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According to the increase in building size and lack of skilled laborers, layout operation has high demands on automation for productivity and quality improvement. With such a background, research has been recently undertaken to develop an automated layout system based on marking robots for structural work in Korea. Although there are several robot-based automation systems under development targeted at interior works, the system for structural work has different functional needs and technical requirements in designing the robots compared with the existing ones. Therefore, this study proposes a conceptual robot design for an automated layout of building structures, based on a systematic design process, by integrating quality function deployment (QFD) and the theory of creative problem solving (TRIZ). With the support of the approach, 11 user requirements and 16 relevant technical characteristics were derived and prioritized, and 15 creative ideas were derived to solve the technical contradictions. The selected design solution improves driving speed by separating driving and marking operations, and the two-wheeled steering drive system with a suspension device allows easier driving control in a narrow and uneven driving environment. The noncontact type of printer head also minimizes the complexity of the device and provides excellent performance in securing marking precision and quality in response to floor conditions. The results of this study will be used for the detailed design of the layout robot system, and the design process can be utilized for designing and evaluating other construction robots and automation systems.

In this paper, a CAD integrated method is proposed for automatic recognition of potential weld locations in large assembly structures predominantly comprised of weld joints. The intention is to reduce the total man-hours spent on manually locating, assigning, and maintaining weld-related information throughout the product life cycle. The method utilizes spatial analysis of extracted stereolithographic data in combination with available CAD functions to determine whether the accessibility surrounding a given intersection edge is sufficient for welding. To demonstrate the method, a system is developed in Siemens NX using their NXOpen Python API. The paper presents the application of the method to real-life use cases in varying complexity in cooperation with industrial partners. The system is able to correctly recognize almost all weld lines for the parts considered within a few minutes. Some exceptions are known for particular intersection lines located deep within notched joints and geometries weldable through sequential assembly, which are left as a subject to further works.

Manual surface inspection methods performed by quality inspectors do not satisfy the continuously increasing quality standards of industrial manufacturing processes. Machine vision provides a solution by using an automated visual inspection (AVI) system to perform quality inspection and remove defective products. Numerous studies and works have been conducted on surface inspection algorithms. With the advent of deep learning, a number of new algorithms have been developed for better inspection. In this paper, the state-of-the-art in surface defect inspection using deep learning is presented. In particular, we focus on the inspection of industrial products in semiconductor, steel, and fabric manufacturing processes. This work makes three contributions. First, we present the prior literature reviews on vision-based surface defect inspection and analyze the recent AVI-related hardware and software. Second, we review traditional surface defect inspection algorithms including statistical methods, spectral methods, model-based methods, and learning-based methods. Third, we investigate recent advances in deep learning-based inspection algorithms and present their applications in the steel, fabric, and semiconductor industries. Furthermore, we provide information on publicly available datasets containing surface image samples to facilitate the research on deep learning-based surface inspection.

Advanced manufacturing in the context of the digital thread has mainly focused on process information related to the integration of machining processes, tools, operations, and specific manufacturing parameters. However, no unified information model has been developed to represent specific manufacturing process in 3D printing. This work therefore proposes a STEP/STEP-NC-compliant process data model to define specific application objects and entities, to model manufacturing data relationships and constraints, and to standardize process parameters through extended 3D printing concepts in fused deposition modelling (FDM). This data model describes manufacturing layers, deposition operations and process parameters in the context of the digital thread. As a special feature, manufacturing layers provide geometric information to layered operations based on STEP/STEP-NC standards for additive manufacturing (AM). Deposition operations specify the definitions of print devices or headers, header paths, FDM technology and functions, and even deposition strategy. Process parameters mainly provide process information in the FDM process. Finally, a conformance testing process is developed, focussed on manufacturing layers and header paths and by means of information exchange.

As main welded components of the rail vehicle, the railcar frames have specific needs in preparing a suitable welding document for each welded joint to guide the welding process during the manufacturing process. In this paper, the expert system and database technology are introduced into the field of rail vehicle welding process preparation, and a knowledge-based software for railcar frame welding process is developed. This system could maintain the normal operation of the enterprise rail welding system based on knowledge base and database. The numerous paper-based and fragmented electronic documents are stored in a unified format within the system’s database, and a reasoning mechanism based on Rule-Based Reasoning (RBR) and Case-Based Reasoning (CBR) is designed to intelligently match the welding procedure specification (WPS) and welding procedure qualification report (WPQR) online. Furthermore, the system supports multiple departments and personnel by integrating the function of workflow to carry out the WPS prepare and review process. Thousands of welded joints with various structures and complex positions in the same vehicle body can be aggregated into a welding summary table to reduce the repeated welding procedure qualifications (WPQ) of the same or similar welding joint. This method not only saves manpower and resources, but also ensures the accuracy of these process documents. In the end, the future development trend of this kind of application software is prospected.

Continuous 3+2-axis additive manufacturing (AM) is an emerging AM technology that overcomes the signature problems of the need of support structures and the staircase effect of the traditional 3-axis AM. This paper presents a novel process planning framework for automatically generating a multi-axis support-free printing path for continuous 3+2-axis AM of an arbitrary freeform part. The framework is based on the geometric processing of skeletonization and decomposition and is particularly suitable for a part with distinct multiple trunk-branch structures. The physical printing experimental results carried out by the authors indicate that the proposed framework has performed well and fabricated some challenging models with large overhangs and twisty spatial topologies.

Offsite construction shifts construction work to the factory environment, enabling automation of traditionally manual operations. While this approach has proven to be advantageous for the construction industry in Canada, changes in the process of manufacturing panelized walls have brought new challenges and opportunities. With the aim of providing alternatives to current manual quality control activities, an automated vision-based online inspection system for screw-fastening operations in light-gauge steel frame manufacturing is proposed in this paper. Targeting two common defects in the framing process, squareness and the quality of the screw-fastening operation itself, real-time quality assessment of the frame is achieved. The proposed system uses novel machine vision algorithms to generate the inspection data: a squareness estimation algorithm is developed, based on edge detection and the Hough transform, that can determine the squareness of a steel connection with a margin of error less than two degrees, whereas a R-CNN is designed based on a pre-trained ResNet-50 for detection and classification of screw-fastening operations, achieving an overall accuracy of 91.67%. All the inspection results are made accessible through a Python-based interface in order to direct operators towards either identifying potential quality issues or confirming the quality of the product leaving the station. The inspection system is validated over a real frame in a semi-automated machine environment. In future work, the inspection system will be deployed in continuous production setups in order to further test its accuracy and applicability.

