This study explores the joining of AA6061-T6 aluminium alloy and AZ31B magnesium alloy using the Cold Metal Transfer (CMT) process with ER4043 aluminium filler wire. The influence of wire feed speed (WFS), welding speed (WS), and arc length correction (ALC) on weld bead geometry, microstructure, and mechanical properties of Al/Mg joints was investigated. The results indicate that WFS, WS, and ALC significantly affect weld characteristics. Increasing WFS leads to higher heat input, improving reinforcement height, penetration, and bead width. At 4700 mm/min WFS, optimal reinforcement height was achieved, while 5000 mm/min further enhanced penetration and bead width. Higher WS reduced heat input, resulting in narrower bead width, shallower penetration, and lower reinforcement height. ALC influenced arc behaviour, with 10% ALC minimising the weld metal area and 15% significantly increasing it. Microstructural analysis identified MgO, Mg solid solution, Mg2Al3, and Mg17Al12 at different joint regions. The optimized parameters (4700 mm/min WFS, 280 mm/min WS, 10% ALC) yielded the highest tensile strength of 34 MPa and hardness of 120 HV. Fracture occurred mainly at the Mg/weld interface and near the fusion line. This study underscores the importance of welding parameters in enhancing the mechanical properties of Al/Mg joints and provides insights for optimising aluminium-magnesium welding.

This study investigates the influence of gas tungsten arc welding (GTAW) current modes on dissimilar joints between Inconel 718 and AISI 410 martensitic stainless steel, targeting aerospace applications. Welding these alloys is challenging due to their differing thermal and chemical properties, which lead to brittle Laves phase formation, elemental segregation, and residual stresses. To address this, constant current (CCGTAW) and pulsed current (PCGTAW) techniques were compared. Microstructural characterisation was performed using optical and scanning electron microscopy to examine fusion zones, interfaces, and heat-affected zones. Both weldments showed niobium-rich Laves phases; however, PCGTAW resulted in a lower volume fraction (7.06%) than CCGTAW (10.50%), indicating improved suppression. Tensile failures occurred in the AISI 410 base metal for both welds. Microhardness profiles revealed uniform fusion zone hardness, softening in the IN 718 HAZ, and martensitic hardening in the AISI 410 HAZ. Hot corrosion tests at 650 °C in a K2SO4-NaCl environment showed superior resistance in PCGTAW welds, with lower weight gain, reduced oxide spallation, and a smaller parabolic rate constant (Kp). These enhancements are attributed to grain refinement, reduced segregation, and a narrower partially melted zone. Overall, PCGTAW significantly improves joint integrity and corrosion resistance, making it ideal for aerospace-grade dissimilar welding applications.

This study examines the microstructural, mechanical, and fractographic characteristics of friction-welded (FW) joints between SA 213 T12 and SA 213 F12 low alloy steels at rotational speeds of 55, 60, and 65 rps. Microstructural analysis using optical and SEM imaging revealed distinct weld zones, including the interface (IF), partially deformed zone (PDZ), and heat-affected zone (HAZ). The IF exhibited refined bainite and acicular ferrite, with increased dynamic recrystallization at 60 rps, leading to enhanced mechanical properties. Elemental mapping through EDS confirmed uniform chromium and molybdenum diffusion across the IF, with greater mechanical mixing at higher speeds. Microhardness profiling showed peak values at the IF, particularly on the SA 213 F12 side, decreasing towards SA 213 T12. The hardness distribution narrowed at higher speeds due to increased flash generation. Tensile testing revealed that all joints exceeded the base metals in ultimate tensile strength (UTS), with the highest UTS at 60 rps. Fractographic analysis confirmed a predominantly ductile failure, with finer dimples at 60 rps, correlating with improved elongation and strength. These findings demonstrate that an optimal rotational speed of 60 rps yields superior mechanical performance and microstructural refinement, providing valuable insights for optimizing FW parameters in high-performance applications.

The large structural components (304 L austenitic stainless steel) used in nuclear power plants are difficult and expensive to manufacture and machine using standard methods. Wire arc additive manufacturing (WAAM) is a low cost and high deposition method for fabricating large structural parts. Therefore, in this investigation, 304 L austenitic stainless steel (304 L ASS) cylindrical component was fabricated using WAAM technique. The mechanical and microstructural characteristics of the bottom (region ①) and top (region ②) of the WAAM 304 L ASS component are studied. The microstructure of region ① consists of austenite and ferrite with vermicular and lathy morphologies, while region ② consists of skeletal and reticular morphologies. In regions ① and ②, yield strength (YS), ultimate tensile strength (UTS), and elongation (EL) were found to be 350 ± 7 MPa, 562 ± 10 MPa, and 75 ± 1%, respectively. The impact toughness and hardness in regions ① and ② were found to be 112 ± 2 J and 183 ± 6 (Hv0.5), respectively. From the results, it is evident that the tensile properties of the WAAM 304 L ASS component were equal/greater than the values of the forged 304 L ASS material, wrought 304 L ASS alloy, and 304 L ASS filler wire.

