Showing papers in "The International Journal of Advanced Manufacturing Technology in 2020"

Review of tool condition monitoring in machining and opportunities for deep learning

Abstract: Tool condition monitoring and machine tool diagnostics are performed using advanced sensors and computational intelligence to predict and avoid adverse conditions for cutting tools and machinery. Undesirable conditions during machining cause chatter, tool wear, and tool breakage, directly affecting the tool life and consequently the surface quality, dimensional accuracy of the machined parts, and tool costs. Tool condition monitoring is, therefore, extremely important for manufacturing efficiency and economics. Acoustic emission, vibration, power, and temperature sensors monitor the stability and efficiency of the machining process, collecting large amounts of data to detect tool wear, breakage, and chatter. Studies on monitoring the vibrations and acoustic emissions from machine tools have provided information and data regarding the detection of undesirable conditions. Herein, studies on tool condition monitoring are reviewed and classified. As Industry 4.0 penetrates all manufacturing sectors, the amount of manufacturing data generated has reached the level of big data, and classical artificial intelligence analyses are no longer adequate. Nevertheless, recent advances in deep learning methods have achieved revolutionary success in numerous industries. Deep multi-layer perceptron (DMLP), long-short-term memory (LSTM), convolutional neural network (CNN), and deep reinforcement learning (DRL) are among the most preferred methods of deep learning in recent years. As data size increases, these methods have shown promising performance improvement in prediction and learning, compared to classical artificial intelligence methods. This paper summarizes tool condition monitoring first, then presents the underlying theory of some of the most recent deep learning methods, and finally, attempts to identify new opportunities in tool condition monitoring, toward the realization of Industry 4.0.

A review on 3D printed matrix polymer composites: its potential and future challenges

Abstract: Additive Manufacturing technology has a significant impact on the modern world because of its ability to fabricate highly complex computerized geometrics. Pure 3D-printed polymer parts have limited potential applications due to inherently inferior mechanical and anisotropic properties. For more utilization and versatility, the addition of fillers has enhanced their functionalities. 3D printing has innovative advantages including low cost, minimal wastage, customized geometry, and ease of material change. This review reveals the development of 3D printing techniques of matrix composite materials with improving properties and their applications in the fields of aerospace, automotive, biomedical, and electronics. A general introduction is given on AM techniques mainly fused deposition modeling (FDM), Powder-liquid 3D printing (PLP), selective laser sintering (SLS), stereolithography (SLA), digital light processing (DLP), and robocasting. Process methodologies and behavior of different filler additives, reinforcement fibers, nanoparticles, and ceramic polymer composites are discussed. Also, some major issues of difficulty including printing parameters, homogeneous desperation of fillers, nozzle clogging due to filler aggregation, void formation, augmented curing time, and anisotropic attributes are addressed. In the end, some capabilities and shortcomings are pointed out for further development of 3D-printing technology.

Review of defects in lattice structures manufactured by powder bed fusion

Abstract: Additively manufactured lattice structures are popular due to their desirable properties, such as high specific stiffness and high surface area, and are being explored for several applications including aerospace components, heat exchangers and biomedical implants. The complexity of lattices challenges the fabrication limits of additive manufacturing processes and thus, lattices are particularly prone to manufacturing defects. This paper presents a review of defects in lattice structures produced by powder bed fusion processes. The review focuses on the effects of lattice design on dimensional inaccuracies, surface texture and porosity. The design constraints on lattice structures are also reviewed, as these can help to discourage defect formation. Appropriate process parameters, post-processing techniques and measurement methods are also discussed. The information presented in this paper contributes towards a deeper understanding of defects in lattice structures, aiming to improve the quality and performance of future designs.