Hyperboloidal-type normal circular-arc gears (HNCGs) are a latest application of circular-arc tooth profile in the gearing with perpendicular non-intersection axes, and the existing software programs provided by the original equipment manufacturers (OEMs) for specific machine tools cannot yet directly support the manufacture of HNCGs. In this paper, a dimension-driven adaptive programming methodology is proposed to automatically carry out the tool-path planning and generate the G-code file for the form milling of HNCGs on general 5-axis CNC machine tools. Based on the mathematical model of tooth surface, the basic strategy for 5-axis form milling of tooth is presented, an interference-free tool path considering both roughing and finishing operations is planned, and furthermore, the tool-path data is transformed to achieve the machine tool coordinates. To quickly respond to the changes of design and machining parameters, a dimension-driven adaptive programming software package is developed to automatically compute the tool path, conduct the post-processing, and generate the G-codes for 5-axis form milling of HNCGs with different specifications, and example verification is carried out to demonstrate the validity of the proposed method.

Agile joint jig (AJJ) is a novel and promising reconfigurable assembly jig, which is put forward to deal with the disadvantages of traditional dedicated assembly jig in aerospace industry. For AJJ design, it is under the combined influence of aircraft product and assembly process requirements, especially the experience and knowledge of designers. Although case-based reasoning (CBR) gives the possibility to make fixture design more efficiently, this method has its weakness that the most similar case maybe is not the optimal selection and the designers still depend on their knowledge to determine what changes need to be made and how these changes can be achieved. In order to lower the requirement for designers’ skills and enhance the AJJ design efficiency, this paper presents an intelligent configuration method based on smart composite jig model (SCJM). Firstly, the concept and definition of SCJM are presented. It is not only a generic assembly jig architecture for a certain aircraft product family but also appends information and knowledge through MBD (model-based definition). Secondly, the requirement information model including product general information and assembly process information and so on is established with MBD for driving AJJ design automatically. Based on the above models, the intelligent configuration method for AJJ is proposed and realized by combing auto-selection reasoning with auto-assembly reasoning. The auto-selection reasoning is to achieve that the standardized components are selected actively by matching attributes between SCJM and product model. The auto-assembly reasoning is to automatically assemble the selected components in terms of the typical constraint relationships. By these ways, the SCJM can perceive the product assembly requirements by itself and then achieve appropriate design automatically. Finally, a computer-aided system for intelligent design of airplane assembly jig was developed. The results indicated that the proposed methods are able to significantly improve the design efficiency and quality of reconfigurable assembly jig.

Stereolithography (SLA)-based three-dimensional (3D) printing is widely used in both industrial and consumer markets for prototyping and concept validation. It also plays an important role in aircraft industry as it offers advantages in surface finish and high precision. Despite the extensive usage, the combination of large volume, high resolution, and high speed is hard to achieve. This paper presents a 3D printing technology that allows a UV projector to continuously cure resin while scanning over the build area. To print large objects, 3D models are sliced into layer-by-layer, high-resolution image “maps”. Each “map” is further divided into sub-region images that are dynamically exposed to the photocurable materials and synchronized with the scanning of the projector, causing a still exposure pattern to appear on the build area. Therefore, large objects with delicate details can be printed layer-by-layer. As such, customized build volumes on a large scale (greater than 1 m3) can be achieved with micro-scale features. Along with a wiping system, this technique is compatible with various materials, leading to the direct manufacturing of final parts from photocurable materials. Furthermore, this technique shows advantages over existing large-scale DLP printing methods regarding both printing speed and material flexural properties. This technique can be implemented at design workflow in the aerospacing industry by facilitating design communication, validation, pre-production, and even assisting in producing final parts.

Although 3D printing was invented in 1984, it was not until recent years that it captured the imagination of everyone from industry experts to at-home hobbyists. Three-dimensional printing, also known as additive manufacturing or rapid prototyping, constructs an object by accumulating materials layer by layer. In recent years, 3D printing technology has been dramatically developed with respect to materials, printer, and process, which laid a foundation for 4D printing. Four-dimensional printing is the targeted evolution of the 3D-printed structure, concerning shape, property, and functionality. The object is produced by 3D printing firstly. Then, the object can self-deform, self-assemble, self-disassemble, self-repair, and change property or functionality over time when the external stimuli are imposed on it. This review mainly introduces the stimulus, types of shape-shifting behaviors, mechanisms of deformation, and applications of 4D printing.

This paper describes an Augmented Reality system for the improvement of the manufacturing process in the packaging sector. It presents a successful use case of how to integrate the Augmented Reality technology in a factory shop floor by providing a tool that helps operators in their daily work. Given a product reference, the proposed system digitizes the setting of the die cutter automatically from an image and stores it in a database to subsequently consult and analyze. Furthermore, the content display is not carried out as a conventional Augmented Reality system (wearable devices such as glasses or mobile), but projecting directly on the workspace to facilitate its interpretation. Compared to the current workflow, where the data is recorded on sheets of paper and stored physically in warehouses, the proposed system offers several advantages such as preventing data loss, reducing costs, or the possibility of increasing knowledge from the post-processing of digitized data.