The proliferation of Wire Arc Additive Manufacturing (WAAM) has significantly enhanced the production capabilities for lightweight and structurally robust components. This study investigates the microstructural characteristics, tensile properties, and preliminary wear performance of AA 5083 aluminum alloy processed via WAAM, focusing on applications for lightweight structures. Using SEM and XRD, microstructural changes during the WAAM process are analyzed, and tensile testing evaluates the mechanical properties, including ultimate tensile strength (UTS) and elongation. The results reveal that the microstructure consists of α-Al and β-(Al5Mg8) phases, with the Al5Mg8 phase distributed along grain boundaries and within grains. Notably, the grain size in the Y-direction (building direction) is larger than in the X-direction (deposition direction) due to temperature variations during processing. Tensile testing shows that horizontal samples (X-direction) have a UTS of 295 ± 5 MPa and elongation of 20.08 ± 0.8 %, while vertical samples (Y-direction) have a UTS of 267 ± 10 MPa and elongation of 16.43 ± 2.1 %. This results in an anisotropy of 9.4 % in tensile strength, reflecting the differences in mechanical properties between the two directions. The WAAM AA 5083 aluminum part exhibits a maximum wear rate of 5.22 × 10⁻³ mm³/m and a coefficient of friction of 0.52 at a load of 3.5 kg and 450 rpm. Under these conditions, deep grooves, layer separation, and load-induced deformation are observed. The primary wear mechanisms include delamination, adhesion, and abrasion. Hardness levels are consistent in the X-direction and show minimal variance in the Y-direction, with an average hardness of 89.4 ± 5.14 HV0.5. The study demonstrates that WAAM-produced AA 5083 aluminum alloy, with an anisotropy below 10 %, is suitable for real-time lightweight structures, offering effective performance in engineering applications such as aerospace and automotive industries. Future research should focus on further quantifying wear behavior and optimizing processing conditions to enhance material performance for specific applications.

Direct energy deposition (DED) is an advanced additive manufacturing (AM) technique for producing large metal components in structural engineering. Its cost-effectiveness and high deposition rates make it suitable for creating substantial and complex parts. However, the mechanical and microstructural properties of these components can be influenced by the varying heat input and repeated thermal treatments associated with different welding procedures used during the deposition process. This study employed gas metal arc welding (GMAW) and cold metal transfer (CMT) arc welding techniques to fabricate cylindrical components from 2209 duplex stainless steel (DSS). The research investigated the impact of these welding methods on the microstructure and mechanical properties of the 2209 DSS cylinders. The intricate thermal cycles and cooling rates inherent in the DED process significantly influenced the primary phase balance, ideally comprising 50% austenite and 50% ferrite. In components processed using GMW, σ-phase formation was noted at the grain boundaries. Additionally, a slower cooling rate and extended time for solid-state phase transformations led to an increase in austenite content from the bottom to the top of the component. The cylinder fabricated using the CMT process exhibited fine austenite morphologies and a higher ferrite content compared to the GMW-processed cylinder. Furthermore, the cylinder produced using the CMT process showed consistent properties across the building direction, unlike the components manufactured with the GMW process. In terms of tensile properties, hardness, and impact toughness, the cylinder produced using the CMT technique outperformed the one made with the GMW process.

To address the challenges of heat input in wire arc additive manufacturing (WAAM), this study employed the pulsed cold metal transfer (PCMT) technique to fabricate Incoloy 825 (IN825) components. PCMT, characterized by controlled droplet transfer and reduced heat input, enhanced mechanical performance and microstructural quality. Comprehensive analyses, including microstructural examination, X-ray diffraction, energy-dispersive X-ray spectroscopy (EDS), and element mapping, were performed. Titanium and molybdenum-rich secondary particles were identified through EDS. The mechanical properties of PCMT-fabricated components were compared with both wrought IN825 and those produced by gas metal arc additive manufacturing (GMAAM). Results demonstrated that PCMT components, particularly those fabricated at a 45° orientation, achieved approximately 113% of the ultimate tensile strength (UTS) and 131% of the elongation compared to wrought IN825. This marked a significant improvement over GMAAM-fabricated components. The reduced heat input and enhanced cooling rates in the PCMT process contributed to finer microstructures and superior mechanical properties. Fractography studies revealed that PCMT components exhibited ductile fractures with significant plastic deformation and some brittle regions. These findings underscored the advantages of PCMT in producing high-performance IN825 components compared to traditional GMAAM.

This study investigates the impact of printing orientation on the mechanical properties and surface characteristics of parts produced using VeroWhitePlus RGD835 polymer material in a layer-based Polymer Jetting Technology process. Tensile, hardness, and surface roughness tests were conducted to evaluate the influence of different printing orientations on the properties of the printed samples. The results show that printing orientation significantly affects both the mechanical strength and surface roughness of the parts. Specifically, samples printed in the XZ, YZ, and vertical orientations exhibited 20–30% higher tensile strength and 15–25% greater hardness compared to those printed in XY and other orientations. Surface roughness values varied by up to 10 µm across orientations but did not directly correlate with tensile strength and hardness, suggesting a complex interaction between orientation, layer bonding, and material properties. This anisotropic behavior is attributed to the non-uniform absorption of light energy during the jetting process, which causes varying layer bonding and material density across different regions of the printed parts. Additionally, areas with higher energy absorption, such as the edges of layers, exhibited smoother surfaces and enhanced mechanical properties, while regions with lower energy absorption showed rougher surfaces and reduced strength. Fracture surface analysis revealed brittle fracture characteristics with localized pressures and voids between layers, weakening the material’s ability to withstand deformation. These findings provide valuable insights into the optimization of Polymer Jetting Technology processes, particularly in selecting printing orientations and adjusting process parameters such as light exposure intensity, to improve mechanical performance and surface quality.

This study investigates the effect of forging pressure on the microstructural evolution, mechanical properties, and fracture behaviour of rotary friction welded (RFW) low-alloy steel (LAS) joints. Three forging pressures - 0.76, 0.84, and 0.91 MPa/s - were applied to evaluate their influence on hardness, tensile strength, and ductility. Microstructural analysis revealed that at 0.84 MPa/s, significant grain refinement occurred in the heat-affected zone, promoting superior mechanical properties. The ultimate tensile strength increased from 473 MPa at 0.76 MPa/s to 488 MPa at 0.84 MPa/s, before slightly decreasing to 482 MPa at 0.91 MPa/s due to grain coarsening. A maximum elongation of 40.01% was achieved at 0.84 MPa/s, representing a 27.05% improvement compared to 0.76 MPa/s. Hardness variations followed a similar trend, with peak values observed at intermediate forging pressure. Fractographic analysis confirmed a ductile fracture mode at 0.84 MPa/s, characterised by deep equiaxed dimples, while coarser fracture features were noted at higher pressures. These results demonstrate that an optimal forging pressure enhances strength-ductility synergy by refining the microstructure and preventing excessive grain growth. The findings provide valuable insights into optimising forging conditions for high-performance RFW LAS joints in structural and industrial applications.