A review on in situ monitoring technology for directed energy deposition of metals

Abstract: Directed energy deposition (DED) is an important additive manufacturing method for producing or repairing high-end and high-value equipment Meanwhile, the lack of reliable and uniform qualities is a key problem in DED applications With the development of sensing devices and control systems, in situ monitoring (IM) and adaptive control (IMAC) technology is an effective method to enhance the reliability and repeatability of DED In this paper, we review current IM technologies in IMAC for metal DED First, this paper describes the important sensing signals and equipment to exhibit the research status in detail Meanwhile, common problems that arise when gathering these signals and resolvent methods are presented Second, process signatures obtained from sensing signals and transfer approaches from sensing signals for processing signatures are shown Third, this work reviews the developments of the IM of product qualities and illustrates ways to realize quality monitoring Lastly, this paper specifies the main existing problems and future research of IM in metal DED

A review of technological improvements in laser-based powder bed fusion of metal printers

Abstract: Additive manufacturing (AM) is an emerging process that has been extremely improved in terms of technology and application in recent years. In this technology review, new industrial improvements in laser powder bed fusion (LPBF) of metals are discussed. LPBF has the lowest build rate among all AM processes that produce metals such as electron beam powder bed fusion, direct energy deposition, binder jetting and sheet lamination. The findings of the current research show that the most innovations and future directions of LPBF printers are toward increasing the speed of the process by using interchangeable feedstock chamber, closed-loop control powder handling, automated powder sieving, multi-layer concurrent printing, 2-axis coating and multi powder hoppers. To increase the speed of the process, the new improvements for transferring time and using fast lasers are presented. Another innovation in the building of LPBF printers is enhancing part quality by improving lasers with the shorter beam diameter, multi-lasers, uniform inert gas flow, accurate positioning systems, using high vacuum systems and using sensors and automation.

Milling force and surface morphology of 45 steel under different Al2O3 nanofluid concentrations

Abstract: Nanofluid minimum quantity lubrication (NMQL) is a resource-saving, environment-friendly, and efficient green processing technology. Cottonseed oil can form a strong lubricating film owing to its abundant saturated fatty acids and monounsaturated fatty acids, which have excellent lubricating properties. The physical and chemical properties of nanofluids change when Al2O3 nanoparticles are added. However, the effects of cottonseed oil–based Al2O3 nanofluid concentrations on the milling force and workpiece surface quality remain unclear. To address this limitation, 45 steel was used to conduct NMQL milling experiments of cottonseed oil–based Al2O3 nanofluids with different mass fractions. Results showed that the minimum milling force was obtained at a concentration of 0.2 wt% (Fx = 58 N, Fy = 12 N). The minimum surface roughness value (Ra = 1.009 μm, RSm = 0.136 mm) was obtained at a mass concentration of 0.5 wt%, and the micromorphology of the workpiece/chip was optimal.

Integration of Lean practices and Industry 4.0 technologies: smart manufacturing for next-generation enterprises

Abstract: Industry 4.0 technologies have attempted to transform current industrial settings to a level that we have never seen before. While at the same time, prevailing applications of Lean tools and techniques over the last 20 years have already dramatically reduced wastes ranging from shop floor production to cross-functional enterprise processes. This paper aims to provide a comprehensive review and report on links between Lean tools and Industry 4.0 technologies, and on how simultaneous implementation of these two paradigms affects the operational performance of factories. The existing and potential enhancements of Lean practices enabled by Industry 4.0 technologies such as wireless networks, big data, cloud computing, and virtual reality (VR) will also be explored. A cloud-based Kanban decision support system is also presented as a real-world demonstrator for integration of an Industry 4.0 technology (cloud computing) and a major Lean tool (Kanban).

Digital twin-based cyber physical production system architectural framework for personalized production

Abstract: Personalized production is a manufacturing concept relevant to the fourth industrial revolution, which can satisfy various customer needs inexpensively. There are three main hurdles to the efficient implementation of this concept: access, cost, and performance. This paper proposes a digital twin-based cyber physical production system (CPPS) architectural framework that overcomes the performance hurdle. The proposed architectural framework comprises five services that are solutions to the performance hurdle of personalized production, and it operates on information based on the proposed product, process, plan, plant, and resource (P4R) information model. This information model is manufacturing abstraction for personalized production and is presented on a detailed level with object-orientation and the “type and instance” concept. Whereas previous studies on the digital twin concept considered one or several facilities and focused on the development of independent applications, this study focuses on the digital twin as a core technological element of the entire system and analyzes CPPS design and its operation from the system-of-systems perspective. The application of the digital twin-based CPPS to a micro smart factory (MSF) provides an advanced solution for the personalized production of various products. An average makespan improvement of ~ 26.87% was achieved using the implemented CPPS services in the MSF.