Milling freeform surfaces using a STEP-compliant CNC machine tool highly reflect the intelligence of STEP-NC, especially when the toolpaths can be generated and adjusted online. However, in contrast to the 2.5D manufacturing features, there are very seldom entities defined in the standard ISO 14649-11 for milling freeform surfaces. Basically, there are only four freeform strategies used for finish milling a freeform surface, and no roughing operations are provided for milling a freeform surface from a raw piece to the shape before the (semi-)finishing operation. Obviously, both of the rough and finish operations are fundamental to machine a freeform surface from the raw piece. This paper extends the EXPRESS definitions for rough milling freeform surfaces, so as to enrich the related operations. Both 2.5D and freeform operations are improved, and individual operations, strategies, and technologies are added to fulfill the need of 2.5D and freeform roughing tasks respectively. The related online toolpath generation algorithms are developed and integrated into a STEP-CNC prototype. The STEP-CNC system is equipped to a three-axis machine tool and finally drives the machine tool to cut a T-spline surface.

In order to take the advantages of the double-sided incremental forming (DSIF) that can freely switch the pressing and supporting functions of the two tools and realize the forming of the sheet parts with protruding features in both the positive and negative directions of the sheet (the sheet part with bidirectional protruding feature), a method for the double-sided incremental forming based on the stereo lithographic (STL) model was proposed. The method first classifies the forming features according to the protruding direction and the position relationship of the model into the different types of the features to be formed. The main forming surface and the supporting surface are determined by the types of the forming features, and the pressing and supporting tasks of the main tool and slave tool heads are assigned. Then, the cutter location points of the main tool and slave tool are generated, and the toolpath of the main tool and slave tool are planned out according to the forming sequence and the forming methods of the different forming features. Finally, a method of the interference detection and correction between the forming tool head and the sheet part is proposed. The finite element numerical simulation and the forming experiments of the sheet part with bidirectional protruding features show that the proposed toolpath generation method for the DSIF is applicable; the DSIF toolpath generated based on the STL model can fabricate the sheet part with the bidirectional protruding feature.

For successful development of the intelligent manufacturing of freeform surfaces using STEP-CNC with online toolpath generation capability, it is required to make a choice of the optimal representation of a 3D model which will be used for machining. Traditionally, most existing CAD-CAM systems use NURBS to design freeform surfaces and to perform toolpath generation in order to machine them. The introduction of T-splines to CAD systems and some reported results of using them in manufacturing makes it possible to consider T-splines, or more generally T-NURCCs (Non-Uniform Rational Catmull-Clark Surfaces with T-junctions), as a good solution for the development of the STEP-NC-based manufacturing of freeform surfaces because of their advantages over NURBS. Therefore, this paper gives an overview of the main arguments in favor of choosing the T-spline surface representation for integration within STEP-CNC systems. We examine the prospects for T-splines to become an integral part of modern manufacturing systems, and highlight some important properties of T-splines which are the most beneficial for manufacturing processes. The paper presents the results of the development of a complete T-spline-enabled STEP-CNC system which can strategically support online toolpath generation for three-axis ball end machining of simple T-spline surfaces using four different freeform strategies defined in ISO 14649-11. These results represent the implementation of the first stage of the development process of intelligent STEP-CNC systems, and in the future more research is needed in this direction.

CNC systems with the vision function have become very valuable for intelligence machine tools because machine vision is a fast-growing intelligent feature for machines. A novel vision-oriented open CNC system was developed in this study and used in profile grinding machines for the precise machining of parts with contour surfaces, such as complex molds and cutting tools. The system is an innovation to the conventional profile grinding method and enabled the profile error to be visually detected and compensated during the machining process. In this study, a novel design methodology for a machine-vision-oriented CNC system was proposed. An Ethernet-based hardware architecture was constructed for the vision-oriented CNC system. The software characteristics of the developed CNC system were analyzed, including a new type of multi-thread software architecture, a seamless handover approach for multi-thread accessing of the memory space, the integration of the human-machine interface with image processing, and virtual-axis-based online error compensation. The running efficiency test of the software development platforms, time-consumption analysis of the measurement and control in the vision-oriented CNC system, and verification of the effectiveness of the developed vision-oriented CNC system were performed. The results indicate that the proposed vision-oriented open CNC system can effectively fuse image processing with motion control, meet the efficiency requirement, and improve the machining precision of profile grinding. The results are also valuable for developing other machine-vision-based intelligent machine tools.

Electrical discharge machining (EDM) is widely used in mold manufacturing to form the intricate geometric features which are difficult to be produced by the conventional machining process. Owing to the use of a large number of electrodes, the cost and time consumption for electrode design and NC programming has become a bottleneck in boosting productivity of mold enterprises. Although computer-aided design (CAD)/computer-aided manufacturing (CAM) systems are widely used, because of the complex shapes and diversity of electrodes, manual operations are commonly employed to generate process plans and tool paths for electrode manufacturing, which is cumbersome and error-prone. In order to realize the intelligent manufacturing of electrodes in such a knowledge-intensive domain, this paper presents a feature-based integration approach of CAD/computer-aided process planning (CAPP)/CAM. A hierarchical taxonomy of electrode features is introduced and a hybrid feature recognition method is proposed to build multi-level feature tree. Then, feature knowledge and domain know-how based process planning and optimization are achieved followed by automatic tool path generation which aim to machining the electrode precisely and economically. In the framework of system integration, a structured product model is established to capture and encapsulate geometric entities, machining features, technical information, process plans, and measurement data of machining error to realize seamless flow of information among CAD/CAPP/CAM systems. The effectiveness and efficiency of the proposed approach are demonstrated by case studies and industry implementation.

This paper explores a compound forming method of the cylindrical drawing by using the servo press forming combined with the electromagnetic pulse-assisted incremental drawing. The method comprises four steps: the punch press pre-drawing, electromagnetic pulse-assisted incremental drawing, punch shaping, and the final continuous punch drawing. By applying the four steps sequentially, the good drawing performance was achieved, and the maximum drawing height was of 3.4 times compared with that of the conventional punch drawing process, without changing the diameter of the punch. During the electromagnetic pulse-assisted incremental drawing process, the drawing coils, the corner coils, and the upper and bottom auxiliary coils generate the electromagnetic pulse force to help achieve the drawing of the metal sheet. The electromagnetic pulse-assisted incremental drawing step and the punch press deforming step were alternately carried out. In the electromagnetic pulse drawing step, by applying a two-time discharge using 13 and 14 kV in turn, the height of the drawing was improved, and the thinning rate of sheet metal was reduced. The application of the servo press and the computer numerical control system in the electromagnetic pulse-assisted incremental drawing process can effectively improve the processing efficiency and provides technical basis for the intelligent control of the electromagnetic pulse-assisted incremental drawing process.

