension is the tool position. This paper studies the milling stability of Al 7075-T6 thin-walled parts during high-speed milling considering the variation of dynamic characteristics and develops three-dimensional stability lobe diagrams of the spindle speed, axial depth of cut, and tool position. The dynamic equations of motion are solved numerically using semi-discretization method. Modal parameters of the tool and the part were extracted experimentally by modal tests. Then, cutting tests were conducted to validate the established model by measuring the machined surface roughness which is used as a criterion for detecting instability. The experimentally obtained results correspond well with the predicted stability limits. Moreover, the influence of different cutting parameters on the machining stability along the tool path was investigated. It is found that the variable spindle speed improves significantly the cutting process, and the best selection of feed per tooth impacts positively on the machined surface quality. [ABSTRACT FROM AUTHOR]

Smart structures of 4D printing are perhaps interdisciplinary research area with significant development and applicability future. The cornerstone of 4D printing is smart materials. When a stimulus is put in front of this structure, it changes into a different structure. This article initially provides a succinct insight of the aforementioned 4DP: SMs-SSs: 4D printing (4DP) technology imminent enlargements of smart material's (SMs) prospective to physique smart structure (SSs). Investigation into 4D printing has pulled in phenomenal enthusiasm. The research work of 4DP: SMs-SSs has stimulated promising future. The paper discusses smart materials and their potential towards mainstream 4D printing for smart constructions (4DP: SMs-SSs). Cursory research write-up on smart materials associated 4D printing approaches to process them based on adaptability to stimuli, fabrication, control mechanisms, multi physics modeling, and existing as well as emerging functionalities. Indeed, innovative structural initiatives could perhaps inspire new paradigms for stimulate positive structures. Novelty structures are being thoroughly researched, and new ideas will be incorporated. Programmability, reactivity toward and adaptability to their circumstances, and automation are all functionality of 4D-printed items. The article's conclusion is that 4DP: SMs that can create intelligent/smart structures (SSs) will even trigger a massive era of construction material. This article shows an insight into how quickly technology is changing, how some researchers and scholars are figuring out what it can do, and how engineers could use the ideas. The adoption of smart materials will assist in resolving the problem to a greater extent. 4D printing relies on shape memory alloys/polymers (SMAs/SMPs) as so forth organic materials. Imminent enlargements of smart materials prospective to physique smart structures are still being experimented with by scientists and engineers. [ABSTRACT FROM AUTHOR]

This paper investigated the cutting behaviors and chip formation in machining of carbon fiber reinforced polymer (CFRP) composites. The single cutting edge and unidirectional (UD) laminates of six different fiber orientations from 0° to 150° with an interval of 30° were employed in the orthogonal cutting test. The effects of fiber cutting angle, cutting speed and cutting depth on cutting mechanism and micro-damage evolution were estimated. Cutting force and thrust force obtained by dynamometer were used to evaluate the interaction between the tool and the workpiece. Subsurface damage was assessed by damage depth and failure mode of microstructure such as fiber and matrix. The machined surface roughness was used to characterize the machined surface quality. The results indicated that the average cutting force at θ > 90° was 7.58 times higher than that at θ < 90° and large deformed fibers below the machined surface existed elasticity recovery in the former case. The cutting speed and cutting depth had the most significant effects on the cutting force at θ = 90° where the fiber bending deformation and fiber kinking keep cutting force at a high level. The micromorphology of machined surface and subsurface revealed four typical cutting mechanisms, namely, interface-debonding, fracture-sliding, shearing-fracture, and bending-fracture in the range of θ = 0 ~ 180°. The variation trend of surface roughness with cutting parameters at θ > 90° is obvious and in consistent with that of cutting force. The most efficient factor on the roughness is found to be the fiber cutting angle accounting for 98.60%, followed by the cutting depth (0.55%) and cutting speed (0.25%). The interaction between the factors is not significant according to the results of ANOVA. [ABSTRACT FROM AUTHOR]

In this paper, a non-supervised technique for on-line paper characterisation is presented. The method uses self-organising maps (SOM) and texture analysis for clustering different kinds of paper according to their properties. A light-through technique is used to get pictures of paper. Then, effective texture features are extracted from greyscale images and the dimensionality of the feature data is reduced with SOM allowing visual analysis of measurements. The method makes it possible to implicitly extract important information about paper formation. The approach provides excellent results. A classification error below 1% was achieved for four quality classes when local binary pattern (LBP) texture features were used. The improvement to the previously used texture features in paper inspection is huge: the classification error was reduced by over 40 times. In addition to the excellent classification accuracy, the method also offers a self-intuitive user interface and a synthetic view of the inspected data. [ABSTRACT FROM AUTHOR]