Microstructure and mechanical properties of 316L austenitic stainless steel processed by different SLM devices

Abstract: In this work, we examined the influence of different types of selective laser melting (SLM) devices on the microstructure and the associated material properties of austenitic 316L stainless steel. Specimens were built using powder from the same powder batch on four different SLM machines. For the specimen build-up, optimized parameter sets were used, as provided by the manufacturers for each individual SLM machine. The resulting microstructure was investigated by means of scanning electron microscopy, which revealed that the different samples possess similar microstructures. Differences between the microstructures were found in terms of porosity, which significantly influences the material properties. Additionally, the build-up direction of the specimens was found to have a strong influence on the mechanical properties. Thus, the defect density defines the material’s properties so that the ascertained characteristic values were used to determine a Weibull modulus for the corresponding values in dependence on the build-up direction. Based on these findings, characteristic averages of the mechanical properties were determined for the SLM-manufactured samples, which can subsequently be used as reference parameters for designing industrially manufactured components.

Tensile properties and microstructural features of 304L austenitic stainless steel produced by wire-and-arc additive manufacturing

Abstract: Additive manufacturing (AM) has gained great importance in the recent development to produce metallic structural elements for civil engineering applications. However, research effort has been focused mainly on powder-based processes, while there is still limited knowledge concerning the structural response of wire-and-arc additive manufactured (WAAM) metallic elements, and very few experimental data concerning their mechanical properties. This paper presents the first results of a wide experimental campaign aimed at assessing the mechanical properties of WAAM plates produced using a commercial ER308LSi stainless steel welding wire. The aim is to evaluate the effect of the orientation in the tensile behavior of planar elements considering specimens extracted along three different directions with respect to the deposition layer: transversal direction (T), longitudinal direction (L), and diagonal direction (D). Compositional, microstructural, and fractographic analyses were carried out to relate the specific microstructural features induced by WAAM to the mechanical properties. The results show that the chemical composition of the plates meets the requirements of UNS-S-30403 for an AISI 304L austenitic stainless steel. The as-built samples were substantially defect-free and characterized by a very fine microstructure of γ and δ phases The fineness of the microstructure and the negligible defect content led to values of tensile strength and elongation to failure in line with the traditionally manufactured stainless steel elements. Anisotropy in the tensile properties between T, L, and D specimens was observed, and the highest elastic and plastic properties were measured in D specimens. This result is related to the crystallographic and mechanical fibering induced by the additive process, that led also, in case of D samples, to the highest density of cell boundaries, obstacles to the dislocation slip, located at 45° with respect to the loading direction, where plastic deformation preferentially occurs.

A conceptual framework to evaluate human-robot collaboration

Abstract: Human-Robot Collaboration (HRC) is a form of direct interaction between humans and robots. The objective of this type of interaction is to perform a task by combining the skills of both humans and robots. HRC is characterized by several aspects, related both to robots and humans. Many works have focused on the study of specific aspects related to HRC, e.g., safety, task organization. However, a major issue is to find a general framework to evaluate the collaboration between humans and robots considering all the aspects of the interaction. The goals of this paper are the following: (i) highlighting the different latent dimensions that characterize the HRC problem and (ii) constructing a conceptual framework to evaluate and compare different HRC configuration profiles. The description of the methodology is supported by some practical examples.

The effect of processing parameters on the mechanical characteristics of PLA produced by a 3D FFF printer

