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Purpose This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material. Design/methodology/approach The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time. Findings Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX. Originality/value A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.

Battery/Ultracapacitor (UC) Hybrid Energy Storage Systems (HESS) for Electric Vehicles (EVs) have been frequently proposed in the literature to increase battery cycle life. The HESS consists of a Power Management Strategy (PMS) and an Energy Management Strategy (EMS). Existing EMS are quite empirical, such as setting constant target UC energy levels regardless of load. This work presents an improved complete HESS management strategy. The EMS involves a more comprehensive method of setting the target UC energy level using a speed-dependent band. This allows the UC to achieve two goals – contain sufficient energy for future accelerations and have sufficient space for capturing energy from future regenerative braking – without knowledge of the future drive profile. The PMS involves a speed-dependent battery power limit, which also achieves two goals – better UC utilization and allowing the battery to supply the steady state power. Simulations show existing works cannot achieve the four goals simultaneously unless their UCs are sized twice as large compared to the proposed rule-based HESS. In addition, the proposed HESS extends battery cycle life by up to 42% compared to a battery-only system. Lastly, a reduced-scale experiment was built to show that the proposed HESS is able to run in real-time.

Energy-efficient manufacturing is playing an important role in addressing worldwide problems like air pollution, climate change, and energy crisis. Despite of the close relationship between process planning and scheduling, existing research efforts often consider energy efficiency-related issues by treating them separately and sequentially. This may cause various problems such as unbalanced resource allocation and infeasible production solutions, thus limiting their potential application. To advance the current state of the art in this area, this paper investigates energy-efficient integration of process planning and scheduling. Specifically, a mixed-integer linear programming model is firstly developed to formulate this problem mathematically. Subsequently, to solve more realistic large-sized problems, a heuristic-based two-stage approach is proposed. Stage 1 and Stage 2 aim at minimizing the total tardiness and reducing the total energy consumption, respectively. A realistic case study shows that the proposed two-stage approach works more efficiently and effectively than a modified genetic algorithm from existing literature. Through instructive modification of the solution space, the proposed approach can effectively reduce the total tardiness and total energy consumption; meanwhile the machining cost of individual process plans can also be kept at low level throughout the searching process. Results show that the proposed approach can allocate the machining resources in a more reasonable manner. As such, this paper may be a valuable supplement to existing efforts aiming at developing energy-efficient manufacturing techniques.

Additively manufactured lattice structures enable the realisation of light-weight, multi-functional, structures. For example, lattices can be used for high stiffness and buckling resistance in sandwich structures or as support material for additive manufacturing. Topology optimisation and additive manufacturing are two technologies that allow the design, optimisation and manufacture of complex lattice designs. In this work, a new lattice optimisation methodology is presented that tailors the size, shape and orientation of individual lattice trusses in three-dimensional space by using principal strain fields obtained from topology optimisation. This new method of generating functionally graded lattices is shown both numerically and experimentally to be capable of generating lattice structures with greatly improved stiffness and strength when compared to lattice structures with a uniform lattice infill. Upper and lower relative density thresholds and minimum truss member sizes are included in the optimisation workflow to ensure that the optimised lattice designs are compatible with additive manufacturing process constraints. The functional grading method is also shown to be capable of generating conformal lattice structures in three dimensions, even for complex loading conditions and arbitrary volume boundaries.

3D printing and particularly fused deposition modelling (FDM) is widely used for prototyping and fabricating low-cost customised parts. However, present fused deposition modelling 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the significant process errors in fused deposition modelling 3D printers, and it affects the quality of prototyped parts in terms of mechanical properties and geometrical accuracy. This paper proposes a dynamic model for current-based nozzle condition monitoring in fused deposition modelling, which is briefly described as follows. First, all the process forces in filament extrusion of the fused deposition modelling were identified and derived theoretically, and theoretical equations of the feed rolling forces and flow-through-nozzle forces were derived. In addition, the effect of the nozzle clogging on the current of extruding motor were identified. Second, based on the proposed dynamic model, current-based nozzle condition monitoring method was proposed. Next, sets of experiments on FDM machine using polylactic acid (PLA) material were carried out to verify the proposed theoretical model, and the results were analysed and evaluated. Findings of the present study indicate that nozzle clogging in FDM 3D printing can be monitored by sensing the current of the filament extruding motor. The proposed model can be used efficiently for monitoring nozzle clogging conditions in fused deposition modelling 3D printers as it is based on the fundamental process modelling.

Specific structures of esophagus play an important role in specific functions. However, current esophageal tissue engineering scaffolds replicate them poorly. To address this issue, the objective of this study is to fabricate a hierarchical PCL/F127 scaffold inspired by the natural esophageal structure. The hierarchical scaffold consists of aligned fibers in micro-size and thin film with nano-sized pores through combining E-jetting and E-spraying. The aligned fibers of scaffold guide the orientation and induce the elongation of fibroblasts, mimicking the uniformly oriented esophageal muscles. Furthermore, the film functioned as a protective barrier to replicate the esophageal mucosa. Meanwhile, the film also increases cell adhesion area, hence, improving cell proliferation. These two features of the fabricated hierarchical scaffold mimic the structure of natural esophagus. Moreover, fabricated hierarchical scaffold possesses comparable mechanical properties to natural esophagus. These results prove the potential of fabricated scaffold for esophagus tissue repair.