The process of complex product assembly-commissioning has the characteristics of high flexibility and firm dynamics. To overcome the drawbacks of manual assembly, deploying automated and intelligent techniques can greatly boost efficiency, improve flexibility, and enhance the quality control. The human–robot collaborative (HRC) technology combines the advantages of human capabilities and the efficiency and precision of robots. However, current HRC technology lacks of perception and cognitive ability, especially in dynamic environments. Therefore, this paper proposed a digital twin-driven HRC assembly-commissioning framework. In this framework, a virtual-physical mapping environment for HRC is constructed. In order to improve the cognitive ability of robot units to tasks, a motion intention recognition approach is proposed which integrates the feature of part into human joint sequences. To improve the adaptability of the robot unit to tasks, the assembly-commissioning task knowledge graph is developed to extract the action sequence of the robot unit in a timely manner. Moreover, the deep deterministic policy gradient (DDPG) is used to adaptively adjust the robot unit movement path in the process of assembly-commissioning. Finally, the effectiveness of the proposed method is verified by taking a particular type of automobile generator as a case study product. [ABSTRACT FROM AUTHOR]

The contact angle (CA) of a water droplet on the polished aluminum surfaces is usually between 60° and 90°. This paper discusses a tuned bulk micro-manufacturing approach for transforming the surface topology of aluminum simultaneously at the micro- and nano-length scales, thereby significantly influencing its wetting characteristics. The approach is cheap, easy to implement, and scalable. The treated aluminum surfaces appeared like roughly polished surfaces at the macroscale and were found to be robust and non-toxic. They exhibited a paper towel effect by showing extreme surface wettability (CA of zero) to many industrial liquids, i.e., wetting on these surfaces is only a function of the surface roughness but not the fluid type. This extreme wetting ability to multiple liquids (or ultra-omniphilicity) was generated by sequentially creating a sub-surface micro- and nano-cavity architecture with nano-cavities within the embryos of micro-cavities interconnected by a network of micro-grooves. [ABSTRACT FROM AUTHOR]

Nanocutting is a method of direct machining in nanomanufacturing field, and it is an important ultraprecision machining method. Nanocutting technology adopts single-point diamond cutting and nanoprobe scratching methods to make the machining accuracy of parts reach the nanometric scale. It is the method with the highest machining accuracy at present, so it is widely used in the processing of precision components. At the same time, nanocutting technology can be used to process nanostructures and provide processing methods for basic research in condensed matter physics. This paper summarized the cutting mechanism and cutting force in the nanocutting process, including the mechanism of nanocutting and brittle–ductile transition. The influence of RTS, temperature, wear and subsurface phase transformation on cutting performance is also discussed. At the same time, the characteristics of cutting force and friction coefficient during the cutting process are reviewed. After that, the simulation and experiment research of the nanocutting process are analyzed. At the end of the paper, the challenges and prospects of nanocutting technology are proposed and summarized. [ABSTRACT FROM AUTHOR]

Tool wear is unavoidable during machining, which is one of the most common tool failure modes. It is significant to evaluate the tool state quickly and effectively for timely tool change strategy. The cutting vibration signals after tool wear show strong non-Gaussian characteristics. Higher order spectrum is a powerful tool for analyzing the non-Gaussian characteristics of signals, and can restrain noise and provide more information than classical power spectrum analysis. This paper presents a milling tool wear state monitoring method based on higher order spectrum entropy. Due to the large amount of calculation of bispectrum, bispectrum diagonal slice is investigated. And the diagonal slice spectral entropy is proposed as tool wear indicator to monitor tool state. To verify the proposed method, cutting vibration signal of CNC machining center were collected and analyzed. The experimental results showed that the proposed approach can effectively monitor and diagnose the tool state, and has good robustness. It is feasible and effective for online monitoring milling tool wear. [ABSTRACT FROM AUTHOR]

Freehand sketch is a natural and intuitive communication channel for idea expression. Lines are drawn one after another to create the outline before additional lines are often drawn over the existing ones to make a sketch clearer. Typically, the sketch is transformed to be a 3D CAD model by a designer for use in subsequent operations. Sketch-based modeling has been researched to support this transformation but mainly for an online sketch on a digital device. For an offline sketch on a paper, commonly found used in practice, sketch-based modeling remains a challenge because a scanned image conceals enriched information on the sketch in a batch of data points. This paper proposes an approach for reconstructing a 3D model from a paper-based overtraced freehand sketch. Two main modules in this approach are single-line drawing identification and 3D reconstruction. The first module where image processing technique is applied is for transforming a paper-based overtraced freehand sketch to be a single-line drawing in order to generate more information about the sketch (i.e., the number of lines and their starting points and endpoints). The second module where progressive reconstruction approach with cubic corner is applied is for reconstructing a 3D model from the obtained single-line drawing. Steps to be taken in both modules have been formalized. The approach has been successfully implemented on LabVIEW, and tested with several samples. [ABSTRACT FROM AUTHOR]

Faced with the global crisis of COVID-19 and the strong increase in customer demands, competition is becoming more intense between companies, on the one hand, and supply chains on the other. This competition has led to the development of new strategies to manage demand and increase market share. Among these strategies are the growing interest in sustainable manufacturing and the need for customizable products that create an increasingly complex manufacturing environment. Sustainable manufacturing and the need for customizable products create an environment of increased competition and constant change. Indeed, companies are trying to establish more flexible and agile manufacturing systems through several systems of reconfiguration. Reconfiguration contributes to an extension of the manufacturing system's life cycle by modifying its physical, organizational and IT characteristics according to the changing market conditions. Due to the rapid development of new information technology (such as IoT, Big Data analytics, cyber-physical systems, cloud computing and artificial intelligence), digital twins have become intensively used in smart manufacturing. This paper proposes a digital twin design and simulation model for reconfigurable manufacturing systems (RMSs). [ABSTRACT FROM AUTHOR]