Abstract: 3D printing by fused filament fabrication (FFF) provides an innovative manufacturing method for complex geometry components. Since FFF is a layered manufacturing process, effects of process parameters are of concern when plastic materials such as polylactic acid (PLA), polystyrene and nylon are used. This study explores how the process parameters, e.g. build orientation and infill pattern/density, affect the mechanical response of PLA samples produced using FFF. Digital image correlation (DIC) was employed to get full-field surface-strain measurements. The results show the influence of build orientation and infill density is significant. For on-edge orientation, the tensile strength and Young’s modulus were 55 MPa and 3.5 GPa respectively, which were about 91% and 40% less for the upright orientation, demonstrating a significant anisotropy. The tensile strength and Young’s modulus increased with increasing infill density. In contrast, different infill patterns have no significant effect. Considering the influence of build orientation, based on the experimental results, a constitutive model derived from the laminate plate theory was employed. The material parameters were determined by tensile tests. Results demonstrated a reasonable agreement between the experimental data and the predictive model. Similar anisotropy to tension was observed in shear tests; shear modulus and shear strength for 45° flat orientation were about 1.55 GPa and 36 MPa, whereas for upright specimens they were about 0.95 GPa and 18 MPa, respectively. The findings provide a framework for systematic mechanical characterisation of 3D-printed polymers and potential ways of choosing process parameters to maximise performance for a given design.

Information modeling for cyber-physical production system based on digital twin and AutomationML

Abstract: Production systems play an important role in intelligent manufacturing. A large number of manufacturing resources are designed and developed with virtual (digital) ones, which will be associated with the physical ones throughout their lifecycle. With the recent emergence of information and communications technologies (ICTs), such as internet of things, big data, virtual reality, artificial intelligence, and 5G, the interconnection and interaction between physical resources and virtual ones become possible in production systems. Digital twin (DT) shows great potential to realize the cyber-physical production system (CPPS) in the era of Industry 4.0. In this paper, we present our vision on integrating various physical resources into CPPS via DT and AutomationML. To elaborate on how to apply ICTs, this paper firstly explores a generic architecture of CPPS based on DT. DT is a virtual and authoritative representation of physical manufacturing resource, since DT includes various models and manufacturing big data of resource. The proposed architecture is illustrated in detail as follows: (1) physical layer, (2) network layer, (3) virtual layer, and (4) application layer. A case of expert fault diagnose for aircraft engine is presented using the proposed information fusion in the architecture. Secondly, this paper proposes an approach of information modeling for CPPS based on AutomationML. Various manufacturing services can be encapsulated and defined in the standardized format (AutomationML), and then the corresponding virtual manufacturing resources (DTs) will be integrated into CPPS. Finally, this paper describes a case of information modeling for blisk machining and demonstrates the modeling approach in real-life scenarios for support manufacturing resource sharing via DT. Furthermore, the conclusion and further work is briefly summarized.

Additive manufacturing of WC-Co hardmetals: a review

Abstract: WC-Co hardmetals are widely used in wear-resistant parts, cutting tools, molds, and mining parts, owing to the combination of high hardness and high toughness. WC-Co hardmetal parts are usually produced by casting and powder metallurgy, which cannot manufacture parts with complex geometries and often require post-processing such as machining. Additive manufacturing (AM) technologies are able to fabricate parts with high geometric complexity and reduce post-processing. Therefore, additive manufacturing of WC-Co hardmetals has been widely studied in recent years. In this article, the current status of additive manufacturing of WC-Co hardmetals is reviewed. The advantages and disadvantages of different AM processes used for producing WC-Co parts, including selective laser melting (SLM), selective electron beam melting (SEBM), binder jet additive manufacturing (BJAM), 3D gel-printing (3DGP), and fused filament fabrication (FFF) are discussed. The studies on microstructures, defects, and mechanical properties of WC-Co parts manufactured by different AM processes are reviewed. Finally, the remaining challenges in additive manufacturing of WC-Co hardmetals are pointed out and suggestions on future research are discussed.

A review of prognostics and health management of machine tools

Abstract: This paper presents a survey of the applications of prognostics and health management maintenance strategy to machine tools. A complete perspective on this Industry 4.0 cutting-edge maintenance policy, through the analysis of all its preliminary phases, is given as an introduction. Then, attention is given to prognostics, whose different approaches are briefly classified and explained, pointing out their advantages and shortcomings. After that, all the works on prognostics of machine tools and their main subsystem are reviewed, highlighting current open research areas for improvement.