Property mapping, an indentation technique, was employed to investigate the nano-mechanical behaviour of austenite, ferrite, and interphase regions in duplex stainless steel (DSS). The influence of furnace cooling and water quenching heat treatment processes on the deformation behaviour of individual phase regions was quantitatively assessed in both the transverse and longitudinal sections of DSS samples. Property evaluation across these regions was conducted through load-displacement curves and associated material parameters such as empirical property ratios, elastic-plastic indentation work values, and other mechanical properties. This study reveals the heterogeneous and anisotropic nature of the mechanical behaviour of DSS phase regions across the sections, which can assist in improving structural design(s).

This study evaluates the degree to which small and medium sized enterprises (SMEs) are prepared to adopt smart manufacturing in contrast to large enterprises, a transition that depends on the effective use of the Internet of Things, artificial intelligence (AI), and advanced analytics. While many large multinational companies have already integrated such technologies, smaller firms still struggle because of tight budgets, limited technical expertise, and difficulties in scaling new systems. To capture these realities, the investigation refines the Initiative Mittelstand-Digital für Produktionsunternehmen und Logistik-Systeme (IMPULS) Industry 4.0 readiness model, which was initially developed to help German SMEs, so that it aligns with the circumstances faced by smaller manufacturers. A thorough review of published work first surveys existing readiness and maturity frameworks, highlights their limitations, and guides the selection of new, SME-specific indicators. The framework gauges readiness across six dimensions: strategic planning and organizational design, smart factory infrastructure, lean operations, digital products, data-driven services, and workforce capability. Each dimension is operationalized through a questionnaire that offers clear benchmarks and actionable targets suited to the current resources of each enterprise. Weaving strategic vision, skill growth, and cooperative support, the approach offers managers a direct path to sharper competitiveness and lasting innovation within a changing industrial landscape. Additionally, a separate Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis is provided for each dimension based on survey data offering decision-makers concise guidance for future investment. The proposed adaptation of the IMPULS framework, validated through empirical data from 31 SMEs, introduces a novel readiness index, diagnostic gap metrics, and actionable cluster profiles tailored to developing-country industrial ecosystems.

Wire arc additive manufacturing (WAAM) using the cold metal transfer (CMT) process has emerged as a transformative method for producing near-net-shape metal components with tailored microstructures and enhanced mechanical performance. This study investigates the wear characteristics of components fabricated using CMT-based WAAM with ER70S-6 low-carbon steel (LCS) and 316LSi stainless steel (SS), focusing on their potential for abrasive and erosive wear applications. Microstructural analysis, including phase transformations and grain morphology, was performed in both the deposition (X) and building (Y) directions. Wear testing was conducted on a pin-on-disc machine under varying loads (1.5–3.5 kg) and sliding speeds (150–450 rpm) to evaluate wear rates, coefficients of friction (COF), and wear track morphology. The microstructure of the WAAMed LCS component is characterized by lamellar structures of ferrite and pearlite, with variations observed along the X- and Y-directions. The X-direction shows ferrite structures including polygonal ferrite and Widmanstätten ferrite (αWD), while the Y-direction exhibits acicular ferrite (αac) and bainite (B) phases. The WAAMed 316LSi SS shows austenitic structures with residual ferrite, exhibiting lathy ferrite morphology in the X-direction and vermicular ferrite in the Y-direction. At the highest load and speed, the wear rate of 316LSi SS was reduced by 83.51% compared to LCS, with wear rates ranging from 0.74 × 103 to 1.98 × 103 g/m for 316LSi SS, and from 1.64 × 104 to 2.65 × 104 g/m for LCS. The COF for 316LSi SS remained within 0.34–0.45, significantly lower than the 0.53–0.57 observed for LCS. SEM analysis of worn surfaces identified abrasive, adhesive, and delamination wear as predominant mechanisms for LCS, whereas 316LSi SS showed minimal material loss due to its higher hardness (193–227 HV0.5 vs. 160–187 HV0.5 for LCS) and stable microstructure. These results establish WAAM-fabricated 316LSi SS as a promising material for wear-critical applications, providing a foundation for optimizing processing parameters and material properties.

This study investigates the development of grain structure and crystallographic texture in Inconel 825 parts produced via wire arc-based additive manufacturing. Microscopy revealed distinct dendritic morphologies across the build height, transitioning from refined cellular and equiaxed structures near the substrate to coarser columnar dendrites in the upper layers due to reduced cooling rates. Electron backscatter diffraction (EBSD) analyses indicated a strong crystallographic texture with preferred 〈111〉 and 〈001〉 orientations along the build direction. The grain boundary character distribution showed a high fraction of high-angle grain boundaries (45%), suggesting potential for superior mechanical performance. Pole figure analysis confirmed orthotropic texture symmetry, highlighting the directional nature of solidification and epitaxial growth. These texture-induced microstructural features contribute to superior load-bearing capability and thermal stability, making WAAM-fabricated IN825 well-suited for demanding applications in aerospace, chemical processing, and power generation environments, where high temperature and corrosion resistance are critical.