Milling force during machining process has strong time-varying and multi-frequency characteristic, which is easy to cause tool vibration, wear, and cutting chatter, and even lead the machining accuracy of parts to be out of tolerance. The paper proposed a milling force prediction method for a general helix cutter during peripheral milling. In this model, the geometric parameters of milling cutter are parametric defined, and then an analytical instantaneous uncut chip thickness (IUCT) model is presented with taking cutter runout (offset and inclination) and geometric entity shape of workpiece into account. A series of milling experiments using aluminum alloy were carried out with six kinds of milling cutters in a high-speed machining center. The analysis results show that the predicted value of milling force can better reflect the change trend of the actual measured one, and well prove the validity of the presented method. Furthermore, the influences of milling parameters, cutter runout, milling type, cutter tooth number, and unequal spacing angle on the time domain and frequency domain excitation characteristics of milling force are systematically analyzed, which can provide useful guidance for the tool design and machining parameter selection in the future. [ABSTRACT FROM AUTHOR]

The kraft manufacturing process is the main pulping process in the paper industry. The kraft chemical recovery process is an efficient technology that enables the recycling of the pulping chemicals and the generation of electrical power. However, this process presents substantial issues related to energy consumption and environmental emissions. One of the main fundamental elements of the kraft process is the lime kiln. Lime kiln gas consumption, SO2, and NOx air emissions are key factors from the energy saving point of view (i.e., energy efficiency) and environmental pollution in this industrial process, respectively. Knowledge of the process variables involved in a lime kiln and how these are related to gas consumption and air emissions is essential to predict the kiln's behavior and minimize its environmental effects. The aim of this research study is to build a regression model for each one of the three prime variables (gas consumption, SO2, and NOx emissions) of a lime kiln employed in the paper manufacturing process using the multivariate adaptive regression splines (MARS) method in combination with the artificial bee colony (ABC) technique. These two statistical learning techniques were combined, thereby obtaining an easy-to-interpret mathematical model with a high goodness-of-fit. A coefficient of determination greater than 0.9 is obtained for all the modeled variables. Moreover, the particular contribution or importance of the input variables in each model is also calculated. The results thus obtained are a useful instrument to gain a better understanding of the dynamics of the lime kiln and the involvement of the process variables in gas consumption and gas emissions. [ABSTRACT FROM AUTHOR]

The global trend in manufacturing has shifted from a manufacturing-centric process toward a user-centric process. This has resulted in a shorter lifespan and a high product replacement rate of any consumer product. Germany has introduced the concept of Industry Revolution 4.0 (IR 4.0) to convert manufacturing processes and mechanisms into cyber-physical systems (CPS). Digital factory, being the first step into CPS and IR4.0, is being targeted as the most important evolution of the manufacturing industry. This paper defines digital factories and their differences between other similar domains such as smart factories, CPS, and virtual factories. The requirements and goals of a digital factory are explained in detail to facilitate future digital factory tool developments. Furthermore, the current challenges faced in the implementation of the digital factory are proposed to be approached by adapting an interoperable virtual reality technology. This paper emphasizes the usage of virtual reality (VR) in simulating a digital factory that aids in the decision-making and efficient operation of a manufacturing facility. Furthermore, recommendations gathered from previous studies for developing VR-based digital factory tools are also explained in detail in this paper. [ABSTRACT FROM AUTHOR]

Based on the proposed model, a multi-objective optimization framework is presented to optimize the feed rate with the objective of increasing the machining efficiency and the loading stability of the spindle. The in-process machining data generated in the machining process is calculated and aligned for building the data-based model of spindle power, and an artificial neural network (ANN)-based modeling approach is proposed for the spindle power. To validate the feasibility and advantage of the proposed methods, a set of machining experiments are conducted, showing that our proposed ANN-based model has good accuracy in terms of predicting the spindle power, as well as that the feed rate optimization framework as solved based on the multi-objective evolutionary algorithm based on decomposition (MOEA/D) can effectively improve the machining efficiency and reduce the fluctuation of spindle power. [Extracted from the article]

Freehand sketching on a paper is commonly found to be used as it is a natural and intuitive communication channel for portraying ideas. Additional strokes are often drawn over the existing ones to make the sketch clearer. For its usefulness in subsequent steps, a sketch is transformed to be a 3D CAD model that is typically performed manually by a designer due to a lack of technology support. Geometrical reconstruction from an offline scanning of a sketch has been a challenge because enriched information obtained during sketching is reduced to a batch of data points. This paper presents an algorithm for identifying a single-line drawing from a paper-based overtraced sketch as it is the first important step towards geometrical reconstruction. Key activities in this approach are thick-line sketch creation, contour boundary extraction, segments identification, and line drawing creation. The algorithm has been successfully implemented on LabVIEW and tested with several samples. [ABSTRACT FROM AUTHOR]