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To explore the evolution mechanism of multistage machining processes and torsional fatigue behaviour based on strain energy for the first time and provide process optimization of axis parts of low-alloy medium-carbon steel for service performance, four multistage machining processes were applied to the 45CrNiMoVA steel, including the rough turning process (RT), RT + the finish turning process (FRT), FRT+ the grinding process (GFRT) and RT+ the finish turning process on dry cutting condition (FRT0). The result showed that the FRT process’s average low-cycle torsional fatigue life increased by 50% when it evolved from the RT process. The lower surface roughness of Ra 1.3 μm caused the total strain energy to increase by 163.8 Pa mm/mm instead of the unchanged strain energy density, and the crack feature evolved from some specific bulges to flat shear plane characteristics. When the GFRT process evolved from the FRT process, its average fatigue life increased by 1.45 times, compared with the RT process. Plastic strain amplitude decreased by 21%, and the strain energy density decreased by 4% due to more considerable compressive residual stress (-249 MPa). Plastic deformation layer depth had a consistent tendency with surface roughness. In this paper, surface integrity evolutions on cyclic characteristics and fatigue behaviour have also been explained. A fatigue life prediction model based on the energy method for machined surface integrity is proposed.

Drawing die complexity is higher than conventional stamping operations, nowadays. It needs to decrease stamping die operation numbers for a part to reduce project budget consumption. Therefore, frequency of tearing, thinning, crack occurrence increase while this amendment. Force, blank cutting, blank location on the drawing die and process optimization were investigated to decrease tearing, thinning and crack occurrence in Transit bodyside inner panels which have over 110 mm. deep drawing process. Formability was improved at the end of this study. Thus production scrap, stoppage time of stamping line were decreased over 90%. This study was conducted at Ford Otosan.

Strength of diffusion bonded AA1100/AA7075 alloys subjected to the lap shear and ram tensile load were performed and Artificial Neural Network (ANN) models was established to inaugurate connection amid input variables. Progress in strength was observed for improved interfacial thickness; however, beyond 6 μm thickness and 375 °C, a decline in strength was noticed. Similar trend was noticed for hardness value at 375 °C, whereas interface hardness is same as that of its hardest base alloy to provide optimum bond strength. In addition, failure nature of developed AA1100/AA7075 alloys is examined using electron microscope and intermetallic at the interface is found using X-ray diffraction pattern. Finally, the optimum values for diffusion bonded joints with their responses are affirmed by experimental results.

Al-Mg-Mn-Er-Zr alloy, produced through a combination of cold rolling and heat treatment process conditions, has been studied on its microstructure evolution, strengthening mechanism, and corrosion properties. The results demonstrated that, the dispersion of coherent Al3 (Er, Zr) nanoscale particles effectively pinned dislocations and increased the strength. The dislocation strengthening was considered as the primary strengthening method for Al-Mg-Mn-Er-Zr alloy. The β phase was preferentially precipitated at the grain boundary and the tip of the Al6Mn phase during annealing. The corrosion resistance of stabilized alloys was degraded after cold rolling, which can be attributed to the increase in the proportion of sub-grain stripe and high-angle grain boundaries. The alloy prepared by the process (50% deformation + 270 ˚C/4 h annealing + 10% deformation) exhibited a UTS of 434 MPa and a YS of 323 MPa; the degree of sensitization was quantified by the ASTM G67 test and the susceptibility to intergranular corrosion was in unsusceptible categories; this alloy thus achieves excellent mechanical properties and presents sufficient corrosion resistance.