In the last two decades, wire arc additive manufacturing (WAAM) has emerged as a cost-effective alternative to traditional additive manufacturing (AM) processes, particularly for producing medium-to-large-scale components. The primary advantages of wire-based AM include simplified automated production and enhanced control and flexibility in the fabrication process. In this study, the gas metal arc welding (GMAW) process was used to produce cylindrical components from 2209 duplex stainless steel (DSS) using the WAAM technique. The mechanical properties and microstructural characteristics of the 2209 DSS cylinders were examined. The microstructure of the components varied from the bottom (region (1)) to the top (region (2)), resulting in a hardness difference between 301 HV0.5 and 327 HV0.5, and an impact toughness variation from 118 to 154 J. Additionally, the tensile properties exhibited anisotropic characteristics: the ultimate tensile strength and yield strength ranged from 750 to 790 MPa and from 566 to 594 MPa, respectively. The complex heat cycles and cooling rates during the WAAM process significantly affected the primary phase balance (50/50 austenite/ferrite) in the produced cylinder. In the GMAW-processed component, σ-phase precipitation was observed at the boundaries of the ferrite grains. The increase in the percentage of austenite from region (1) to region (2) was attributed to a decrease in the cooling rate and a longer time for solid-state phase transformation.

Aluminium (Al) and magnesium (Mg) alloys are extensively used in the automobile sector because of their high strength-to-weight ratio, excellent castability low density and simplicity of recycling. Al-Mg structures used in the automotive sector can potentially reduce their weight. Although there is a significant opportunity for substantial cost reduction, the use of magnesium in aluminium structures remains restricted. This study aims to weld 3 mm-thick rolled sheets of AA6061 Al and AZ31B Mg alloy using the cold metal transfer (CMT) arc welding process. Three different filler wires (ER1100, ER4043, and ER5356) were used in the experiment. In this article, the mechanical and microstructure characteristics of Al/Mg dissimilar joints manufactured by CMT are evaluated and discussed in detail. Optical microscope (OM), scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX), and x-ray diffraction (XRD) were used to analyze the CMT-welded Al/Mg dissimilar joints. Of the three filler wires used, ER4043 (Al-5%Si) filler wire yielded defect-free sound joints due to the presence of Si, which improves the flow ability of molten filler during welding. The presence of Mg-rich intermetallics-Al12Mg17) and Al-rich intermetallics-Al3Mg2 were observed. The fractured area of the CMT-welded Al/Mg dissimilar joints revealed the presence of the Mg-rich intermetallics (Al12Mg17), which is responsible for the decrease in tensile strength. The reduction of intermetallics, particularly of Mg-rich intermetallics (Al12Mg17) is important for improving joint strength. Research Highlights: Cold metal transfer (CMT) arc welding was used to control the Al-Mg-rich intermetallics in the Al/Mg dissimilar joints. The microstructure, morphology and phase composition of the welded joints were studied by OM, SEM, TEM, EDS and XRD. The weld metal and AL substrate bonded with a strong interface, while weld metal and Mg substrate were joined at the epitaxial solidification area where the intermetallic compounds of Mg2Al3, Mg17Al12 and Mg2Si are generated. The weld metal on the Mg side experienced brittle fracture, with a continuous distribution of Mg2Al3, Mg17Al12 and Mg2Si.

Accelerated property mapping, an advanced indentation technique was used to describe the nanomechanical behaviour of duplex stainless steel (DSS) surfaces prior to and post heat treatments. Heterogeneity in deformation responses and relative elastic and/or plastic nature of DSS was assessed on longitudinal and transverse directions through load–displacement curves, property maps, histograms of hardness (H), modulus (E) and indentation works. Empirical ratios such as H/E, (H/E)1/2, H3/E2 and plasticity index were employed to understand the anisotropy across the directions.

Wire arc additive manufacturing (WAAM) is an advanced additive manufacturing (AM) technology that offers low cost and high deposition rates, making it suitable for building large metal parts for structural engineering applications. However, various welding procedures result in differing heat inputs and repetitive heating treatments throughout the deposition process, which can affect the microstructural and mechanical characteristics of the parts. In the current study, cylindrical parts made of 304L austenitic stainless steel (ASS) were manufactured using the WAAM technique, employing both gas metal arc welding (GMAW) and cold metal transfer (CMT) processes. This study explores the correlation between WAAM techniques and their effects on the bead geometry, microstructure and mechanical properties. The microstructure of the cylinders consisted of vertically growing austenite dendrites with residual ferrite (δ) within the austenite (γ) matrix. Compared to the bottom region (region ①), the top region (region ②) contained more residual ferrite. Although the microstructural characteristics from region ① to region ② are similar, they exhibit different ferrite morphologies. The rapid cooling rate in the CMT-AM process resulted in finer structures and a greater presence of ferrite phases in both regions compared to the GMAW-AM method. Cylinders produced by the CMT process displayed nearly uniform properties across both regions and demonstrated superior tensile properties, hardness, and impact toughness relative to those made using the GMAW technique. The WAAM 304L ASS cylinders also showed enhanced performance compared to stainless steel manufactured using traditional industrial forging standards, indicating that WAAM-processed 304L ASS cylinders are suitable for industrial applications.

The fabrication of dissimilar metal joints, particularly between AA 6061 aluminum alloy (Al) and AZ31B magnesium alloy (Mg), poses significant technical challenges due to their distinct metallurgical characteristics and the inherent difficulties associated with welding such materials. These challenges include the propensity for intermetallic compound formation, thermal cracking, and differences in thermal and mechanical properties between the two alloys. Cold Metal Transfer (CMT) welding, known for its low heat input and controlled metal transfer, offers a potential solution to these issues. However, optimizing the process parameters to ensure strong, defect-free joints requires a systematic approach. This study aims to optimize CMT welding parameters using parametric mathematical modeling (PMM) to produce high-strength Al and Mg dissimilar joints and to study the effects of CMT parameters on tensile strength (TS) and weld metal hardness (WMH), as well as the microstructural features of AA 6061 aluminum alloy/AZ31B magnesium alloy (Al/Mg) dissimilar joints. Al/Mg dissimilar butt joints were produced by the CMT process using ER4043 as filler wire. CMT, a low-heat input welding technique, was used to mitigate issues such as intermetallic compounds (IMCs), wider heat-affected zone (HAZ), and distortion. The CMT parameters, particularly wire feed speed (WFS), welding speed (WS), and arc length correction (ALC), were optimized using response surface methodology (RSM) to maximize the TS and WMH of the Al/Mg dissimilar joints. Polynomial regression was employed to create PMMs that integrated these CMT parameters to forecast the TS and WMH of the joints. An analysis of variance (ANOVA) was applied to assess the feasibility of the PMMs. The results indicated that the Al/Mg dissimilar joints, produced using a WFS of 4700 mm/min, a WS of 280 mm/min, and an ALC of 10%, exhibited higher TS and WMH values of 33 MPa and 95.8 HV, respectively. The PMMs provided precise forecasts for the TS and WMH of the Al/Mg joints with an error rate of less than 1% and a confidence level of 97%.