Wire and arc additive manufacturing of metal components: a review of recent research developments

Abstract: Wire arc additive manufacturing (WAAM) is an important metal 3D printing method, which has many advantages, such as rapid deposition rate, low cost, and suitability for large complex metal components manufacturing, and it has received extensive attention. This paper summarizes the research developments of WAAM in recent years, including the WAAM-suitable metal materials and processing technology, deposition strategy optimization including slicing and path planning algorithm, multi-sensor monitoring and intelligent control, and the large complex metal components manufacturing technology. The promising development directions of WAAM are prospected, including the research of new materials and new technology, composite manufacturing, multi-sensor and real-time monitoring, algorithmic optimization of metal filling strategy, and the application of artificial intelligence technology in WAAM, etc.

Concept and validation of an active cooling technique to mitigate heat accumulation in WAAM

Abstract: This work aimed at introducing and exploring the potential of a thermal management technique, named as near-immersion active cooling (NIAC), to mitigate heat accumulation in Wire + Arc Additive Manufacturing (WAAM). According to this technique concept, the preform is deposited inside a work tank that is filled with water, whose level rises while the metal layers are deposited. For validation of the NIAC technique, Al5Mg single-pass multi-layer linear walls were deposited by the CMT® process under different thermal management approaches. During depositions, the temperature history of the preforms was measured. Porosity was assessed as a means of analyzing the potential negative effect of the water cooling in the NIAC technique. The preform geometry and mechanical properties were also assessed. The results showed that the NIAC technique was efficient to mitigate heat accumulation in WAAM of aluminum. The temperature of the preforms was kept low independently of its height. There was no measurable increase in porosity with the water cooling. In addition, the wall width was virtually constant, and the anisotropy of mechanical properties tends to be reduced, characterizing a preform quality improvement. Thus, the NIAC technique offers an efficient and low-cost thermal management approach to mitigate heat accumulation in WAAM and, consequently, also to cope with the deleterious issues related to such emerging alternative of additive manufacturing.

Selective laser melting (SLM) of AISI 316L—impact of laser power, layer thickness, and hatch spacing on roughness, density, and microhardness at constant input energy density

Abstract: In selective laser melting (SLM) the variation of process parameters significantly impacts the resulting workpiece characteristics. In this study, AISI 316L was manufactured by SLM with varying laser power, layer thickness, and hatch spacing. Contrary to most studies, the input energy density was kept constant for all variations by adjusting the scanning speed. The varied parameters were evaluated at two different input energy densities. The investigations reveal that a constant energy density with varying laser parameters results into considerable differences of the workpieces’ roughness, density, and microhardness. The density and the microhardness of the manufactured components can be improved by selecting appropriate parameters of the laser power, the layer thickness, and the hatch spacing. For this reason, the input energy density alone is no indicator for the resulting workpiece characteristics, but rather the ratio of scanning speed, layer thickness, or hatch spacing to laser power. Furthermore, it was found that the microhardness of an additively manufactured material correlates with its relative density. In the parameter study presented in this paper, relative densities of the additively manufactured workpieces of up to 99.9% were achieved.

Influence of heat treatment temperature on the microstructural, mechanical, and wear behavior of 316L stainless steel fabricated by laser powder bed additive manufacturing

Abstract: A metal component fabricated by additive manufacturing (AM) is generally required to be heat treated to enhance microstructural and mechanical aspects. This present study aims to contribute to the literature in understanding the effect of heat treatment and various heat treatment temperatures on as-built components fabricated by AM. In this study, various heat treatment temperatures were applied to 316L stainless steel specimens produced by selective laser melting (SLM) and the effects on the microstructure, microhardness, XRD response, porosity, and wear behavior were investigated. The microhardness, XRD, and wear response of SLM 316L were compared with those of wrought 316L. The results illustrate that the heat treatment temperature has a substantial effect on the evolution of microstructure, XRD response, and porosity. Our results also support the argument that the effect of porosity on wear behavior is more dominant than the effect on microhardness. It should also be noted that the wrought 316L stainless steel specimen shows much better wear resistance than SLM 316L specimen.