Process optimization of additively manufactured Ti–6Al–4V alloy is an important aspect of the production of engineered, high-performance parts for the aerospace and medical industries. In this study, the microstructural evolution and mechanical properties of direct energy deposition processed Ti–6Al–4V alloy were investigated using different processing parameters. Experimental analyses revealed that the line energy density corresponding to the processing parameters of the direct energy deposition process influences the properties of additively manufactured Ti–6Al–4V alloy. First, an optimal line energy density limits the incidence and size of voids resulting from a lack of fusion to enhance both alloy strength and ductility. Second, an excessively high energy density induces the coarsening of prior-β grains to impair both alloy strength with the Hall–Petch relationship and alloy ductility due to the plastic deformation instability caused by the limited number of grains. These results indicate that both the extent of fusion and prior-β grain size affect the mechanical properties of additively manufactured Ti–6Al–4V alloy. Moreover, the results demonstrate the utility of the line energy density-based approach in determining the optimal processing parameters for realizing high-performance materials.

This literature review outlines the most important—agricultural and non-agricultural—types of sewage sludge management. The potential of waste sludge protein hydrolysates obtained by chemical sludge conditioning was reported. The discussed areas include acidic and alkaline hydrolysis, lime conditioning, polyelectrolyte dewatering and other supporting techniques such as ultrasounds, microwave or thermal methods. The legislative aspects related to the indication of the development method and admission to various applications based on specified criteria were discussed. Particular attention was devoted to the legally regulated content of toxic elements: cadmium, lead, nickel, mercury, chromium and microelements that may be toxic: copper and zinc. Various methods of extracting valuable proteins from sewage sludge have been proposed: chemical, physical and enzymatic. While developing the process concept, you need to consider extraction efficiency (time, temperature, humidity, pH), drainage efficiency of post-extraction residues and directions of their management. The final process optimization is crucial. Despite the development of assumptions for various technologies, excess sewage sludge remains a big problem for sewage treatment plants. The high costs of enzymatic hydrolysis, thermal hydrolysis and ultrasonic methods and the need for a neutralizing agent in acid solubilization limit the rapid implementation of these processes in industrial practice. Graphical abstract

More than 50 billion disposable paper cups used for cold and hot beverages are sold within the United States each year. Most of the cups are coated with a thin layer of plastic — low density polyethylene (LDPE) — to prevent leaking and staining. While the paper in these cups is both recyclable and compostable, the LDPE coating is neither. In recycling a paper cup, the paper is separated from the plastic lining. The paper is sent to be recycled and the plastic lining is typically sent to landfill. In an industrial composting environment, the paper and lining can be composted together if the lining is made from compostable materials. Coating paper cups with a compostable performance material uniquely allows for used cups to be processed by either recycling or composting, thus creating multiple pathways for these products to flow through a circular economy. A segment of the paper converting industry frequently uses an extrusion grade of polylactic acid (PLA) for zero-waste venues and for municipalities with ordinances for local composting and food service items. The results among these early adopters reveal process inefficiencies that elevate manufacturing costs while increasing scrap and generally lowering output when using PLA for extrusion coating. NatureWorks and Sung An Machinery (SAM) North America researched the extrusion coating process utilizing the incumbent polymer (LDPE) and PLA. The trademarked Ingeo 1102 is a new, compostable, and bio-based PLA grade that is specifically designed for the extrusion coating process. The research team identified the optimum process parameters for new, dedicated PLA extrusion coating lines. The team also identified changes to existing LDPE extrusion lines that processors can make today to improve output. The key finding is that LDPE and PLA are significantly different polymers and that processing them on the same equipment without modification of systems and/or setpoints can be the root cause of inefficiencies. These polymers each have unique processing requirements with inverse responses. Fine tuning existing systems may improve over-all output for the biopolymer without capital investment, and this study showed an increase in line speed of 130% by making these adjustments. However, the researchers found that highest productivity can be achieved by specifying new systems for PLA. A line speed increase to more than 180% and a reduction in coat weight to 8.6 µm (10.6 g/m2 or 6.5 lb/3000 ft2) was achieved in this study. These results show that Ingeo 1102 could be used as a paper coating beyond cups.