A new machining method for lens molds using tilt electrical discharge milling (ED milling) has been experimentally investigated. Compared with the conventional ED milling, the tilt ED milling enables efficient enlargement of discharge gap by adjusting the tilt angles of the workpiece which results in efficient chip removal and burnish surface quality. On account of this method, micro lens craters were fabricated on the tungsten carbide (WC) and silicon carbide particulate reinforced aluminum metal matrix composite (SiCp/Al) at the optimized machining parameters under various tilt angles of the workpiece. The surface morphology and material removal rate were determined with a laser scanning microscope VK-X100 (KEYENCE, Japan). Experimental results present a 60% rise in surface quality at 25° in tilt ED milling. On the basis of electromagnetic effect, the machining mechanism is analyzed in detail in tilt ED milling for lens molds.

Chemical mechanical polishing (CMP) process has been a popular wafer and thin film planarization process for semiconductor fabrication. In CMP process, a diamond dresser with well-distributed diamond grits is usually applied for regenerating the pad surface topography to maintain the pad polishing capability. This paper describes the fundamentally quasi-orthogonal diamond dressing process by pyramid single-point diamond tools at different grit angles under the fixed down pressure and slow dressing speed for elastomer pad conditioning. Experiments of single-point diamond dressing by both face direction dressing (FDD) and edge direction dressing (EDD) have been performed to investigate the normal force profile and pad surface topography. Experimental results show that FDD generates a higher quality of pad surface with lesser plowing volume and relatively stable pad cutting rate (PCR). Moreover, diamond grit with grit angle of 90° has been found to be most suitable while shifting between EDD and FDD during actual diamond dressing process. Results of this study can be applied to diamond dresserv design and optimization of the pad surface topography uniformity in diamond dressing process for CMP of integrated circuit (IC) production.

In the industrial applications of intersecting curve welding, in order to improve the accuracy and quality of welding, the automation program of weld seam positioning, data processing, and the actual welding is widely used. In this paper, a lot of research has been carried out, and a method based on non-uniform rational B-spline (NURBS) curve fitting is presented, while the trajectory of the welding torch is planned. The method can use the position data of the discrete weld seam points obtained by manual teaching or weld seam location. By the improved least squares method and the White rule, the outliers are eliminated and the weld seam points for intersecting curve fitting are obtained. These points are fitted based on NURBS, and then the parameter expressions of the fitted intersecting curve are given. For the purpose of obtaining the orientation of the welding torch, the coordinate system which can describe the feature of the fitted intersecting curve is established. The coordinate system is combined with the theoretical intersecting curve model and the fitted intersecting curve model and gives a novel approach to compute the orientation of the welding torch according to the position of the fitted intersecting curve. In the process of planning the welding trajectory, a fitted intersecting curve discrete algorithm based on the equal arc length principle is proposed to reduce the fluctuation of the feed rate according to the restriction of chord error. Finally, this method gives the position and orientation of the welding torch in the form of a homogeneous matrix and verifies the correctness and flexibility of the algorithm by MATLAB simulation and intersecting curve welding experiment.

Weld bead geometry at start and end of the bead is often abnormal compared with the middle region, which will greatly affect the forming in gas metal arc welding (GMAW) additive manufacturing. The study’s aim is to investigate the causes and the optimization strategy of the weld bead abnormity at the unstable region. The weld pool dynamics, convection, and the extension process were analyzed through a three-dimensional transient fluid model and the finite element analysis of thermal behavior. The results showed that the abnormal bead geometry can be attributed to the backward fluid flow and the metal swelling in the weld pool, and the length of the initial bulky region is positively correlated with the inclined shape at the end, as well as the length of the weld pool. Some strategies to control the bead abnormity through adjusting the welding parameters, the crater filling options, and the path planning patterns were proposed. These methods contributed to the continuous and smooth deposition surface and laid the foundation of GMAW-based additive manufacturing process.

The tool path used for polishing applications with characteristic of physically uniform coverage, which is similar to the iso-scallop path in milling operations, is significantly important to facilitate uniform material removal and acquire low surface roughness and consistent surface quality. In this paper, tool path planning method for physically uniform coverage instead of traditional geometrically uniform coverage of polishing path based on scanning mode is further investigated and an efficient iterative approximation algorithm is proposed. Then a complete spiral path generation strategy for small tool polishing of freeform surface is presented, which uses a cyclic iteration correction and driving method to produce spiral path with physically uniform coverage. At the same time, this strategy uses surface expansion and re-parameterization techniques to avoid edge effect in polishing. The effectiveness and robustness of the developed polishing path generation technique are proved by case studies. And the superiority of the planned polishing path over the traditional path in promoting uniformity of material removal is examined through the practical application of polishing.

Fast tool servo (FTS) in ultra-precision machining (UPM) is an enabling and efficient technology for fabricating optical freeform surfaces or microstructures with submicrometric form accuracy and nanometric surface finish. There are many kinds of FTS in the different driving principle to present their various performances currently. Their kernel technologies influence the machining ability and accuracy of freeform surfaces, consequently receiving much research attention and interest. These technologies are generally summarized as the development of FTS structure, the advanced control algorithms, tool path planning, machining condition monitoring, and surface measurement and error compensation. This paper aims to survey the current state of the art in machining freeform optics by FTS. An analysis of the principle, performance, and application of FTS machining with regard to freeform optics is presented. And the key machining technologies for optical freeform surfaces by FTS are then introduced in detail. The challenges and opportunities for further studies are concluded according to the FTS machining difficult of optical freeform surfaces finally.