Cold Metal Transfer (CMT) technology has emerged as a promising welding technique, offering numerous advantages such as reduced heat input, minimal spatter, and enhanced control over the welding process. This paper provides a comprehensive review of recent research developments in CMT technology, focusing on its history, variants, recent advancements, and future perspectives. Initially, the paper traces the historical development of CMT welding, highlighting its evolution and the introduction of various CMT variants with distinct characteristics and applications. Recent studies have focused on optimizing CMT process parameters to improve weld quality and productivity, leading to advancements in parameter control, arc stability, and wire feeding mechanisms. Additionally, research has explored the microstructural evolution and mechanical properties of CMT-welded joints for both similar and dissimilar metals, providing insights into material compatibility, joint design, and performance under various conditions. Specific applications such as Laser-CMT hybrid welding, CMT cladding, CMT wire arc additive manufacturing, and CMT welding for repair across various materials are examined, demonstrating the versatility of CMT technology. This review also addresses the challenges and methodologies for defect reduction in CMT welding, along with recommendations for best practices. Furthermore, the paper discusses the integration of artificial intelligence in CMT welding, exploring opportunities for enhanced weld quality, economic, and social implications, and future research directions.

The learning factory is an emerging ‘hands-on’ approach to teaching advanced manufacturing technologies. This study aims to identify the key challenges for implementing learning factory in I4.0 arena. Since no past research works addressed the challenges associated with learning factory, participatory surveys were conducted to identify the key challenges. Industry leaders, policymakers, trainers, and academicians were selected as participants of the survey to collect a broad perspective from individuals at various levels. The experts’ feedback was synthesised in a mind map depicting challenges in implementing learning factories. Then, the interrelationship between the identified challenges is evaluated using decision-making trial and evaluation laboratory technique. Consequently, the significance and nature of each challenge is determined. The challenges identified in this work, and the findings of empirical analysis will help the industry and academia in creating and implementing Industry 4.0 learning factories.

Streetscape design can encourage social interaction and community building, creating a sense of place and improving the overall well-being of the resident community. Detailed investigation of streetscape quantitatively can identify the opportunities to reduce energy use, improve air quality, and enhance the natural environment. Data derived from street view services are typically used to analyze the streetscape. However, the availability of street view services is limited to selected regions, because of which conducting a study for an area deprived of street view services is a challenge. Building on this gap, this study proposes a new system introduced as Urban scan to overcome the limitation. • The proposed system can capture the streetscape in 360°. • Helps to analyze the streetscape composition with the least computational effort. • The accuracy of the classification is tested with different datasets and is noted to be above 96.02%.

Purpose: This study aims to propose a conceptual model indicating the impact of Industry 4.0 (I4.0) technologies on lean tools. Additionally, it prioritizes I4.0 technologies for the digital transformation of lean plants. Design/methodology/approach: The authors conducted a questionnaire-based survey to capture the perception of 115 experts of manufacturing industries from Germany, India, Taiwan and China. The impact of I4.0 on lean tools, using analysis of variance (ANOVA). Further, the authors drew a prioritization map of I4.0 on the employment of lean tools in manufacturing, using the Best–Worst Method (BWM). Findings: The findings indicate that cloud manufacturing, simulation, industrial internet of things, horizontal and vertical integration impact 100% of the lean tools, while both cyber-security, big data analytics impact 93% of the lean tools and advanced robotics impact 74% of the lean tools. On the other hand, it is observed that augmented reality and additive manufacturing will impact 21% and 14% of the lean tools, respectively. Practical implications: The results of this study would help practitioners draw up a strategic plan and roadmap for implementing lean 4.0. The amalgamation of lean with I4.0 technologies in the right combination would enhance speed productivity and facilitate autonomous operations. Originality/value: Studies exploring the influence of I4.0 on lean manufacturing lack comprehensiveness, testing and validation. Importantly, no studies in the recent past have explored mapping and prioritizing I4.0 technologies in the “lean” context. This study thereby attempts to establish a conceptual model, indicating the influence of I4.0 technologies on lean tools and presents the hierarchy of all digital technologies.

Today, the health care and medical sector is adopting digital technologies aggressively. However, this adoption also has significant challenges, especially during COVID-19. This research aims to identify and categorize the significant challenges related with application of Industry 4.0 (I4.0) technologies in the medical device industry. An expert-based survey is carried to capture the perception of medical device industry leaders about the challenges associated with the implementation of digital technologies. Further, interpretive structural modeling (ISM) method was used for an empirical investigation of the hierarchy and interdependencies of identified challenges. The authors have proposed a mind map and conceptual model of hierarchy and interdependencies of challenges associated with the digital transformation of the medical device industry towards I4.0. Industry leaders and policymakers worldwide are defying challenges while the digital transformation of the organizations post COVID-19. The I4.0 implementation challenges identified and ategorized in this research may aid as a guide for medical device manufacturing organizations while designing a strategy for I4.0 transformation and to make sure that they start on the right-footing. Most of the existing work is focused on the advantages of I4.0 for managing the organization's post-COVID-19, lacks thoroughness and testing. Owing to the identified gap, this study intends to empirically identify the critical challenges associated with applying I4.0 technologies in the medical device manufacturing sector. This study is a pioneer in identifying and categorizing the vital challenges needed to deal with this critical situation. A potential area of future research can be the validation of the identified challenges with a larger sample size.