Wire arc additive manufacturing of high-strength low alloy steels: study of process parameters and their influence on the bead geometry and mechanical characteristics

Abstract: Additive manufacturing (AM) is becoming increasingly popular since it offers flexibility to produce complex designs with less tooling and minimum material at shorter lead times. Wire arc additive manufacturing (WAAM) is a variant of additive manufacturing which allows economical production of large-scale and high-density parts. The WAAM process has been studied extensively on different steels; however, the influence of process parameters, specifically wire feed speed (WFS), travel speed (TS), and their ratio on bead geometry, microstructure, and mechanical properties, are yet to be studied. The present work aims at closing this gap by using the WAAM process with robotic cold metal transfer (CMT) technology to manufacture high-strength structural steel parts. For that purpose, single-bead welds were produced from HSLA steel by varying WFS between 5 and 10 m/min and the WFS to TS ratio between 10 and 20. Those variations produce heat inputs in the range of 266–619 J/mm. The results have shown that the wire feed speed to travel speed ratio is the major parameter to control the heat input. Increasing heat input increases characteristic bead dimension, whereas it reduces the hardness. In the second part of experiments, two single-bead walls were deposited via the parallel deposition strategy and one multiple-bead wall was produced using the oscillation strategy. The tensile properties were tested along two directions: parallel and perpendicular to deposition directions. For the yield strength and tensile strength, the difference between horizontally and vertically tested specimens was smaller than the standard deviations. On the other hand, the total and uniform elongation values exhibit up to 10% difference in the test direction, indicating anisotropy in ductility. Those tensile properties were attributed to repeated thermal cycles during the WAMM process, which can cause heat transfer in multiple directions. The yield strength of the multiple-bead wall produced via oscillation was lower, whereas its ductility was higher. The tensile properties and hardness differences were found to correlate well with the microstructure.

Digital twin: current scenario and a case study on a manufacturing process

Abstract: In the current scenario, industries need to have continuous improvement in their manufacturing processes. Digital twin (DT), a virtual representation of a physical entity, serves this purpose. It aims to bridge the prevailing gap between the design and manufacturing stages of a product by effective flow of information. This article aims to create a state-of-the-art review on various DTs with their application areas. The article also includes schematic representations of some of the DTs proposed in various fields. The concept is also represented by a case study based on a DT model developed for an advanced manufacturing process named friction stir welding. Towards the end, a model for implementing DT in a factory has been proposed.

Recent development of improved clinching process

Abstract: Clinching technology has been widely applied in automobile assembly industries to join sheet materials of different thicknesses and properties. It does not require any auxiliary parts and only depends on the plastic deformation of materials themselves to form a joint. Furthermore, clinching tools that include the punch and the die are simpler than other thermal joining methods. However, the usability of the clinched joint is restricted by a low joining strength. In order to expand the application range of clinching technologies, researchers have conducted extensive researches on how to improve clinching technologies. In this article, the latest advances of clinching technologies are reviewed on the development of clinching tools and processes. The improved clinching processes including flat clinching, hole clinching, reshaping the clinched joint without a rivet, reshaped joint with a rivet, rivet clinching, rectangular clinching, dieless clinching, roller clinching, laser shock clinching, hydro-clinching, injection clinching, adhesive clinching, resistance spot clinching, friction-assisted clinching, and laser-assisted clinching are introduced. The advantages and disadvantages of different clinching technologies are proposed. In addition, some suggestions for the future development of clinching technology are given in this paper. The clinching technology is developing towards a hybrid joining technology with high strength, high stability, and high efficiency.

From tolerance allocation to tolerance-cost optimization: a comprehensive literature review

Abstract: It is widely acknowledged that the allocation of part tolerances is a highly responsible task due to the complex repercussions on both product quality and cost. As a consequence, since its beginnings in the 1960s, least-cost tolerance allocation using optimization techniques, i.e. tolerance-cost optimization, was continuously in focus of numerous research activities. Nowadays, increasing cost and quality pressure, availability of real manufacturing data driven by Industry 4.0 technologies, and rising computational power result in a continuously growing interest in tolerance-cost optimization in both research and industry. However, inconsistent terminology and the lack of a classification of the various relevant aspects is an obstacle for the application of tolerance-cost optimization approaches. There is no literature comprehensively and clearly summarizing the current state of the art and illustrating the relevant key aspects. Motivated to overcome this drawback, this article provides a comprehensive as well as detailed overview of the broad research field in tolerance-cost optimization for both beginners and experts. To facilitate the first steps for readers who are less familiar with the topic, the paper initially outlines the fundamentals of tolerance-cost optimization including its basic idea, elementary terminology and mathematical formulation. These fundamentals serve as a basis for a subsequent detailed discussion of the key elements with focus on the different characteristics concerning the optimization problem, tolerance-cost model, technical system model and the tolerance analysis model. These aspects are gathered and summarized in a structured mind map, which equips the reader with a comprehensive graphical overview of all the various facets and aspects of tolerance-cost optimization. Beside this, the paper gives a retrospect of the past fifty years of research in tolerance cost-optimization, considering 290 relevant publications. Based thereon, current issues and future research needs in tolerance-cost optimization were identified.