In order to improve the accuracy and efficiency of damage assessment, a novel method to evaluate the damage state for remanufacturing blanks based on the magnetic and surface texture feature fusion was developed. Through modeling of the magnetic and surface texture features, sample entropy parameters from the magnetic intensity and its gradients were extracted, and energy, entropy, contrast, and correlation parameters from surface texture were obtained. The two-layered feature fusion model comprised of the data layer and the index layer was established. In the data layer, parameters of the magnetic and surface texture features and their nonlinear mapping relationships with damage were obtained. In the index layer, the information fusion between the magnetic and surface texture features was carried out by Dempster-Shafer (D-S) evidence theory. Finally, fatigue test samples were selected to verify the feasibility of the proposed method. Results show that the method can be used to determine the damage states of the remanufacturing blanks, which provides theoretical and technical decision support for remanufacturability of the components.

Acrylonitrile butadiene styrene (ABS) specimens manufactured by fused deposition are tested under uniaxial compression in order to judge the effectiveness of printing orientation, density, and filler patterns in terms of stiffness and strength per printing time. The compressive properties of the 3D printed materials along the three orthogonal directions are studied on cylindrical specimens filled with honeycomb and rectangular patterns. In order to achieve different densities, five filler percentages (0, 20, 30, 40, and 100%) are employed for each type of structure. Specimens filled with honeycomb patterns are stiffer and stronger than those with rectangular patterns only when they are oriented along the applied load. However, structures with rectangular patterns only require roughly half of printing time of those filled honeycomb cells, which yields effective rectangular structures with high elastic properties per printing time. Stress–strain curves reveal that compressive strength and stiffness increase with respect to the structure density. Patterns printed along the loading direction present higher strength and stiffness than on the other orthogonal orientations. Local buckling and compressive failure mechanisms are identified for light weight and heavy structures, respectively. A combination of shear and local buckling failure appeared in honeycomb structures printed transversely with relative densities around 20–40%.

Micro end-milling is widely used in many industries to produce micro products with complex 3D shapes. The accurate modeling and prediction of surface roughness are important for evaluating the productivity of the machine tools and the surface quality of the machined parts. This paper presents an accurate surface roughness model based on the kinematics of cutting process and tool geometry by considering the effects of tool run-out and minimum chip thickness. The proposed surface roughness model is validated by micro end-milling experiments with the miniaturized machine tool. The results show that the proposed surface roughness model can accurately predict both the trends and magnitude of the surface roughness in micro end-milling.

Additive manufacturing (AM) has become a prominent manufacturing technology due to its capability in manufacturing complex geometries without the demand for specific tools. However, AM technologies suffer from poor surface roughness limiting its widespread industrial application. Application of AM parts in industrial services highly relies on an appropriate post-processing stage to improve the surface roughness of the products. In the case of fused deposition modeling (FDM), acetone vapor bath smoothing is an effective solution for the post-processing stage. However, a vast understanding of the smoothing process is required. This paper presents an experimental study on the effect of the smoothing parameters on the resulting surface roughness of the final FDM products. The smoothing parameters are divided into the number of smoothing cycles and the cycle duration. The surface roughness is calculated based on the deviations from the total least square plane fitted to the surface topographic data sets. The effects of the design and the smoothing parameters are studied, experimental models are developed, and the best smoothing setups are proposed. The developed experimental models enable the engineers to predict the final surface roughness based on the exposure time to the acetone vapor bath or define the required post-processing steps to achieve the desired surface quality.

To optimize the machining process, finding the minimum uncut chip thickness is of paramount importance in micro-scale machining. However, strong dependency of the minimum uncut chip thickness to the tool geometry, workpiece material, tool-work friction, and process condition makes its evaluation complicated. The paper focuses on determination of the minimum uncut chip thickness experimentally during micro-end milling of titanium alloy Ti-6Al-4V with respect to influences of cutting parameters and lubricating systems. Experiments were carried out on a CNC machining center Kern Evo with two flute end mills of 0.8 and 2 mm diameters being used in the tests for micro- and macro-milling, respectively. It was found that the micro-milling caused more size effect than macro-milling due to higher surface micro-hardness and specific cutting forces. The specific cutting force depended strongly on feed rate (f z) and lubricating system, followed by depth of cut (a p) and cutting speed (v c), mainly in the micro-scale. All output parameters were inversely proportional to the specific cutting force. Finally, depending on different process parameters during micro-milling of Ti-6Al-4V, the minimum uncut chip thickness was found to vary between 0.15 and 0.49 of the tool edge radius.

As one of the incremental bulk metal forming, the main plastic metal flow of axial closed die rolling (ACDR) process consists of the axial compression and circumferential torsion. The key difference between the ACDR and forging processes should be concentrating on the plastic deformation zone (PDZ) evolution, especially on the condition of thermal deformation. Therefore, the verified FEM and corresponding experiment have been proposed to find out the systematic rule of PDZ. The thermal parameter distribution of the workpiece has been explored to obtain the PDZ evolution at different deformation extent. PDZ evolution mode has also been proposed, and the distribution of microstructure/hardness is given to the evidence of PDZ mode. The results show that the PDZ spreads from the contact area of the upper surface of the lower/side surface in ACDR process. Multiple thermal parameter evolution in ACDR process could be found through the analysis of microstructure morphology. Also, microstructure orientation could be the fundament of PDZ evolution. The cooling rate and the periodic evaluation of thermal parameters should be the main factors for the microstructure evolution, including the distribution of lamellar α and globular α. Then, the extent and range of PDZ could be defined through the observation and analysis of hardness evolution.

This paper reports a highly effective method for replicating large-area micropattern devices through hybrid extrusion rolling embossing using a roller mold, wherein a thin stainless steel mold with a large-area micropattern is wrapped onto a metallic roll to form a roller mold. During the hybrid extrusion rolling embossing period, the molten polymer film is extruded and immediately pressed against the embossing roller and roller mold, which results in the molten polymer completely filling the micropattern on the surface of the roller mold. Next, the molten polymer film is cooled and wound using a conveying system equipped with highly polished rollers. Thus, a continuous polymer film with many large-area micropattern devices can be fabricated. In this study, a new hybrid extrusion rolling embossing system was designed, constructed, and tested; the basic film extrusion and rolling embossing conditions were investigated; and the thickness uniformity of the polymer films and the replication quality of the micropattern devices were measured and analyzed. The results indicate that the hybrid extrusion rolling embossing can potentially be used for continuous mass production of large-area micropattern devices.