Bioconversion (e.g. anaerobic fermentation and compost) is the common recycling method of waste activated sludge (WAS) and its hydrolysis, as the rate-limiting step of fermentation, could be accelerated by protease. However, the commercial protease was unstable in a sludge environment, which increased the cost. An endogenous alkaline protease stable in sludge environment was screened in this study and its suitability for treating the sludge was analyzed. The optimal production medium was determined by Response Surface Methodology as starch 20 g/L, KH2PO4 4 g/L, MgSO4·7H2O 1 g/L, sodium carboxy-methyl-cellulose 4 g/L, casein 4 g/L and initial pH 11.3, which elevated the yield of protease by up to 15 times (713.46 U/mL) compared with the basal medium. The obtained protease was active and stable at 35 °C–50 °C and pH 7.0–11.0. Furthermore, it was highly tolerant to sludge environment and maintained high efficiency of sludge hydrolysis for a long time. Thus, the obtained protease significantly hydrolyzed WAS and improved its bioavailability. Overall, this work provided a new insight for enzymatic treatment of WAS by isolating the endogenous and stable protease in a sludge environment, which would promote the resource utilization of WAS by further bioconversion. HIGHLIGHTS A novel protease-producing bacterium was isolated from the sludge.; The screened protease was highly tolerant to the sludge environment.; Treatment of the sludge by the screened protease elevated its bioavailability.; The screened protease was a promising biocatalyst for sludge treatment.

Two scalable coating techniques, slot die and spray coating (SC), are used to apply cellulose nanocrystals (CNCs) to the surface of glass fibers with the goal of enhancing interfacial interactions between glass fibers and epoxy and, consequently, the strength of fiber-reinforced composites. The quality of the cellulose coatings and the interfacial shear strength, assessed via the single fiber fragmentation test, are determined as a function of the method and conditions used to coat the fibers. In addition, a comparison with glass fibers coated with identical CNC formulations using a laboratory-scale dip coating (DC) technique is provided. Results from both scalable methods were found to be comparable or superior to the DC technique, with SC outperforming DC by up to 18% on average depending on the coating applied. Further analysis was conducted on coating morphology, fracture behavior, elemental composition, and surface loading. The observed differences can be used to determine which technique is most appropriate for a given application. This work demonstrates the viability in adapting existing, scalable processes for CNC glass fiber coatings and establishes key avenues for future process optimization.

Chitin is the most abundant marine biopolymer, being recovered during the shell biorefining of crustacean shell waste. In its native form, chitin displays a poor reactivity and solubility in most solvents due to its extensive hydrogen bonding. This can be overcome by deacetylation. However, this process requires a high concentration of acids or bases at high temperatures, forming large amounts of toxic waste. Herein, we report on the first deacetylation with deep eutectic solvents (DESs) as an environmentally friendly alternative, requiring only mild reaction conditions. Biocompatible DESs are efficient in disturbing the native hydrogen-bonding network of chitin, readily dissolving it. First, quantum chemical calculations have been performed to evaluate the feasibility of different DESs to perform chitin deacetylation by studying their mechanism. Comparing these with the calculated barriers for garden-variety alkaline/acidic hydrolysis, which are known to proceed, prospective DESs were identified with barriers around 25 kcal·mol–1 or lower. Based on density functional theory results, an experimental screening of 10 distinct DESs for chitin deacetylation followed. The most promising DESs were identified as K2CO3:glycerol (K2CO3:G), choline chloride:acetic acid ([Ch]Cl:AA), and choline chloride:malic acid ([Ch]Cl:MA) and were subjected to further optimization with respect to the water content, process duration, and temperature. Ultimately, [Ch]Cl:MA showed the best results, yielding a degree of deacetylation (DDA) of 40% after 24 h of reaction at 120 °C, which falls slightly behind the threshold value (50%) for chitin to be considered chitosan. Further quantum chemical calculations were performed to elucidate the mechanism. Upon the removal of 40% N-acetyl groups from the chitin structure, its reactivity was considerably improved., Chitin is the most abundant marine biopolymer, being recovered during the shell biorefining of crustacean shell waste. In its native form, chitin displays a poor reactivity and solubility in most solvents due to its extensive hydrogen bonding. This can be overcome by deacetylation.