Improving energy efficiency has been one of main objectives in modern manufacturing enterprises. Various approaches aiming at efficient energy management have been proposed/developed, among which minimizing energy consumption by energy-sensible production scheduling techniques has emerged as a promising one. However, reported workshop models are quite simple and unrealistic. This paper studies a more realistic workshop model called ultra-flexible job shop (uFJS). In an uFJS, the sequence among operations for a job can be changed within certain constraints. To formulate this energy-efficient scheduling problem, a mixed-integer linear programming model was developed. To deal with large-sized problems, a specially designed genetic algorithm (GA) was subsequently proposed and implemented. Numerical results showed the proposed GA worked with decent effectiveness and efficiency. Finally, several comparative studies are carried out to further demonstrate its efficacy in terms of energy efficiency improvement. The advantage of the uFJS as compared to other relative simple workshop models is also shown. By considering the flexibility in operation sequencing in each job, the uFJS effectively integrates process planning and scheduling in discrete parts manufacturing system, thus providing a much larger solution space for more energy-efficient solutions. It therefore provides an excellent platform for decision-makers when developing energy-efficient techniques and strategies

NGCs are considered as an alternative treatment method for treating peripheral nerve injuries in place of nerve autografts. Biomimicry, conductivity, and biodegradability are the properties expected of an ideal NGC. PCL/PAA NGCs with three different concentrations of PAA (2.5, 5 and 7.5%) were fabricated using EHD-jet 3D printing. The mechanical properties of the PCL/PAA NGCs mimic the native human nerve properties (ultimate tensile strength of 6.5 to 11.7 MPa) and the conductivity match that of the amphibian motor nerve fiber myelin sheath (10−6 S/cm). The in vitro degradation studies reveal that they are biodegradable and injury/site-specific biodegradability can be obtained by tuning the PCL/PAA concentration ratio. In addition, PAA being a polyanionic polymer has the potential to act as a cation-exchanger, mimicking the functions of the nerve cortical gel layer, thereby influencing the electrophysiological phenomena called nerve excitation and conduction. Neural differentiation studies with PC12 cells assessed by the Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and immunocytochemistry showed enhanced gene expression with the presence of PAA. Our results suggest that the EHD-jet 3D printed porous conductive PCL/PAA NGCs has the potential to be used in the treatment of peripheral nerve injuries. Keywords: 3D printing, Tissue engineering scaffolds, Peripheral nerve injury, Nerve guide conduits, Electrohydrodynamic jet, Conductive scaffolds

3D printing and particularly fused filament fabrication is widely used for prototyping and fabricating low-cost customized parts. However, current fused filament fabrication 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the most significant process errors in current fused filament fabrication 3D printers, and it affects the quality of the prototyped parts in terms of geometry tolerance, surface roughness, and mechanical properties. This paper proposes a nozzle condition monitoring technique in fused filament fabrication 3D printing using a vibration sensor, which is briefly described as follows. First, a bar mount that supports the liquefier in fused filament fabrication extruder was modeled as a beam excited by a system of process forces. The boundary conditions were identified, and the applied forces were analyzed for Direct and Bowden types of fused filament fabrication extruders. Second, a new 3D printer with a fixed extruder and a moving platform was designed and built for conducting nozzle condition monitoring experiments. Third, nozzle clogging was simulated by reducing the nozzle extrusion temperature, which caused partial solidification of the filament around inner walls of the nozzle. Fourth, sets of experiments were performed by measuring the vibrations of a bar mount during extrusion of polylactic acid, acrylonitrile butadiene styrene, and SemiFlex filaments via Direct and Bowden types of fused filament fabrication extruders. Findings of the current study show that nozzle clogging in fused filament fabrication 3D printers can be monitored using an accelerometer sensor by measuring extruder’s bar mount vibrations. The proposed technique can be used efficiently for monitoring nozzle clogging in fused filament fabrication 3D printers as it is based on the fundamental process modeling.

The rapid development of additive manufacturing technology provides a more flexible and efficient manufacturing solution for the high value-added parts with a complex topology. However, the poor surface finish poses a major obstacle for the wide application of the additively manufactured components when their functionality and tolerance are benchmarked with those produced by the conventional process. In selective laser melting, visible pattern and texture of the printed layers and unmolten particles cannot be avoided although research works have been conducted to improve the surface finish by optimising the selective laser melting strategy and process parameters. Therefore, a dedicated post-processing technique is generally required to improve the surface finish of the additively manufactured products in terms of various levels of geometric complexity. In this study, a vibration-assisted conformal polishing tool is developed to finish a representative v-groove structure fabricated by selective laser melting. Experiments are conducted to investigate the effects of abrasive size and polishing time on the improvement in surface roughness. The developed technique in this paper can be applied to finish the additively manufactured internal structures such as honeycomb structure and irregular holes that have linear projection along a single axis.