Investigations of surface quality and energy consumption associated with costs and material removal rate during face milling of AISI 1045 steel

Abstract: Machining of AISI 1045 steel is prominent in several industries due to their good machining characteristics. In this study, the optimum conditions of fly (face) milling of parts made of AISI 1045 steel was analyzed. The generated surface quality, the cost of the cutting tool components, the energy consumption, the wearing of the cutting tool, and material removal rate are the main parameters in this study. Several cutting experiments over different cutting lengths have been conducted and analyzed statistically to determine the optimum targeted cutting conditions. A multilayer regression analysis was conducted on obtained experimental results and inducing non-linear mathematical equations with high coefficient of determination (R2 = 0.98). The influence of feed per tooth (fz), cutting speed (vc), flank wear (VB) to surface roughness (Rz), cutting power (Pc), material removal rate (MRR), sliding distance (ls), and the tool life (T/) has been considered. The overall results, estimated through Grey relational analysis (GRA), revealed that the optimum fly milling performance for a fast manufacturing (case 1) are obtained for feed per tooth fz = 0.25 mm/tooth, cutting speed vc = 392.6 m/min, and machined length l = 5 mm. While the optimum parameters for resource (tools) conservation (case 2) are feed per tooth fz = 0.125 mm/tooth, cutting speed vc = 392.6 m/min, and machined length l = 5 mm.

Milling chatter detection using scalogram and deep convolutional neural network

Abstract: In this paper, a novel approach of the real-time chatter detection in the milling process is presented based on the scalogram of the continuous wavelet transform (CWT) and the deep convolutional neural network (CNN). The cutting force signals measured from the stable and unstable cutting conditions were converted into two-dimensional images using the CWT. When chatter occurs, the amount of energy at the tooth passing frequency and its harmonics are shifted toward the chatter frequency. Hence, the scalogram images can serve as input to the CNN framework to identify the stable, transitive, and unstable cutting states. The proposed method does not require the subjective feature-generation and feature-selection procedures, and its classification accuracy of 99.67% is higher than the conventional machine learning techniques described in the existing literature. The result demonstrates that the proposed method can effectively detect the occurrence of chatter.

Machine learning and optimization for production rescheduling in Industry 4.0

Abstract: Along with the fourth industrial revolution, different tools coming from optimization, Internet of Things, data science, and artificial intelligence fields are creating new opportunities in production management. While manufacturing processes are stochastic and rescheduling decisions need to be made under uncertainty, it is still a complicated task to decide whether a rescheduling is worthwhile, which is often addressed in practice on a greedy basis. To find a tradeoff between rescheduling frequency and the growing accumulation of delays, we propose a rescheduling framework, which integrates machine learning (ML) techniques and optimization algorithms. To prove the effectiveness, we first model a flexible job-shop scheduling problem with sequence-dependent setup and limited dual resources (FJSP) inspired by an industrial application. Then, we solve the scheduling problem through a hybrid metaheuristic approach. We train the ML classification model for identifying rescheduling patterns. Finally, we compare its rescheduling performance with periodical rescheduling approaches. Through observing the simulation results, we find the integration of these techniques can provide a good compromise between rescheduling frequency and scheduling delays. The main contributions of the work are the formalization of the FJSP problem, the development of ad hoc solution methods, and the proposal/validation of an innovative ML and optimization-based framework for supporting rescheduling decisions.