The powder bed fusion additive manufacturing process enables fabrication of metal parts with complex geometry and elaborate internal features, the simplification of the assembly process, and the reduction of development time; however, its tremendous potential for widespread application in industry is hampered by the lack of consistent quality. This limits its ability as a viable manufacturing process particularly in the aerospace and medical industries where high quality and repeatability are critical. A variety of defects, which may be initiated during powder bed fusion additive manufacturing, compromise the repeatability, precision, and resulting mechanical properties of the final part. One approach that has been more recently proposed to try to control the process by detecting, avoiding, and/or eliminating defects is online monitoring. In order to support the design and implementation of effective monitoring and control strategies, this paper identifies, analyzes, and classifies the common defects and their contributing parameters reported in the literature, and defines the relationship between the two. Next, both defects and contributing parameters are categorized under an umbrella of manufacturing features for monitoring and control purposes. The quintuple set of manufacturing features presented here is meant to be employed for online monitoring and control in order to ultimately achieve a defect-free part. This categorization is established based on three criteria: (1) covering all the defects generated during the process, (2) including the essential contributing parameters for the majority of defects, and (3) the defects need to be detectable by existing monitoring approaches as well as controllable through standard process parameters. Finally, the monitoring of signatures instead of actual defects is presented as an alternative approach to controlling the process “indirectly.”

Circular economy (CE) is a new business model that is pressing manufacturing companies to think about closed loop scenarios for materials and products. Design for End-of-Life (DfEoL) and Design for Disassembly (DfD) are key enabling methods for the effective application of this model. The paper presents a time-based method for the calculation of disassembly sequences, adopting basic theories and techniques in this topic and integrating new concepts for the assessment of the disassembly time. The method consists of five steps and starts from the documentations (e.g., CAD model) generally available early in the product development process. The first three steps encompass the product analysis by including (i) the definition of target components from the general assembly, (ii) the analyses of the virtual model, and (iii) the assessment of the so-called level matrix, which is based on the concept of disassembly levels and liaisons characterization among components. The last two steps allow for the assessment of the time-based disassembly sequence by including (iv) the analysis of feasible sequences and (v) the generation of the best disassembly sequence for target components. The method mainly overcomes two issues highlighted in the literature regarding the reliability of the disassemblability analysis using a time-based approach and the quality of results accounting for the real condition of the product at the time of disassembly. The calculation of the effective disassembly time is grounded on a specific repository developed to gather knowledge about the disassembly tasks and related disassembly time. This is the main contribution and novelty of the proposed approach. By using the proposed method, different target components of a washing machine are analysed with the aim of demonstrating the robustness of the method and its consistency in the estimation of disassembly time. A maximum deviation of 10% between the estimated and measured disassembly times is noticed.

During the manufacturing of dental prostheses, tight tolerances have to be obtained in order to ensure the correct fitting of the prosthesis seats to the implants located on the patient’s jaw. However, the wearing of the tool can generate errors during precision milling processes that lead to unacceptable geometrical deviations, producing a high cost due to the waste of resources and machine time. The present paper introduces a procedure for the avoidance of these defects during the precision milling processes employed for the machining of dental prostheses. By the use of geometrical models, the deviations generated on the machined surfaces by a worn tool can be calculated in comparison to a fresh tool. Once the deviations are calculated, it is possible to avoid them by the use of 2D tool radius compensation techniques. The capability of the solution presented here was validated by machining prosthesis seats and evaluating their assembly to a fitting part. The obtained results show that the developed solution is capable of eliminating the fitting strains generated when machining dental prosthesis seats with a worn tool.

The combination of different materials in one workpiece in order to optimize the workpiece characteristics is a state of the art design method for high-performance components. These workpieces can be made of the most qualified materials according to local requirements. However, during machining of material compounds, the different materials have to be considered. This is due to the specific material properties, cutting characteristics, and chip formation mechanisms. Cutting parameters have to be adapted for each material in order to achieve the demanded workpiece quality and optimal processes in respect of tool life and material removal rate. The focus of this research is the development of an in-process material identification algorithm. Thus, a cylindrical turning process is investigated for friction welded aluminum/steel shafts (EN-AW6082/20MnCr5). A universal monitoring approach is presented which detects the different materials process-parallel. For this purpose, cutting forces and spindle torque are linked with a dexel-based material removal model to determine monitoring parameters. The design of experiment method is used to validate the approach for various process parameters. Cutting speed and feed velocity are adapted for cylindrical turning operations based on the monitoring algorithm. As a result, material-specific cutting parameters are adjusted during the machining in order to optimize the material removal rate. Based on this approach, further process optimization can be implemented, like the improvement of chip formation, while machining hybrid workpieces.

In industry, many taper shafts are designed with tolerances of a few microns. To cut them in finish turning, paths of the tool in virtual machining should be accurately generated beforehand. For this purpose, the dimension errors and surface roughness of the virtually cut workpiece should be predicted. Unfortunately, the current tool path generation methods cannot accurately calculate the errors and the roughness, resulting in the taper errors larger than the part tolerance. Our research formulates equations of the effective turning edge to accurately calculate the dimension errors and the surface roughness, and then proposes a new approach to CNC programming for high-precision CNC turning. It lays a theoretical foundation of modeling parts in virtual turning and can generate tool paths to machine taper parts with high accuracy.