The purpose of this research was to reduce the amount of noble metal palladium catalyst and improve the catalytic performance in the Suzuki?Miyaura cross-coupling reaction, which is the key step in the synthesis of Boscalid. Taking o-bromonitrobenzene and p-chlorophenylboronic acid as raw materials, three kinds of Pd-PEPPSI-IPr catalysts were synthesized and employed in the Suzuki reaction, and then the biaryl product was subjected to reduction and condensation reaction to give Boscalid. Under the optimal reaction conditions, the result showed that the catalytic system exhibits highest catalytic efficiency under aerobic conditions, giving the 2-(4-chlorophenyl)nitrobenzene in over 99 % yield. Moreover, the Pd-PEPPSI-IPrDtBu-An catalyst was minimized to 0.01 mol%. The synthesis process was mild, the post-treatment was simple, and the production cost was reduced, which makes it suitable for industrial production.

The color filter required for manufacturing a CMOS image sensor was redeveloped to optimize its optical uniformity. An in-depth study of the three-dimensional (3D) coating process and how it gives rise to various radial-shaped striation patterns was conducted. These radial-shaped striation patterns were systematically investigated with reference to two types of patterns: the orthogonal type found only at the orthogonal edges of the wafer and the diagonal type found mostly at the corner of each quadrant. The formation of the orthogonal pattern was based on the wide standing wave created by the incident force of the spreading color photoresist (PR) and the reflective force from the bump pads acting as coating barriers. The diagonal pattern was found to be generated by the turbulent wakes created behind the bump pads by the drag force, which interfered with the coating flow. An in-depth study using Ansys CFX software and an in-line inspection tool revealed that lowering the viscosity of the color PR material is a key factor for improving the phenomenon whereby the 3D striation patterns of the orthogonal and diagonal types are formed. Based on this finding, it was possible to drastically reduce the formation of the 3D striation patterns by decreasing the viscosity of the material comprising each color PR. This study provides not only an empirical and theoretical understanding of the 3D color PR coating mechanism, but also guidelines for future color filter processes.

Deneyin tasarımı, yeni bir süreç geliştirmek veya mevcut bir süreci geliştirmek için kilit bir rol oynar. Literatürde sürekli kalite iyileştirme için faktöriyel deneysel tasarımları kullanılmıştır. Bu makalede, tasarım faktörlerinin optimizasyonu için bir deney verisi analizi yapmak amacıyla faktöriyel deney tasarımına sahip yeni bir yöntem sunulmaktadır. Önerilen yöntem beş ana adıma sahiptir. İlk adım deney öncesi planlama ile ilgilidir. İkinci adım faktöriyel tasarıma sahip deneysel aşamadır. Üçüncü adım bir deneye ait verileri analiz eder. Daha sonra, tasarım faktörlerinin en uygun değerlerini elde etmek için faktöriyel tasarıma dayalı optimizasyon modeli ilk defa geliştirilmiştir. Son adım deneyden elde edilen sonuçları doğrulamak için sonuçlar ve tavsiyeler adımdır. Son olarak, güncel literatürdeki sayısal bir örnek için farklı hedef değerler kullanılarak karşılaştırma çalışmaları yapılmıştır. Ayrıca, önerilen faktöriyel tasarıma dayalı süreç optimizasyon modelinin belirtilen hedef değere göre daha fazla varyansı azaltabileceği sonucuna varılmıştır., The design of the experiment plays a key role to develop a new process or improve an existing process. In the literature, factorial experimental designs are used for continuous quality improvement. This paper presents a novel methodology with a factorial experimental design in order to conduct an experiment data analysis for the optimization of design factors. The proposed methodology has five main steps. The first step is related to pre-experimental planning. The second step is the experimental phase with a factorial design. The third step analyzes data for an experiment. Next, a factorial design-based optimization model is firstly developed to get the optimal settings of design factors. The last step is the conclusions and recommendations step in order to validate the conclusions from the experiment. Finally, comparison studies are performed using the different target values for a numerical example from the current literature. In addition, it was concluded that the proposed factorial design-based process optimization model could reduce more variance based on the specified target value.