Earthworm-like soft robots have been widely studied for various applications, such as medical endoscopy and pipeline inspection. Many actuation modes have been chosen to drive the soft robots, including pneumatic actuators, dielectric elastomeric actuators, and shape memory actuators. Pneumatic actuators stand out since the soft robots with pneumatic actuation can produce relatively large forces and displacements with relatively ease of fabrication. Currently, several pneumatic actuators are used to realize elongating movement and anchoring movement of the earthworm for peristaltic motion. More pneumatic actuators not only require more pumps and valves to actuate and control the earthworm, but also lead to less efficient movement control of the earthworm. To address this issue, a new design with integrated single pneumatic actuator and cellular structures is developed to realize elongating movement and anchoring movement of the earthworm-like soft robot in peristaltic motion. With the new design, the simulation model of the new earthworm is developed to simulate both elongating and anchoring movements of the earthworm. A 3D printed prototype of the earthworm-like soft robot is fabricated to validate the proposed design and simulation model. Experimental results show good agreement with the simulation in elongations of peristaltic motion as the differences between the simulated and experimental is 5.8 % in one cycle of the peristaltic motion.

Apparent anisotropies have been found in the microstructure and mechanical properties of selective laser melted (SLM) Ti–6Al–4V alloy, which will significantly influence the comprehensive performance of the SLM parts. In this study, the effect of scanning strategies on material anisotropy, including surface morphology, microstructure, microhardness, quasi-static and dynamic mechanical properties, were comprehensively investigated with 0°, 67.5°, and 90° scanning strategies. The SLM Ti6Al4V alloy prepared by the 0° scanning strategy exhibited the most pronounced anisotropy. The size of the primary columnar crystals on the front surface (158–173 μm) is approximately 1.8–3.2 times larger than that of the top surface (54–88 μm), and the microhardness at the top surface is ∼30% higher than that of the front surface. In addition, the modified Johnson-Cook constitutive model for the SLM Ti6Al4V alloy was developed based on the results of quasi-static compression and dynamic compression with the average absolute relative error controlled within 10%. This provides a reliable solution and an effective material constitutive model for modeling and simulation of the machining SLM parts with higher accuracy and enhanced physical meaning.

Overlapping melting trajectories and partially-melted powders result in poor surface morphology and high surface roughness values (Ra = ~13.34 μm) of selective laser melted (SLMed) Ti6Al4V alloy. Secondary processing of SLMed components is thus an essential finishing operation to produce functional SLMed parts in precision engineering. This paper investigates the effects of laser scanning strategies (0°, 67.5° and 90° laser scanning schemes) and machining surfaces (top and front surfaces) on the machining performance of SLMed Ti6Al4V alloy in milling, compared with that of annealed ASTM B265 Ti6Al4V alloy. High degree of anisotropy of SLMed Ti6Al4V alloy is reflected in cutting force, surface morphology and surface roughness on different machining surfaces. The machining anisotropy is dominated by the anisotropy of microstructure and mechanical properties of SLMed Ti6Al4V alloy, where the anisotropy weakens following the sequence of 0°, 90° and 67.5° SLMed samples. It is verified that high cutting speed can improve machining anisotropy features of SLMed titanium alloy. The chip shape of SLMed Ti6Al4V alloy is a typical conical spiral chip, and the bending degree and length of chips produced by SLMed Ti6Al4V alloy are larger than those produced by annealed Ti6Al4V alloy.

This paper aims to improve the surface quality of 316L stainless steel parts manufactured by selective laser melting (SLM) using dry mechanical-electrochemical polishing (DMECP). DMECP is an advanced surface finishing method combining the advantages of both mechanical and electrochemical polishing techniques in a more environmentally friendly manner. In this paper, the SLM process-related defects causing poor surface quality are analysed first. The material removal mechanism of DMECP is investigated to continuously remove the oxide layers formed during polishing. Surface morphology and roughness evolution under different polishing conditions are characterised. The top surface roughness can be reduced by over 91% from 8.72 μm to 0.75 μm compared to side surface by over 93% from 12.10 to 0.80 μm. The material removal on the top surface is more efficient than that on the side surface under the same polishing condition. The secondary defects formed during polishing can be removed using mechanical polishing mode. The chemical element composition of the polished surface exhibits almost identical content to the initial 316L powders. Compared with the initial dark and rough surfaces, the results validate the capability of DMECP as an effective tool to improve the SLM surface quality and achieve a mirror finish.