In this study, the performance of Si wafer machining by employing the die-sinking microelectrical discharge machining technique is reported. Specifically, the machining performance was examined on both high- (1–10 Ω cm) and low-resistivity (0.001–0.005 Ω cm) Si wafers by means of using a range of discharge energies. In this regard, the machining time, material removal rate, surface quality, surface roughness, and material mapping, which are categorized among the important properties in micromachining, have been investigated. In order to analyze the surface properties and to perform the elemental analysis, the scanning electron microscope and energy-dispersive X-ray spectroscopy were used. In contrast, the 3D surface profiler was used to evaluate the roughness of machined surface. The results of this experimental study revealed that the electrical resistivity and discharge energy parameter of microelectrical discharge machining had a great influence on the Si wafer machining performances. The observations in this study indicated a decrease in machining time, high material removal rate, and high surface roughness with an increased discharge energy values. Overall, it was learnt that the minimum amount of energy required to machine Si wafer was 5 μJ for both low and high-resistivity Si. In addition, the highest material removal of 5.842 × 10−5 mm3/s was observed for low-resistivity Si. On the contrary, the best surface roughness, R a, of 0.6203 μm was achieved for high-resistivity Si and it also pointed to a higher carbon percentage after the machining process.

This paper offers a review of rolling technology of shape flat products. The demands for the shape flat products are increasing quickly in the market of structural material. Some of them are so new that up to now there are no the standard specification, clear concept, and even no widely agreed name. Then, several kinds of shape flat products by rolling are introduced, and the definition, classification, characteristics of cross section, and production and application of them are given. One of them is the rolled profile strip (RPS), of which the thickness is different in transverse direction. The differences among the RPS, roll forming products, and economical sections are analyzed. Taking RPS as an example, the three forming methods are introduced, which are channel spread method, band spread method, and multi-pass spread method. The RPS products are applied to the uneven load distribution of bearing as to reduce the structural weight or meet the needs of the space dimension, special loading requirement by construction design. An example is introduced to carry out the experiments of rolling RPS products with band spread method, taking Al as simulating material. The RPS samples with thickness ratio of 1:1.3 are obtained. The results prove that the band spread method is a reasonable way to produce the RPS products.

Aiming at providing an effective mechanism for representation, organization, and reuse of fixture design knowledge, this paper puts forward an intelligent methodology for fixture design based on knowledge component technology. First, the ontology models of fixture elements, the workpiece, and the fixture design case are constructed to organize the statical design knowledge related to each of them. Then, the fixture design process-related knowledge is modeled by knowledge components corresponding to fixture layout planning process and fixture structure design process. Hence, the hierarchy structure of the fixture design knowledge reuse is formed. Under the framework of the fixture layout knowledge component, the association analysis method is used for generating reasoning rules and then the rule-based reasoning (RBR) method is used for the determination of the workpiece-locating mode and the initiative candidate of the locating datum. Further, an entropy weight fuzzy comprehensive evaluation method is employed to select the most suitable locating datum from the candidates. Under the framework of the fixture structure design knowledge component, the selection of fixture elements, element dimension drive, and auto-assemble are fulfilled by the combination of RBR and case-based reasoning (CBR). The method realizes the effective organization and efficient use of fixture design knowledge and improves the efficiency of fixture design. It has been verified by a case of airplane part machining fixture design.

The paper presents an original contribution to the prediction of surface topography produced by precision hard turning operations using CBN cutting tools and the variable feed rate of 0.025–0.075 mm/rev. The differences between theoretical and real surface roughness parameters Rz and Sz are quantified in terms of springback effect, additional smoothing of irregularities and side flow effect. The primary experimental study includes measurements of 2D and 3D surface roughness parameters using contact profilometer. Correspondingly, cutting forces were measured using a piezoelectric dynamometer, and based on this data, specific corresponding values of ploughing energy and friction coefficient were determined. It was found that the measured value of maximum height of the surface Sz differs from the theoretical value mainly due to elastic recovery of the machined surface and the smoothing effect at the lower feeds and the elastic recovery and the side flow effect at the higher feeds employed. An empirical model for the prediction of the Sz value in function of the feed rate is derived. The prediction accuracy can be improved by advanced numerical modelling of surface generation mechanisms and associated distortions.

Increasing competition and high accuracy make it necessary to optimize and evaluate the outcome of manufacturing processes. In tool grinding, models for the tool path and tool setting are of particular interest. In this article, to establish a valid general grinding model, an improved method for tool setting error compensation is proposed. We consequently developed models of tool path and tool setting, and verified the models by simulations. Lastly, the model is demonstrated through testing of a concave aspheric surface. The experiment results show that the introduced models are valid for grinding in aspherical mirror, since they are solely based on the geometry and process parameters, and hence are applicable for manufacturing process optimization.

Wave-transmitting Si3N4 ceramics exhibits high levels of brittleness, and the milling surface inevitably exists defects. Critical cutting depth is an important reference parameter to improve the surface quality and processing efficiency in milling. A theoretical mathematical model has been proposed to predict the critical cutting depth in the study. The contact relationship between the tool cutting edge and the ceramics surface is analyzed, and the non-uniform bearing crack system is established. The micro cracks propagation critical condition has been put as the criterion of critical cutting depth. Through the model calculation, the critical cutting depth is 0.38 mm, and it is confirmed the critical cutting depth is between 0.3 and 0.4 mm with experimental results. The model predictions are consistent well with the experimental results. In addition, the theoretical model shows that the critical cutting depth decreases exponentially with the increase of the material hardness, while the increase of fracture toughness, tool helix angle and side edge rear angle, leads to critical cutting depth rising. The theoretical model can be applied to evaluate the critical cutting depth of brittle ceramics in milling.

Presently, the quality evaluation of long blade profile is still mainly based on the specific cross section, focusing on the twist, position, and profile errors. However, the common registration methods of blade profiles only focus on profile error and ignore other important parameters, which may results in misjudgment of qualified blade or increasing the scrap rate. So, a new global-to-local registration and error evaluation method for a long blade is proposed in this paper. Based on the parameter priority, the registration of the blade is completed from global fine registrations to local fine registrations. The best-fit algorithm is used for global fine registration to screen out the qualified blades firstly. Then, the unqualified results are further optimized by the coordinate alternation method in the local fine registration to guarantee the evaluation result qualified as far as possible. The experimental results show that the proposed method reduces the misjudgment effectively by keeping the more important parameters in the tolerance range. And it is beneficial and practical to guide blade finish machining or repairing because the difficult finish machining or repairable machining parameters are priority to guarantee in the allowable error range.