The global electronics industry is one of the world's biggest industrial sector. Most of the innovative products like portable devices, wearable electronics, and even self-driving vehicles and artificial intelligence enabled products are revolutionazing this industry in recent years. The number of customized products in the electronic manufacturing are increasing, profit margins are reducing, innovation cycles are reducing and time to the marketplace is fast-moving up. The necessity for modernized, well-organized and efficient operations has never been ever stronger and in the same arena the 4th Industrial revolution is under progress with the potential to take the efficiency of the electronics assembly industry to the next level. This paper is a case study of Industry 4.0 (I4.0) technologies in an Indian electronics sector and provides the deep insights on implementation of digital technologies in electronics parts manufacturing, its enablers, associated challenges and concludes with the leanings to adopt the digital technologies in the electronics parts manufacturing which can be a ready reckoner for its implementation to best deal with the deal with the challenges and take leverage of the potential opportunities, understand the key success factors by learning from real life examples. These learnings will help industries and enterprises to harness I4.0 in a methodical, accessible and effective manner.

There is a strong opinion about the impact of Industry 4.0 (I4.0) technologies on the operations performance of manufacturing firms. However, there are several challenges while evaluating such situations. Determining the significance of I4.0 technologies in the context of the pandemic situation must consider several criteria for exhaustive understanding. This study aims to determine the significance and impact of I4.0 technologies on medical devices manufacturing firms’ operations during the COVID-19 outbreak. The set of technologies of I4.0 is evaluated over productivity, quality, cost, delivery, health, and safety parameters using a fuzzy analytical hierarchy process. The study reveals that the significance of big data analytics, autonomous robotics, and industrial internet of things (IIoT) in the business continuity of medical device manufacturing operations during the COVID-19 outbreak is high. Cloud technologies, digital simulations and augmented reality follow the order.

This research aims to identify the critical challenges associated with restarting manufacturing organizations post-coronavirus disease 2019 (COVID-19). The authors conducted an expert-based survey among various industry leaders of manufacturing organizations to capture a holistic view of business continuity plans and the associated challenges. The selected individuals are responsible for making business continuity policies and plans at their respective organizations. They were asked to reflect on their experience of the present-day challenges in managing business continuity in their organizations. Expert interviews were reflective and provided candid inputs. Consequently, the keywords of the experts' feedback were synthesized by using the mind map qualitative approach, which helps in the visualization of the critical challenges at an abstract level. Further, the interrelation between them and the significance of each critical challenge is evaluated using fuzzy theory with the decision-making trial and evaluation laboratory (DEMATEL) technique. The findings of these evaluations will help to assess the existing policies/ practices and to strengthen business continuity plans post-COVID-19. This study is a pioneering work that will help organizations to prepare action plans for kick-starting their broken-down economic engines.

The objective of this paper is to integrate Industry 4.0 (I4.0) into national policy framework of countries, and asses their readiness in adopting I40 through a literature review of their existing policy initiatives, while analyzing secondary data of some critical factors related to the future of production. I4.0 policy frameworks in both developing and developed countries are intended at enhancing modernization, endorsing the acceptance of up-to-date technology to fast-track financial development, boosting production output, and help in the holistic effectiveness of industries. Singapore, Japan, and Korea have been at the forefront of embracing I4.0 technologies. The findings of this study would help and support policymakers, researchers, and practitioners for the development of strategies for implementation of I4.0.

Global reporting initiative (GRI) is the global standard of sustainability. It epitomizes the global best practice of triple bottom line, i.e., economic, environmental, and social impacts. This research is an expert-based analysis of 132 industry leaders and policymakers from 36 industries to evaluate the significance of Industry 4.0 (I4.0) technologies on GRI adoption. In the first phase, the influence of I4.0 on GRI standards is analyzed using basic descriptive statistics and analysis of variance. In the second phase, the significance of the GRI standards in the context of I4.0 is evaluated using the Fuzzy Analytical Hierarchy Process (AHP). The findings indicate that 85% of environmental, 65% economic, and 50% societal GRI standards are influenced by I4.0. It is also found that the influence on economic performance, indirect economic impacts, energy, and emissions are significantly high. Findings ratify that the social aspect, which is often overlooked, needs more focus in manufacturing. Most of the contemporary research on evaluating the impact of I4.0 on sustainability is conceptual, lacks comprehensiveness, and rigor by thorough testing and validation. This study is one of the pioneering works offering a conceptual framework that aids in integrating I4.0 with GRI.

Purpose: This research aims to outline the key factors responsible for industry 4.0 (I4.0) application in industries and establish a factor stratification model. Design/methodology/approach: This article identifies the factor pool responsible for I4.0 from the extant literature. It aims to identify the set of key factors for the I4.0 application in the manufacturing industry and validate, classify factor pool using appropriate statistical tools, for example, factor analysis, principal component analysis and item analysis. Findings: This study would shed light on critical factors and subfactors for implementing I4.0 in manufacturing industries from the factor pool. This study would shed light on critical factors and subfactors for implementing I4.0 in manufacturing industries. Strategy, leadership and culture are found key elements of transformation in the journey of I4.0. Additionally, design and development in the digital twin, virtual testing and simulations were also important factors to consider by manufacturing firms. Research limitations/implications: The proposed I4.0 factor stratification model will act as a starting point while designing strategy, adopting readiness index for I4.0 and creating a roadmap for I4.0 application in manufacturing. The I4.0 factors identified and validated in this paper will act as a guide for policymakers, researchers, academicians and practitioners working on the implementation of Industry 4.0. This work establishes a solid groundwork for developing an I4.0 maturity model for manufacturing industries. Originality/value: The existing I4.0 literature is critically examined for creating a factor pool that further presented to experts to ensure sufficient rigor and comprehensiveness, particularly checking the relevance of subfactors for the manufacturing sector. This work is an attempt to identify and validate major I4.0 factors that can impact its mass adoption that is further empirically tested for factor stratification.