Stress shielding is one of the main problems that lead to bone resorption and revision surgery after implantation. Most of the commercially available metallic non-porous bone implants have a much greater stiffness than the native human bones and are prone to cause stress-shielding. With an open cell structure and intricate architecture, hyperbolic minimal surfaces offer several advantages such as less stress concentration, high permeability and high surface area to volume ratio, thus providing an ideal environment for cell adhesion, migration, and proliferation. This paper explores the use of porous bone implant design based on Triply Periodic Minimal Surfaces (TPMS) which is additively manufactured with ceramic material (Alumina) using Lithography-based Ceramics Manufacturing (LCM) technology. A total of 12 different primitive surface structure unit cells with pore size in the range of 500–1000 μm and porosity above 50% were considered. This is one of the earliest studies reporting the 3D printing of TPMS-based structures using ceramic material. Our results suggest that the choice of material and a porous TPMS-based design led to fabrication of structures with a much lesser compressive modulus comparable with the native bone and hence could potentially be adopted for bone implant design to mitigate the stress-shielding effect.

Biomimicry is a desirable quality of tissue engineering scaffolds. While most of the scaffolds reported in the literature contain a single pore size or porosity, the native biological tissues such as cartilage and skin have a layered architecture with zone-specific pore size and mechanical properties. Thus, there is a need for functionally graded scaffolds (FGS). EHD-jet 3D printing is a high-resolution process and a variety of polymer solutions can be processed into 3D porous scaffolds at ease, overcoming the limitations of other 3D printing methods (SLS, stereolithography, and FDM) in terms of resolution and limited material choice. In this paper, a novel proof of concept study on fabrication of porous polycaprolactone-based FGS by using EHD-jet 3D printing technology is presented. Organomorphic scaffolds, multiculture systems, interfacial tissue engineering, and in vitro cancer metastasis models are some of the futuristic applications of these polymeric FGS.

Lightweight lattice structures are an important class of cellular structures with high potentials for multi-functional applications. Considering load-bearing requirements, truss buckling is one of the main failure mechanisms for low density and slender lattice structures. Critical buckling loads can be increased by modifying the profile of a truss. In this paper, we present a shape design method to optimize the critical buckling loads for lattice cores with free-form trusses. The free-form truss is represented by Fourier series and implicit surfaces, having smooth truss diameter variations and truss joints. The optimized truss profile is obtained by solving a parametric shape optimization problem with Fourier series coefficients as design variables. The method is used for designing optimized 1D columns and 3D Kagome lattice cores for sandwich panels. The numerical results predict 26.8% and 20.4% improvements of the critical buckling loads for 1D columns and 3D Kagome lattice cores compared to their uniform counterparts of the same mass, respectively. The optimized structures include complex smooth and curved geometries that are well suited for additive manufacturing because of the greater design freedom. Finally, the initial and optimized lattice cores are additively manufactured and tested. The experimental results validate the effectiveness of the proposed method. Keywords: Additive manufacturing, Shape design, Buckling failure, Kagome lattice core, Free-form truss

For negative Poisson's ratio (NPR) cellular structures, most previous research focus on the design of unit cells, and then repeat the unit cell to construct uniform cellular structures. However, there is a disadvantage that these structures do not have much design freedom to achieve high-level functions, such as performing a desired deformation. As a solution, an evolutionary design method is proposed to develop nonuniform cellular structures. To conduct this method, the design domain is divided into finite unit cells with tunable Poisson's ratio (PR). With a given objective deformation, the value of each unit cell's PR is optimized using evolutionary algorithm (EA). In order to reduce the computational cost of the algorithm, discrete cosine transform (DCT) is applied to encode the structure for evolving. Considering the geometrical complexity of the optimized nonuniform cellular structures, additive manufacturing (AM) is chosen to build them physically. Both two-dimensional (2D) and three-dimensional (3D) design cases were developed and analyzed to validate the proposed method. The computational and experimental results showed good conformation with each other. Most importantly, this novel design method brings huge potential to NPR cellular structures with high-level functions and much wider applications. Keywords: Nonuniform cellular structure, Poisson's ratio, Evolutionary algorithm, Re-entrant structure, Additive manufacturing

Thin-walled tubes have long been used as energy absorbing structures, owing to their high specific energy absorption (SEA) capacity. But, they are associated with substantial high values of peak cr...

In the robotic machining process, the external force due to cutter-workpiece interactions and gravity force due to link weights can cause considerable deviations of the desired trajectory. Besides, gravity compensators can be found in many heavy-duty industrial robots to balance the gravity force. However, the effects of gravity force and balancing force are rarely considered in the deflection analysis. This paper proposes an effective method for the stiffness modeling of heavy-duty industrial robots by taking account of the joint/link compliances, link weights and gravity compensator. Firstly, the static equilibrium equations of each substructure are formulated to derive the expressions of reaction force exerted on each joint. Secondly, a linear map of linear/angular deflections between the joints/links and the end-effector is developed. Finally, the stiffness model of the whole robot is formulated by integrating the joint/link compliances. The robot deflections at several configurations are analyzed, and the deflection distributions throughout the workspace are demonstrated. With this model, it is possible to analytically evaluate the contributions of external force, link weights and gravity compensator to the total deflections. The correctness of the proposed model is also experimentally verified by comparing the calculated and the measured deflections under the same conditions.