This work aimed to develop an empirical statistical model to determine the optimized parameters for depositing multi-bead single layer Stellite-6 coating on AISI 316 L austenitic stainless steel by laser cladding. A full factorial experimental design was carried out to establish a correlation between processing parameters (laser power, scanning speed and powder feed rate) and geometric characteristics of the coatings (dilution, peak height and surface waviness) through multiple regression. Optimized deposition parameters were estimated by desirability function and experimentally validated. The microstructure and microhardness were assessed as a mean of estimate the performance of optimized coating. The empirical-statistical model and optimization method proposed in this work were demonstrated to be valuable tools for process optimization with low computational cost. This would contribute for a higher material efficiency and reducing post-processing operations, such as machining. As expected for Stellite-6 coatings, the microstructure was composed of dendrites rich in cobalt and interdendritic regions composed of chromium carbides. The microhardness level corroborates the literature, suggesting that the performance was not compromised in favor of the coating geometry.

Process optimization for the selective laser melting (SLM) of the Fe-10Cu alloy was performed to obtain defect-free parts based on the energy density for thermodynamically complete melting. A microstructural study was conducted for the corresponding energy densities that focused on identifying defect formation mechanisms. A range of defects formed via by diverse mechanisms, such as lack of fusion, balling, shrinkage and the key-hole effect, were characterized, including mixed zones. The process range in which these defects were not formed could be suggested as the optimal conditions for SLM of the Fe-10Cu alloy. In this study, a laser power below 320 W, a scan speed below 1523 mm/s and an energy density under 15.56 J/mm3 were indicated to be the optimum process conditions for SLM of Fe-10Cu alloy to avoid micro-cracks from shrinkage, balling and rounded pores from the key-hole phenomenon.

Additive manufacturing not only offers the ability of constructing complex structural components but also creating strong and more durable parts than any other existing fabrication methods. In addition, it opens a novel research direction in developing new materials specifically for additive manufacturing beside the current wrought and cast materials. The present research attempted to produce an aluminum–magnesium–scandium alloy for selective laser melting. Nearly full dense samples were achieved through the process optimization. Significantly high mechanical strengths as-printed condition (450 MPa) with high ductility (26%) were obtained. This could be explained through super-fine and hierarchically graded microstructure and the formation of rod bundles in the melt-pool.

Complete understanding of ultrasonic interaction with aluminum alloys is essential to promote application of ultrasonic-assisted friction stir welding process in manufacturing industry. In this study, the ultrasonic-assisted compression tests were performed to investigate the effect of ultrasonic vibration on the stress-strain characteristics of AA2024-T3 alloy. At the same time, AA6061-T6 alloy was also tested, and the stress-strain relations for both alloys were compared and analyzed to study the influence of material properties on the variation of stress-strain characteristics under ultrasonic assisted compression. It was found that on the stress-strain curves of AA2024-T3 there are an obvious and transient stress reduction concave point at the beginning of ultrasonic exertion, a hysteresis of stress recovery and a short-term small hardening phenomenon after the ultrasonic exertion stopped. The results laid foundation for process optimization of ultrasonic-assisted friction stir welding of AA2024-T3.

The Bessemer process enabling to produce high-quality steels was implemented at steel mills of the Urals region more than 200 years ago. At the beginning of the 20th century, the process was modified by scientists from the Mining Institute and was then adopted by copper and nickel alloy producers. The converter process became one of the key processing stages with Russian copper and nickel smelters. This paper examines certain ways to improve the tuyere air flow in a horizontal converter. The authors came up with a generic equation for calculating specific blast air pressure and discuss the use of hydrothermal and aerodynamic techniques for tuyere purging. The blast air limit was determined for a horizontal converter that is characterized with massive melt ejections. The authors demonstrate that, in spite of all the process and design improvements, the modern converter process still has three major drawbacks. They include process cycling, the gas ductwork not being completely tight, unbalanced thermal and chemical status of the vessel leading to excessive thermal and chemical loads on the tuyere zone and incomplete slag formation in zones that are farther from the tuyeres. Research work is ongoing on a novel continuous converter design which involves the use of special-design unsubmerged tuyeres. Such tuyeres produce spatially oriented high-pressure blasts which enable consistent rotation of the molten matte in a tight cylindrical vessel.

Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are required for the evaluation of parametric combinations in order to improve the quality of the machined parts and machining time. This problem could be categorized as the offline data-driven optimization problem. For such problems, the surrogate or predictive models are useful, which could be employed to approximate the objective functions for the optimization algorithms. This paper presents a data-driven surrogate-assisted optimizer to model the end mill cutting of aluminum alloy on a desktop milling machine. To facilitate that, material removal rate (MRR), surface roughness (Ra), and cutting forces are considered as the functions of tool diameter, spindle speed, feed rate, and depth of cut. The principal methodology is developed using a Bayesian regularized neural network (surrogate) and a beetle antennae search algorithm (optimizer) to perform the process optimization. The relationships among the process responses are studied using Kohonen’s self-organizing map. The proposed methodology is successfully compared with three different optimization techniques and shown to outperform them with improvements of 40.98% for MRR and 10.56% for Ra. The proposed surrogate-assisted optimization method is prompt and efficient in handling the offline machining data. Finally, the validation has been done using the experimental end milling cutting carried out on aluminum alloy to measure the surface roughness, material removal rate, and cutting forces using dynamometer for the optimal cutting parameters on desktop milling center. From the estimated surface roughness value of 0.4651 μm, the optimal cutting parameters have given a maximum material removal rate of 44.027 mm3/s with less amplitude of cutting force on the workpiece. The obtained test results show that more optimal surface quality and material removal can be achieved with the optimal set of parameters.

This study was performed to optimize the papaya pulp foaming process and determine the effect of drying conditions on the drying kinetics and the quality of the obtained powder. Thus, the one- factor-at-a-time experimental method, followed by 2( k) full factorial design was implemented to determine the optimal conditions of the foaming process. The factors studied were egg white percentage (EW%), xanthan gum percentage (XG%), and whipping time (WT) which varied between 5–20%, 0–0.5%, and 5–20 min, respectively. The optimum conditions (EW% of 15%, XG% of 0.3% and WT of 15 min) for papaya foam expansion percentage (FE%) resulted in a foam with the highest FE% (275.64%) and desirability of 0.916. Foamed and non-foamed papaya pulp in thickness layers of 2-, 4- and 6-mm were dried at 60° and 80° C. Foaming papaya pulp reduced drying time at various layer thicknesses from 140–400 min to 60–160 min, and from 70–160 min to 30–100 min at 60° and 80° C, respectively. Foamed powder samples had the lowest dissolution times and hygroscopicity values; in addition, reconstituted solutions were lighter than non-foamed solutions. Ascorbic acid retention and total phenolic compound content was adversely affected by increased drying time. The obtained papaya powder was classified into six groups based on its quality parameters via hierarchical cluster analysis. In general, foam mat drying is a promising method for producing papaya pulp powder due to its high drying rates and better-quality product.

The acetate-initiated aliphatic isocyanate trimerization to isocyanurate was investigated by state-of-the-art analytical and computational methods. Although the common cyclotrimerization mechanism assumes the consecutive addition of three equivalents of isocyanate to acetate prior to product formation, we found that the underlying mechanism is more complex. In this work, we demonstrate that the product, in fact, is formed via the connection of two unexpected catalytic cycles, with acetate being only the precatalyst. The initial discovery of a precatalyst activation by quantum chemical computations and the resulting first catalysis cycle were corroborated by mass spectrometric and NMR experiments, thereby additionally revealing a catalyst migration to the second catalytic cycle. These results were further confirmed by computations, completing the full mechanistic understanding of this catalytic system. Identification of a side product with undesired properties for final coating applications allows for process optimization in the chemical industry.