The impact on the mechanical properties of multi-material polymers fabricated with a single mixing nozzle and multi-nozzle systems via fused deposition modeling

Abstract: Multi-material 3D printing and process parameters optimization using multiple extruders are the significant challenges of fused deposition modeling (FDM). This paper focuses on the filament extrusion method and presents a comparison of two modes: multi-material single mixing nozzle and multi-material multiple nozzles, thereby linking technology with the mechanical properties. Tensile testing specimens were printed in two different scenarios to validate the comparison: (1) multi-material multi-layered section printed using a multi in-out single mixing nozzle and (2) multi-material multi-layered section printed using a multiple extrusion nozzle within the same carriage. Both modes followed a rectilinear infill pattern and different material combinations. The material combinations implemented included ABS-HIPS, ABS-PLA, PLA- HIPS, and PLA-HIPS-ABS. A behavioral study was evaluated on the mechanical properties of these materials. The results provide a tool for selection on which type of mode is considered suitable for maximizing efficiency and performance to fabricate a multi-material 3D printed product.

Optimization of printing parameters in fused deposition modeling for improving part quality and process sustainability

Abstract: Additive manufacturing (AM) technology is capable of efficiently building complex shapes when compared with traditional manufacturing methods. Fused deposition modeling (FDM) is one of the AM processes, and it produces a great variety of polymeric parts. Therefore, it is essential to determine the relationship that exists among its process parameters, productivity and sustainability, quality of the final piece, and its structural performance. This paper presents an experimental study centered on optimizing five responses associated with FDM: energy consumption of the 3D printer, processing time, part's dimensional accuracy, the quantity of material used to print the pieces, and mechanical strength of the specimens. The model material employed was acrylonitrile styrene acrylate. The effects of five key process parameters on the responses were studied using the Taguchi methodology and analysis of variance (ANOVA). These parameters were layer thickness, filling pattern, orientation angle, printing plane, and position of the piece on the build platform. A desirability analysis was employed to determine the set of process parameters that provided the best trade-off among all the considered variables. The results showed that the approach presented in this work allowed for simultaneous optimization of all the observed variables for the 3D printing process.

Rolling element bearing fault diagnosis for rotating machinery using vibration spectrum imaging and convolutional neural networks

Abstract: In this paper, we propose a novel method for the classification of bearing faults using a convolutional neural network (CNN) and vibration spectrum imaging (VSI). The normalized amplitudes of the spectral content extracted from segmented temporal vibratory signals using a time-moving segmentation window are transformed into spectral images for training and testing of the CNN classifier. To show the efficiency of the proposed method, vibratory data for healthy and faulted bearings operating at different speeds are collected from an experimental test bench. The classification accuracy, variable load and speed testing, generalization, and robustness by adding noise to the collected data at different levels (SNR) are then evaluated. The obtained experimental classification results show excellent performance in terms of both accuracy and robustness.

Effect of print orientation and bronze existence on tribological and mechanical properties of 3D-printed bronze/PLA composite

Abstract: In this work, fused deposition modeling (FDM) technology is employed for manufacturing tribological and tensile testing specimens. The test pieces are fabricated in diverse directions to examine the influence of print orientation. The tribological tests are carried out in reciprocating sliding and under dry condition. Due to their relevance, the surface roughness and the hardness of the products are studied as well. Many images are captured under a microscope to better understand the surface morphology of 3D-printed parts before and after testing. The findings reveal that the existence of various print orientations determines differences in mechanical properties and tribological behavior. Among the investigated parameters, the one with the highest tensile strength at break point is the On-Edge print orientation. The vertically oriented test pieces offer the highest friction tendency but the lowest wear depth. Meanwhile, less wear is observed when sliding under low loads but the tendency for stick-slip phenomenon occurrence increases. Although PLA is presently one of the most popular filaments for 3D printing, it can be employed in some industrial applications (e.g., bushings and bearings), if the tribological properties are amended. Bronze is characterized by excellent sliding capability because of its very low metal-on-metal friction. To date, very limited attention has been given to research on the tribology of 3D-printed objects. Therefore, the purpose of the current work is to fill the gap in knowledge by being the first study to evaluate the impact of bronze presence and 3D printing orientation on the tribological properties of bronze/PLA composite.