Functionally graded lattice core structures show a gradual and localised variation in their mechanical properties with the aim of improving structural performance whilst minimising weight. We present a novel approach to generate optimised functionally graded lattice core structures. Firstly, topology optimisation is performed to return the optimal core density distribution to minimise the structure's compliance subject to a mass constraint. A series of isostatic lines are then constructed with respect to the local principal stresses to generate a lattice structure spatially graded with respect to lattice cell size, aspect ratio and orientation. To validate this novel approach, optimisation is performed on a sandwich core structure subject to three point bending. Experimental tests confirm the greatly improved stiffness and strength properties (101% and 172% respectively) of the core as a result of spatially grading the lattice cells when compared to a benchmark core with uniform cell size of the same density. The new approach also significantly outperforms lattice structures with graded diameters as optimised by state-of-the-art commercial software packages. Non-dimensional core performance indices are formulated to express the relative specific stiffness and strength properties of the core for the three design approaches. Keywords: Topology optimisation, Lattice structures, Finite element analysis, Functionally graded materials, Sandwich structures

Surface roughness is often considered as one of the most important technical requirements for a machined part in production. Traditional selection of conservative process parameters neither guarantees part surface quality nor attains high metal removal rates. An accurate prediction and effective control of surface roughness is of vital importance for improving machining efficiency and reducing machining cost. In this paper, a novel model is presented for predicting surface roughness when slot milling Al-7075. The model is developed using a hybrid approach combining analytical calculation of specific cutting energy consumption (SCEC) and empirical characterization of the relationship between the surface roughness and SCEC. The proposed model has been validated by experiments under various cutting conditions. Compared to Taguchi methodology for predicting surface roughness, the proposed model is more accurate and reliable. From a novel viewpoint of SCEC, the model may provide valuable information regarding the effects of the cutting parameters on the surface roughness. Besides, the implementation of this model is straightforward, thus providing great potential for surface roughness control in real production.

Metallic lattice structures are well known for having high specific elastic moduli and strength. However, very little is understood about their resistance to fracture. In this work Ti–6Al–4V lattice structures are additively manufactured by selective laser melting and their fracture toughness characteristics are investigated. Resistance to fracture was determined under Mode-I loading at static rates using an extended compact tension (EC(T)) specimen, modified to contain lattice cells. The lattices consist of octet cells with a 3.5 mm edge length and relative densities ranging from 25% to 56%. Toughness is shown to increase by a power law with relative density and this trend was also obtained with finite element models. A new functional grading optimisation methodology is also presented for increasing fracture toughness. The size optimisation results in a functionally graded lattice whereby lattice truss diameters become the design variables. After size optimisation, initiation fracture toughness increases by up to 37%.

Selective laser melting (SLM) is generally characterized by the brief laser-powder interaction time, highly localized heat intensity and input distributions, steep temperature gradients and high cooling rate. It was admitted that the mechanical properties of as-built SLMed components exhibit significantly anisotropic due to different heat history and microstructures in different directions. Post-processing of additively manufactured parts is generally considered an essential operation due to poor surface quality and dimensional accuracy. In this paper, comprehensive research is conducted about the influence of material anisotropy of additively manufactured Ti-6Al-4V alloys on machining performance in ultra-precision micromachining. The machining performance of SLMed Ti-6Al-4V alloys was derived from two cutting directions (parallel/perpendicular to the laser scanning direction), two machining surfaces (top/front surface) and three laser scanning strategies (0°-line scanning, 67.5°/90°- rotation scanning). Surface topography, roughness, microstructure and microhardness were assessed to characterize the material anisotropy of SLMed titanium alloy. The machining results showed that the anisotropic mechanical properties and microstructure feature of the Ti-6Al-4V alloys are the fundamental reasons for the anisotropic machining performance in terms of cutting force and surface roughness. The machining properties of SLMed Ti-6Al-4V alloys are affected by the microstructure, machining surfaces, cutting directions and cutting parameters. Both the magnitude and fluctuation of dynamic cutting force produced on the front surfaces are obviously larger than those generated on the top surfaces. Significant improvement in surface roughness ranging from Sa = 80–100 nm could be achieved along the laser scanning direction for 0°-line SLMed Ti-6Al-4V sample when cutting depth was from 1 to 15 μm at vc = 50 mm/min. In addition, some typical SLMed defects appear on the machined surface and produced chips. This research is applicable to assist manufacturers in choosing the appropriate machining method for SLMed components in ultra-precision machining.