Super-duplex stainless steel (SDSS) is a class of materials that possess excellent mechanical properties with enhanced corrosion resistance. Given the presence of several alloying elements and the existence of a two-phase microstructure, it can be argued that it is one of the few materials that are difficult to machine. Therefore, the present study attempts to establish an improved understanding of the state-of-the-art development in insert coatings capable of providing excellent tribological and thermal resistance properties. In this work, monolayers of AlTiN and AlCrN are PVD coated on commercial carbide inserts so as to compare and contrast the performance of nitride coatings in the dry turning of SDSS. This study evaluates the machining performance in terms of tool wear, chip characteristics, tool life and surface finish. The coated surfaces were observed through optical microscope, profilometers, scanning electron microscope and energy-dispersive X-ray spectroscopy to evaluate the morphological changes. The results of the work indicate that machining with PVD-coated AlTiN insert showed longer tool life, better surface finish and smaller chip thickness when compared to AlCrN-coated and uncoated inserts at low to moderate cutting speeds. The dominant wear mechanism was found to be adhesion, where during turning long continuous chips were formed for uncoated inserts and small segmented chips were formed for coated inserts at different machining parameters. Contrarily, the study also purportedly explores the improved performance of AlCrN-coated inserts over AlTiN-coated inserts at high cutting speed.

Mixed Martial Arts is a rapidly growing combat sport that has a highly multi-dimensional nature. Due to a large number of possible strategies available to each fighter, and multitude of skills and techniques involved, the potential for upset in any fight is very high. That is the chance of a highly skilled, veteran athlete being defeated by an athlete with significantly less experience is possible. This problem is further exacerbated by the lack of a well-defined, time series database of fighter profiles prior to every fight. In this paper, we attempt to develop an efficient model based on the machine learning algorithms for the prior prediction of UFC fights. The efficacy of various machine learning models based on Perceptron, Random Forests, Decision Trees classifier, Stochastic Gradient Descent (SGD) classifier, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) classifiers is tested on a time series set of a fighter’s data before each fight.

Credit scoring is the most important and critical component conducted by the credit providers to decide whether to grant a loan to the applicant or not. Therefore credit scoring models are generally used to predict the potentiality of the loan applicant. A proper evaluation of the credit can help the service provider to determine whether to grant or to reject the credit. The objective of the study is to predict banking credit scoring assessment using a data mining technique i.e. Functional Link Artificial Neural Network (FLANN) classifier. Credit approval datasets: Australian credit and German credit have been used to do this analysis. The output of the study shows that the proposed model used for classification works better on credit dataset. Secondly, we have applied our proposed model on the two credit approval dataset to check the performance of the model for the classification accuracy. A proper evaluation of the credit using the proposed FLANN approach can help the service provider to accurately and quickly ascertain whether to grant credit or to reject.

Recently, single point incremental forming has caught the attention of automotive and aerospace industry as an alternative to conventional stamping process as an economical process capable of manufacturing sheet metal prototypes devoid of expensive dies. The first objective of the study was to ascertain the nature of cutting forces expected during the single point incremental forming process. The second objective is to study the effect of different process parameters on these forming forces. Detailed experiments were conducted based on the Taguchi’s robust design approach. Forming forces were measured for different working conditions (sheet thickness, wall angle, tool diameter, and step down). Based on the experimental results, several conclusions were made on the effect of process parameters on the forming forces. Analysis of variance (ANOVA) was used to identify the most significant control factors and their interactions. From the experimental findings, an attempt was also made to find the optimal combination of the process parameters on the basis of a proposed predictive mathematical model. Finally, the study proposed guidelines for forming thick sheets and improving production rate of SPIF process.

The use of electric vehicles (EVs) as a means of sustainable transportation is being discussed worldwide. The Indian government has also reacted to this with commendable effort to accelerate the rate of diffusion of EVs in Indian automotive sector. However, many hurdles should be dealt with for wider and easy adoption of EVs in India. This article identifies a set of barriers for mass adoption of EVs in context of Indian automotive market, find relationship and hierarchy to interpret them using Interpretive Structural Modeling (ISM) technique. The study reveals that the government incentives and consumer characteristics are most crucial areas of concern to improve the EV penetration in mass market.

Incremental Sheet Forming (ISF) is a relatively new sheet metal forming process. It hasshown great diversity in its applications ranging from automotive to biomedical fields. However, the geometries having steep walls cannot bemanufactured in single stage incremental forming process due to the fact that the maximum wall angle that can be formed is limitedfor a given sheet material and thickness. This limitation can be overcome with Multi Stage Incremental Forming (MSIF) process. This paper presents some of the experimental studies in multi stage incremental forming of steel sheets to get steep wall angles.The effect of process parameters in forming cylindrical, square and spherical cups in MSIF process has been discussed.

Credit scoring models is a scientific methodology adopted by credit providers to assess the credit worthiness of applicants. The primary objective of such models has been to predict the potentiality of the loan applicant. A proper evaluation of the credit can help the service provider to determine whether to grant or to reject credit. Therefore, the objective of the study is to predict banking credit scoring assessment using Predictive K-Nearest Neighbour (PKNN) classifier. For the purpose of analysis two different credit approval datasets: Australian credit and German credit have been used. The results from the study show that the proposed model used for classification works better on credit dataset. Here, the study firstly attempted to find the optimal 'K' value of the neighbourhood so that the classifier is tuned to forecast the credit worthiness and secondly, validated our proposed model on two credit approval datasets by checking the performance of the proposed models on the basis of classification accuracy.