It is likely for the interaction between the cubic boron nitride grains on the working surface of grinding wheels and maraging C250 steel workpiece to cause phase transformation, thus reducing the material removal rates and affecting the quality of the workpiece surface generated during grinding. Up to now, there remain few studies focusing on the relationship between grinding wheel topography and phase transformation. In this study, an analysis was conducted of the effects that the topography of cubic boron nitride grinding wheel has on the distribution of phase transformation and the surface quality of maraging steel during grinding. The phase transformation diffraction curve was plotted based on the results of X-ray diffraction (XRD) analysis, and then, it was compared with the known data under different grinding wheel conditions. The topography of the cubic boron nitride grinding wheel was characterized using 3D digital microscope analysis, and the dynamic abrasive grit density coefficient λd for micro-grinding was proposed to clarify the effect of relevant parameters on phase transformation. The surface quality of grinding wheel and workpiece after grinding was analyzed, while the combination of different grinding wheel topography parameters and the process optimization scheme were proposed to achieve the optimal effect of grinding.

Wire electrical discharge machining (WEDM) process used in a wide spectrum of industrial applications. AISI 1045 is medium carbon steel, because of its excellent physical and chemical properties, it is used in many applications. However, the review of the state of the art literature reveals that literature is lacking research to optimize WEDM process for machining AISI 1045 steel. The objectives of this research are building ANN model to predict metal removal rate (MRR) and surface roughness (Ra) values for machining AISI 1045 steel, identifying the significance of the pulse on-time (TON), pulse off time (TOFF) and servo feed (SF) for the MRR and Ra, and selecting optimal machining parameters that give maximum MRR value and that give the minimum Ra value. Taguchi method (Design of Experiments), artificial neural network (ANN), and analysis of variances (ANOVA) used in this research as a methodology to fulfill research objectives. This research reveals that the architecture (3-5-1) of ANN models is the best architecture to predict the Ra and MRR with about 98.136% and 97.3% accuracy respectively. It can be realized that TON is the most significant cutting parameter affecting Ra by P % value 42.922% followed by TOFF with a P % value of 24.860%. SF was not a significant parameter for Ra because of Fα > F. For MRR, the most significant parameter is TON with a P % value of (71.733%), i.e. about three times the TOFF P % value (21.796%) and the SF parameter has a small influence with P % value 3.02%. The analysis confirmed that the optimal cutting parameters for maximum MRR were: TON at the third level (25 µs), TOFF at the first level (20 µs), and SF at the third level (700 mm/min). On the other hand, the optimal cutting parameters for minimum Ra were: TON at the first level (10 µs), TOFF at the third level (40 µs), and SF at the first level (500 mm/min). Future work may focus on optimizing the WEDM process for machining other types of materials or other sets of parameters and performance measures.

The additive/subtractive hybrid manufacturing (ASHM) method, which takes the advantages of both additive manufacturing (AM) and precision subtractive machining (SM), is a promising technique for the surface quality improvement of an AMed part. However, machining characteristics and the residual stress evolution during the ASHM process have not been investigated in detail for the materials with phase transformation. In this study, an experimental study is conducted on manufacturing of a 6511 martensitic stainless steel with the ASHM method that combines selective laser melting (SLM) and end milling. The process window of SLM is determined in terms of the relative density. Milling forces, surface roughness, and residual stress of the ASHM samples with different cutting parameters are studied. The phase transformation of the martensitic steel is considered in the analysis of the residual stress. It is found that the surface residual stress state and distribution can be controlled by the milling parameters. This study provides guidance for the optimization of the process parameters for ASHM to manufacture martensitic stainless steel.

The green, high efficient and high value-added utilization of petroleum resource requires the molecular management of refining process. As the basis of precisely controlling and optimization of refinery, the molecular-level characterization and modeling of the petroleum and the related conversion process are widely concerned. The complexity of petroleum composition and conversion pathway form significant challenge for the development of molecular management technologies. In the presented paper, we summarized the progress in the fields of petroleum molecular-level characterization and modeling, and the researches that needed in the future were also prospected.