The effects of trace MoSi2 addition on the microstructure evolution, mechanical properties and fracture behavior of Ti–6Al–4V wall via cold metal transfer additive manufacturing (CMTAM) were investigated. After the addition of trace MoSi2 powder, trace (β-Ti, Mo) phase and SiO2 particles were obtained and partly prior-β→α’ phase transformation was suppressed. Compared with the as-built Ti–6Al–4V wall, the prior-β grains changed from columnar to the equiaxed or near-equiaxed after the addition of trace MoSi2. The tensile analysis result revealed that the addition of trace MoSi2 could improve the average strain while reduce anisotropy. All specimens showed dimples corresponding to ductile failure mode. The possible thermal cycles for the trace-MoSi2-addition specimens during the CMTAM process were analyzed.

This study investigated the effects of dendrite axis and fusion boundary (FB) on the stress corrosion cracking (SCC) of 308 L/304 L welds by using an alternating current potential drop (ACPD) technique to measure the SCC growth rates in a simulated boiling water reactor environment. The results show that the ferrite/austenite interfaces are more susceptible to SCC in the SS 308 L welds. Furthermore, the angle between the applied load and the dendrite axis affects the SCC growth rate, and as this angle approached 90°, the SCC crack growth rate increases. The SCC cracks in the heat affected zone (HAZ) are mainly intergranular and some cracks propagate transgranularly. Furthermore, the primary crack in the HAZ propagates along the FB; when reaching FB, some secondary cracks are arrested at the FB. The residual strain caused by weld shrinkage is the crucial factor for the increase in SCC susceptibility in HAZ.

Abrasive grit blasting process is widely used in many industries. Cleanliness level of the blasted surface is a critical criterion in abrasive blasting process. Modelling of abrasive blasting process is important to understand the effect of blasting parameters, such as moving speed of the blasting gun, on blasting productivity and quality. Based on the assumption that blasting process is the kinematic energy exchange between the abrasive grits and the removed material from workpiece surface, cleanliness level is modelled by the total energy consumed on the elemental blasted surface for given blasting parameters. Furthermore, as the moving speed affects the energy distribution on the surface, the effect of moving speed of the blasting gun on cleanliness level is analysed. According to the required surface cleanliness level (For example, the required surface quality in shipyard is SA 2.5), the effective productivity is calculated, which can guide the user to select the proper moving speed to improve the productivity and reduce the wastage of the abrasive grits. Finally, the proposed model is validated by experiments, and the result shows a good agreement between the predicted and measured results.

Lattice structures are broadly used in lightweight structure designs and multifunctional applications. Especially, with the unprecedented capabilities of additive manufacturing (AM) technologies and computational optimization methods, design of nonuniform lattice structures has recently attracted great research interests. To eliminate constraints of the common “ground structure approaches” (GSAs), a novel topology optimization-based method is proposed in this paper. Particularly, the structural wall thickness in the proposed design method was set as uniform for better manufacturability. As a solution to carry out the optimized material distribution for the lattice structure, geometrical size of each unit cell was set as design variable. The relative density model, which can be obtained from the solid isotropic microstructure with penalization (SIMP)-based topology optimization method, was mapped into a nonuniform lattice structure with different size cells. Finite element analysis (FEA)-based homogenization method was applied to obtain the mechanical properties of these different size gradient unit cells. With similar mechanical properties, elements with different “relative density” were translated into unit cells with different size. Consequently, the common topology optimization result can be mapped into a nonuniform lattice structure. This proposed method was computationally and experimentally validated by two different load-support design cases. Taking advantage of the changeable surface-to-volume ratio through manipulating the cell size, this method was also applied to design a heat sink with optimum heat dissipation efficiency. Most importantly, this design method provides a new perspective to design nonuniform lattice structures with enhanced functionality and manufacturability.

Cellular structures are broadly applicable to lightweight design and multifunctional applications. Especially, with unprecedented fabrication freedom provided by additive manufacturing (AM), design and optimization of nonuniform cellular structures have recently attracted great research interests. Topology optimization is one of the most powerful tools to obtain the optimized material distribution, and much research have been conducted to optimize cellular structures with the help of this optimization technique. In general, the optimized cellular structure is generated based on a predefined ground structure, and thickness of each strut is then decided based on the optimization result. However, many existing studies did not consider the constraints of AM processes, such as some generated struts may be too thin to be manufactured. Besides, only load support structure was considered in these studies. Other applications, such as heat dissipation or energy absorption, were rarely researched. In this paper, a novel cellular structure design method, which considered both functionality and manufacturability, is proposed. Different from other methods, wall thickness of the structure was set as a constant. To get the optimized material distribution, variable cell sizes were applied. Because of uniform wall thickness, the smaller the unit cell is, the higher its volume fraction will be. By mapping small unit cells to high density area and large cell to low density area, the final optimized cellular structure can be generated. In addition, because smaller unit cells have higher surface-to-volume ratio, this method can also be applied to solve heat transfer problem. Two examples, minimum compliance design of a cantilever beam and maximum heat dissipation efficiency design of a CPU heat sink, were conducted to validate the proposed method.