As one of the most efficient machining methods, plunge milling has gained more attention as a promising cutting process. This strategy is often used for roughing and semi-roughing processes for the more vibration free than other cutting operations. The motivation of this paper is that the cutting forces in plunge milling differ from that in side milling for the complex cutting condition and tool geometry. In this work, a systematic and analytical cutting force prediction model considering cutter runout for plunge milling is proposed. The detailed analysis of cutting geometry is important for modeling. The precise uncut width is calculated with consideration of the cutting step. In addition, the real-time uncut chip thickness of different inserts is calculated with consideration of the effect of cutter runout. The deduced cutting force model based on the predictive model can be used in various cutting conditions in the plunge milling process. Plunge milling tests with various cutting steps are carried out to verify the proposed model with the quantitative analysis of the results. The results indicate that the simulated results show quite good agreements with the measured cutting forces, which proves the correctness and accuracy of the proposed model.

This study aimed to realize tailored pressure distributions by vaporizing metal foils. The foil specimen with two separate active areas can be fully vaporized at both tailoring positions using capacitor bank discharge. The shock pressure amplitude was revealed by free bulging test. The length effect of the foil specimen on generating shock pressure for the metal-forming work was firstly examined. Aluminum foil with an active length up to 300 mm was completely vaporized under a charging energy of 6 kJ. Using different combinations of process parameters including foil geometry and polyurethane plates, a variety of tailored pressure distributions were created. The pressure amplitudes at two separate positions can be varied by changing the process parameters used such as foil length and width and polyurethane thickness. Finally, the tailored pressure distribution was applied to sheet metal-forming process and a part with different forming depths was manufactured.

This paper investigates the issue of unevenness of machined surface using ceramic brush for aiming the automatic lapping of the large work surface. A numerical model and machining results with ceramic brush are presented. In the machined surface, the slight sloped surfaces between left and right sides along the feed direction were generated, and they were highly affected by the protrusion of fiber, the preload, the feed rate, and the overlapped machining. The numerical model for ceramic brush lapping is induced based on trajectory simulation of each brush fiber using the dynamic FEA result of contact pressure and deformation to understand the issues of surface uniformity. In the simulation part, A FEA model of brush lapping is proposed to investigate not only its elastic behavior during the machining process but also its effect on the machined surface. The lapping experiment is comprised of several steps using different preload, revolution speed, protrusion, feed rate, and overlapped machining pitch. For each step, it is shown that the trend of change in surface quality according to each machining parameter using the numerically controlled machine. Each machining condition plays an important role in lapping quality, which can determine the surface uniformity. Highly smooth surfaces were obtained by selecting the appropriate conditions without any unevenness issues on overlapped machining region. Also, the surface roughness comparison result with other surface finishing method presents similar quality even in worse initial surface roughness condition, which indicates the possibility of efficient automatic surface uniformity using ceramic brush lapping on milling surface of workpiece.

The design of hyperbolic profile grinding wheels operating at peripheral speeds up to 250 m/s is described in detail. The wheels considered here are segmented with vitrified bonded cubic boron nitride abrasive (cBN) structures and attached to a variety of reinforced centre materials using a high-strength adhesive bond. The simulation of stresses at various speeds is conducted using a finite element analysis compared to closed-form solutions. Safety factors are calculated using analytical stress predictions and experimental strength measurements assuming that the segments bonded to the reinforcing centre section that is not constrained by radial motion. The paper shows that beyond peripheral speeds of 190 m/s, carbon fibre epoxy with a 15° ply is the only material that can guarantee the industry standard of a safety factor of three at such high operating speeds.

The Taguchi method and numerical simulations were used to determine the significant parameters of a 3D deflector in channel flow. The lost-wax casting method was used to fabricate polydimethylsiloxane (PDMS) channels with a 3D deflector. Once fluid passes through the deflector, it will induce vortexes in the channel, causing flow separation, stretching, twisting, and interactions with the fluid already in the channel. Better mixing ratios can be achieved with a stronger vorticity. Our methods and measurements demonstrated the fidelity of the replication process from the original CAD file to the PMMA mold, wax pattern, and PDMS channel. Compared to other microfabrication methods, such as injection molding, micromachining, and hot embossing, lost-wax casting is a successful method for producing a 3D deflector in a PDMS channel.

Laser beam micromachining (LBMM) process is one of the important advanced manufacturing processes which can shape almost all engineering materials with micron scale precision even for complex geometries. LBMM process when performed in air generates high heat flux causing thermal damage and poor surface finish on the substrate material. Liquid-assisted laser beam micromachining is considered as an alternate approach to the traditional laser beam micromachining process performed under air to reduce the thermal damages caused due to high heat of laser. The presence of liquid medium also helps in carrying away the molten material from the machining zone thereby preventing re-deposition. The focus of this research is to understand the effect of critical process parameters involved in liquid-assisted laser beam micromachining using finite element simulation technique. The study revealed that the width (diameter) and depth of the heat-affected zone decreased considerably with water film thickness of 0.50 mm and higher. Further experimentation is used to validate the results of the simulation model. The experimental results closely matched with the predictions of the simulation study. Micromachining performed under thin films of water and ethylene glycol showed better surface finish as compared to machining performed without water. This suggests that the liquid medium occupies the void during material removal due to laser beam and helps reducing the thermal damage.

This paper describes a development of in-process prediction of roundness from the previous research of the author in CNC turning process. The relations of roundness, dynamic cutting forces, and cutting conditions have been investigated. In order to eliminate the effects of the cutting conditions, the dynamic cutting forces are dimensionless by taking the ratio of the average variations of dynamic radial force to that of the dynamic feed force. The exponential function is employed for the sake to model the in-process prediction of roundness which consists of cutting speeds, feed rates, depths of cut, tool nose radiuses, rake angles, and dynamic cutting force ratio. The experimentally obtained results showed that the better roundness errors can be obtained by increasing the cutting speed, the tool nose radius, and the rake angle. The new cutting tests have been conducted to verify the obtained model. It is understood that the in-process roundness can be predicted well during cutting with the high accuracy by using the proposed method.