The problem of growing e-waste (also called as WEEE) quantities in developing countries have prompted governments to plan innovative control measures and to institutionalize environment friendly strategies to mitigate the threats emanating from such waste. In India, e-waste recycling has been primarily a market driven industry. Under India's newly drafted e-waste management handling rules, the producers are expected to introduce and implement EPR regimes as early as possible. The scope of implementing EPR has also been discussed in these guidelines. In this work, we make an attempt to assess different EPR take-back policies and investigate their suitability for the Indian conditions. We use an economic model to ascertain the profitability of different EPR take-back schemes. In order to sustain the higher costs of e-waste recycling, the overall profitability of the e-waste take-back scheme is vital to the success of any e-waste recycling mandate. The results from our modeling clearly show that from the viewpoint of both the consumers and the producers, an individual take-back scheme outperforms the collective take-back scheme. We also describe impacts and implications of these take-back schemes on the model parameters of interest.

This article is a first, limited attempt made to understand the significant factors affecting consumer's willingness to participate in e-waste (waste from electronic consumer products) recycling program in the context of India. As India introduced a draft rule of e-waste management in May 2012, the need for understanding consumer's behavior affecting recycling program is very important to bring clarity and specific changes in the draft rule for better effectiveness. Three major groups of covariates, viz; demographic, socio-economic and individual preferences are discussed in the paper. The results are compared with mixed evidence from developed countries and from China. The authors claim to be the first to study this question using Indian data. © 2013 Elsevier B.V.

Reverse supply chains that characterize reuse and recycling remains the primary focus of large businesses in a globalized economy. This article critically examines the environmental and social benefits of reuse that would result through systematic interventions in the existing WEEE trade chain in India. There exists an increasing body of scientific evidence documenting the deleterious effects of informal recycling in India. Though formal recycling remains the focus of existing e-waste management systems in developed nations, we argue that alternative systems should be explored by making reuse as a policy instrument through appropriate interventions in the existing disposal practices found in developing nations. We show that prompt reselling of WEEE to other users can potentially go a long way in increasing their lifespan. The study uses a Markov chain model to analyze the underlying relationship that exist within the reverse supply chain partners by quantitatively evaluating the performance measure of different policy scenarios. Finally we discuss the critical factors affecting the reuse business in the context of Extended Producer Responsibility (EPR). © 2012 Elsevier Ltd. All rights reserved.

The current practice of assessing students through the open-book mode as against the traditional closed-book mode has been a topic of extensive research by academia. There is a growing consensus among academicians at large that open-book examinations are generally more suitable than closed- book examinations for testing the application of knowledge to innovative situations, as well as for examining higher order thinking abilities. Open-book examinations are believed to be able to reduce anxiety and rote memorising of facts. However, many argue that not all courses are suitable for open-book examination, as we should not overemphasise the benefits of open-book mode at the cost of knowledge content and depth of understanding. The purpose of this study is to develop a framework for the selection of courses suitable for open-book examination. A case study of a particular course offered by one of the leading university in India is taken up to evaluate the proposed framework using the multi-criteria decision-making approach. © 2010 Inderscience Enterprises Ltd.

The purpose of this study is to construct an approach and a methodology to estimate the future outflows of electronic waste (e-waste) in India. Consequently, the study utilizes a time-series multiple lifespan end-of-life model proposed by Peralta and Fontanos for estimating the current and future quantities of e-waste in India. The model estimates future e-waste generation quantities by modeling their usage and disposal. The present work considers two scenarios for the approximation of e-waste generation based on user preferences to store or to recycle the e-waste. This model will help formal recyclers in India to make strategic decisions in planning for appropriate recycling infrastructure and institutional capacity building. Also an extension of the model proposed by Peralta and Fontanos is developed with the objective of helping decision makers to conduct WEEE estimates under a variety of assumptions to suit their region of study. During 2007-2011, the total WEEE estimates will be around 2.5 million metric tons which include waste from personal computers (PC), television, refrigerators and washing machines. During the said period, the waste from PC will account for 30% of total units of WEEE generated. © 2009 Elsevier Ltd. All rights reserved.

Parametric appraisal of a dry sliding wear process is presented for a set of new composites consisting of polyester as the matrix, flakes of pine-bark as the fibrous reinforcing component, and the kiln-dust of a cement plant as the filler. The filler content in the composites is fixed at 50 wt%, while the weight fraction of fiber reinforcement is varied (0-12 wt%) so as to obtain composite samples of three different compositions. Wear tests are carried out with the help of a pin-on-disc test rig employing the design of experiments approach based on Taguchi's orthogonal arrays. The findings of the experiments indicate that the rate of wear is greatly influenced by various control factors. An optimal parameter combination is determined, which leads to minimization of wear rate. Analysis of variance is performed on the measured data and signal-to-noise (S/N) ratios. A mathematical correlation, consistent with the experimental observations is proposed as a predictive equation for estimation of sliding wear rate of these composites. Finally, optimal factor settings for minimum wear are determined using genetic algorithm. © The Author(s), 2010.

The objective of this paper is to estimate the future projection of computer waste in India and to subsequently analyze their flow at the end of their useful phase. For this purpose, the study utilizes the logistic model-based approach proposed by Yang and Williams to forecast future trends in computer waste. The model estimates future projection of computer penetration rate utilizing their first lifespan distribution and historical sales data. A bounding analysis on the future carrying capacity was simulated using the three parameter logistic curve. The observed obsolete generation quantities from the extrapolated penetration rates are then used to model the disposal phase. The results of the bounding analysis indicate that in the year 2020, around 41-152 million units of computers will become obsolete. The obsolete computer generation quantities are then used to estimate the End-of-Life outflows by utilizing a time-series multiple lifespan model. Even a conservative estimate of the future recycling capacity of PCs will reach upwards of 30 million units during 2025. Apparently, more than 150 million units could be potentially recycled in the upper bound case. However, considering significant future investment in the e-waste recycling sector from all stakeholders in India, we propose a logistic growth in the recycling rate and estimate the requirement of recycling capacity between 60 and 400 million units for the lower and upper bound case during 2025. Finally, we compare the future obsolete PC generation amount of the US and India. © 2010 Elsevier Ltd.