Design documents and design project footprints accumulated by corporate information technology systems have increasingly become valuable sources of evidence for design information and knowledge management. Identification and extraction of such embedded information and knowledge into a clear and usable format will greatly accelerate continuous learning from past design efforts for competitive product innovation and efficient design process management in future design projects. Most of the existing design information extraction systems focus on either organizing design documents for efficient retrieval or extracting relevant product information for product optimization. Different from traditional systems, this paper proposes a methodology of learning and extracting useful knowledge using past design project documents from design process perspective based on process mining techniques. Particularly different from conventional techniques that deal with timestamps or event logs only, a new process mining approach that is able to directly process textual data is proposed at the first stage of the proposed methodology. The outcome is a hierarchical process model that reveals the actual design process hidden behind a large amount of design documents and enables the connection of various design information from different perspectives. At the second stage, the discovered process model is analyzed to extract multifaceted knowledge patterns by applying a number of statistical analysis methods. The outcomes range from task dependency study from workflow analysis, identification of irregular task execution from performance analysis, cooperation pattern discovery from social net analysis to evaluation of personal contribution based on role analysis. Relying on the knowledge patterns extracted, lessons and best practices can be uncovered which offer great support to decision makers in managing any future design initiatives. The proposed methodology was tested using an email dataset from a university-hosted multiyear multidisciplinary design project.

Mechanical systems with adaptable functions are versatile in functionalities and compact in physical structure than ordinary ones, hence are useful in many industrial and agricultural applications. One aspect of design analysis for these systems is the analysis of functional coupling degree among the adaptable functions, because this is a measurement of how compact and material-effective (thus cost-effective) the systems are. Existing work on functional coupling is mainly oriented to multiple-function systems rather than adaptable-function systems, where the former owes multiple functions without the need of adjustment or replacement of system components. The purpose of this paper is to investigate the methodologies for the evaluation of functional coupling and component importance of adaptable-function systems, so as to provide support for the development of this kind of mechanical systems. To this end, the function-component dependency is investigated first by exploiting the methods for design change propagation, whereby a change possibility matrix is proposed and calculated, and a function-component incidence matrix is developed. Based on the incidence matrix, the functional coupling degree is evaluated to measure the coupling between individual functions, and a comprehensive coupling degree is evaluated to measure the functional coupling of the entire system. These results are then used for the evaluation of component utilization and component importance. Finally, a design case of an adaptable-function juicing machine is studied to illustrate the proposed methods as well as the related concepts.

It is widely agreed that environmental issues, from climate change to energy and water scarcity, to over exploitation of natural resources, represent critical challenges for the society. Thereby, industry has progressively adopted lean manufacturing by reducing amount of energy and materials used in the production. However, manufacturer has limitation towards improving product efficiency without feedback from user as a close loop. Knowing the complexity of environmental issues and economy changes, this paper introduces a new system framework that takes the holistic approach by capturing information at end-of-life (EoL) and feeding back to design or manufacturing in making a greener product. With complete understanding of EoL product status, it enables OEMs to develop technology diversely and at the same time rapidly incorporating environmental concept in part of the product chain. For instance, the valuable knowledge learned in EoL product put forward a more efficient way for product maintenance by cutting down time, cost and negative impact to the environment. Moreover, a greater reliable product could be achieved by utilizing appropriate material or design in particular product. This resulted in improved product design as an inherent loop in product life cycle, therefore producing greener product for better reusability, remanufacturability and recyclability. Overall, efficient EoL product recovery system enables sustainable and competitive manufacturing, and thus drives the economy growth.

To ensure that the economic and environmental impact over the entire product life cycle is taken into consideration during the design process, an integrated life cycle approach to Design for Environment (DfE) must be taken. In this paper, we describe the application of the product structure-based methodology for integrated life cycle analysis as a DfE decision-support tool. While maintaining an integrated perspective of the product life cycle, this methodology modularises the product life cycle model to the individual parts of the product structure; thus, allowing product designers to analyse the parts independently from the rest of the product system and enabling them to systematically evaluate the design alternatives. Using a case study on a dive torchlight, we demonstrate how through our proposed methodology, design alternatives for the product can be evaluated based on the life cycle eco-efficiency.

Digital prototypes (DPs) allow designers to communicate design concepts to users by rendering physical characteristics of the concepts. To enhance user understanding of the concepts, it is important that the users be able to make better estimates of the values of the characteristics. Correctness of the estimates can depend on two crucial factors: the ability of DPs to render the physical characteristics and the way the DPs are used to communicate the physical characteristics. However, little attention has been paid to the latter. A DP can be used in different ways, e.g., it can be projected on different backgrounds, or be manipulated using different input/output devices. Hence, it is important to identify an effective way of using DPs, via an assessment of the effectiveness of various ways. This paper introduces a methodology for evaluating the effectiveness of communication of physical characteristics to users using DPs. The methodology is used to assess the degree to which users can correctly and quickly estimate the values of the characteristics through interactions with DPs. Such assessments are then analyzed with statistical methods and hypothesis tests to reveal the effectiveness. To validate the proposed methodology, the size of hand-held electronic consumer products, such as smartphones, is considered in a case study. In the study, the effectiveness of two communication setups is evaluated. The same DP is used in both setups, while the environments and input devices are different. The experimental results show that the evaluated effectiveness can reflect how successful the setups are, and can help select the best way of using the DP, i.e., by providing a better environment, a better input device, or a combination of both.

Developing new generation wearable electronics with skin-like stretchability and conformability has become the research hotspot in many areas, such as bio-sensoring, communication and robotics. In this study, a novel design and manufacturing method was proposed to develop wearable electronics, which could perform a similar deformation as the target skin surface during the rotation of joint. Considering the nonuniform auxetic deformation behaviour of the skin around joint areas, the designed electronics should also have the same Poisson's ratio (PR) distribution. Re-entrant honeycomb structure was chosen to obtain tuneable PR, by changing the interior angel of each unit cell. By mapping unit cells with different PR to the target surface, the obtained structure would have the same mechanical property and deformation behaviour as the covered skin. Consequently, there would be little sheer stress at the connection areas between wearable electronics and human skin, which would surely increase the attachment stability. Besides, the conformability of the device could also be generated. PloyJet process was introduced to fabricate the flexible substrate, and silver ink was printed directly on the substrate with direct-ink-writing (DIW) technology. Conductive wire with 'wavy' structure was manufactured by this PolyJet-DIW process, and it had shown a much better stretchability than the common straight-line structure. Furthermore, wearable electronics that suitable for a person-specific elbow was developed. Both the conformability and conductivity were tested, and all results had shown much better performance than traditional wearable electronics with uniform structures.

This paper presents a methodology of proposing a platform differentiation plan (PDP) to provide a platform leverage strategy across market niches. PDP is designed to provide a consistent balance between mutual differentiation and components sharing for the leveraged platforms at the early product planning stage. Two indices, i.e. differentiation index (DI) and commonality opportunity index (COI), are presented to represent the dimensions of product platform differentiation and commonality, respectively. Through a case study of electronic test equipment (ETE), the usefulness of PDP for the platform leverage strategy across market niches is demonstrated.

Concurrently engineered product development requires effective inter-functional communication and knowledge sharing across multidisciplinary teams and heterogeneous processes. This paper presents a semantics-enabled approach to the integration of knowledge maps with design process configurations to support more meaningful communication and seamless collaboration between cross-functional teams and concurrent workflows in new product introduction (NPI) processes. The proposed approach focuses on: explicit and formalized process description and configuration of NPI activities; process knowledge capture and reuse through knowledge maps; integration of knowledge maps into design process configurations; and ontology-based process model mapping and knowledge sharing to support seamless process collaboration. It thereby contributes to the development of the next generation concurrent engineering methodologies in order to achieve NPI process advances for meaningful inter-functional communication and collaboration. The approach has been implemented in a software prototype to provide the concurrently engineered product development with the capabilities of semantic process description and configuration, knowledge reuse, and process collaboration.

The problem of controlling the average resultant cutting force together with the contour error in multi-dimensional end milling operations is considered in this study. Two sets of neural networks are used in the control system. The first set is used to specify the feed rate to maintain a desired cutting force. This feed rate is resolved along the feed axes using a parametric interpolation algorithm so that the desired part shape is obtained. The second set is used to make corrections to the feed rate components specified by the parametric interpolation algorithm to minimize the contour error caused by the dynamic lag of the closed-loop servo systems controlling the feed drives. In addition, the control system includes a feedforward input to compensate for static friction effects. Experimental results are presented for machining two-dimensional circular slots and a three-dimensional spherical surface to show the validity of the proposed approach.

This paper addresses the methodology development for achieving one of the important functions in automated process planning: automated determination of sequence of machining operations for prismatic parts containing various types of form features. A framework of using the case-based reasoning approach to support learning capability in operation sequencing is first proposed. The methodology to accomplish various issues in case-based operation sequencing is then discussed. In particular, the following issues are considered: 1. Representation of operation sequencing cases. 2. Indexing and retrieval of operation sequencing cases. 3. Adaptation of operation sequencing cases. Finally, the implementation issues are addressed and the learning functions of the intelligent operation sequencing system are demonstrated.

There are many fabrication processes in modern manufacturing, but current modeling and simulation tools only simulate a few unit processes based on different geometry models. To overcome the data exchange problem between different models, this paper studies various in-process geometry models together with their working systems / prototypes for traditional manufacturing processes. Novel hybrid multiple-machining and layered manufacturing processes are presented to identify critical issues. Working towards a vision of pervasive modeling and simulation, a unified Voxel-based in-process geometry model for multiple-machining and layered manufacturing simulations is proposed and discussed.Copyright © 2005 by ASME