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Vehicle lightweighting is a current focus of research in the automotive industry, aiming to reduce vehicle weight, improve fuel economy, and reduce tailpipe emissions. One mechanical joining technology that can improve the performance and sustainability of vehicles is clinching. Clinching is characterized by its lightweight, high strength, and aesthetically pleasing green features, and it is mainly used to join metal or non-metal materials. In this article, a comprehensive overview of clinching is provided, including performance evaluation and testing methods. The influence of section parameters on joint performance is analyzed, and the latest finite element simulation and numerical simulation methods are introduced. Additionally, the relevant testing methods for static and fatigue performance are summarized. Furthermore, new environmental testing and non-destructive testing technologies are introduced. Finally, potential research directions for clinched joining technologies are proposed. [ABSTRACT FROM AUTHOR]

As a technology for the interaction and integration of products and simulation models, the digital twin can achieve accurate prediction and evaluation of product performance. However, the accurate model base is computationally complex, has a long iteration time, and is unable to perceive changes in the operating state in time. This leads to poor adaptability of the model and low efficiency of performance evaluation. The surrogate model can simplify the above model and improve computational efficiency. Based on this, this paper proposes a digital twin modelling and updating approach. The surrogate model is applied to the digital twin modelling process, which can accurately describe the physical mechanism and achieve interaction with the physical world. Then, this paper defines the consistency metric function, which achieves the rapid perception of the operation state and follows the physical world. Meanwhile, an improved LHS-Adam model update algorithm is used to adaptively update the model structure, improving the efficiency of the model parameters adjustment. Finally, experiments are conducted on the bogie suspension system to verify the feasibility and effectiveness of the update method in practical applications. The experimental results show that the established digital twin model has good updating performance and more efficient performance evaluation capability. [ABSTRACT FROM AUTHOR]

The reconfiguration of supply chain is becoming a crucial concept used to deal with market disruptions and changes such as the COVID-19 pandemic, demand uncertainty, and new technologies. It can be defined as the ability of the supply chain to change its structure and functions in order to adapt to new changes. Its assessment requires an understanding of its quantitative factors to provide indicators that are easy to interpret. Effective reconfigurability assessment can be achieved by measuring quantitatively its six characteristics (modularity, integrability, convertibility, diagnosability, scalability, and customization). This paper aims at identifying the quantitative factors of each characteristic and their inter-relationships by using Total Interpretive Structural Modelling (TISM). The structural model obtained by TISM is applied to understand the dependency quantitative factors. Based on TISM results, a classification of quantitative factors is determined using "Matrice d′Impacts Croisés, Multiplication Appliquée à un Classement" (MICMAC) analysis. This article provides a better understanding of the six characteristics previously mentioned to improve the reconfigurability of supply chains by considering the interactions between their factors. Thus, this analysis helps managers to understand the characteristics that influence the change of the supply chain structure and those that enable changing the supply chain functions in order to optimize the supply chain reconfiguration process. [ABSTRACT FROM AUTHOR]

In milling of thin-walled structures such as impellers or blisks, critical workpiece vibrations occur due to the excitation by the cutting forces and the dynamic interface between the workpiece and the fixture. Vibrations may cause instable state of the milling process, thus decreasing the production outcome by causing rejects. In respect to the milling process of thin-walled workpiece, a challenging task is to monitor the critical vibrations occurred in the workpiece itself or the contact surface between the workpiece and the clamping system. Vibrations can be reflected in the clamping system, and thus the clamping force variation monitoring is a potential scenario or solution to the challenging task. This article introduces a measurement prototype for the real-time dynamic clamping force monitoring. With respect to the measurement of clamping force, two case studies are carried out by a direct sensing method with PVDF thin-film sensors. In the first study, the measurement prototype with embedded PVDF sensors is located on the dynamometer, and an additional eddy-current transducer is applied for monitoring the workpiece deflection during the milling process. Deflection signals and cutting force signals from dynamometer are used as two referential signals to demonstrate the reliability of the prototype with embedded PVDF sensors. In the second study, milling test with the same tool and workpiece is implemented with only PVDF sensors monitoring. Dynamic clamping signal varying with different cutting durations in time, frequency, and time-frequency domain and different milling surface results is performed. Relationship between the collected signals and machining results is preliminarily analyzed. Case studies with thin-walled workpiece show the performance of the measurement prototype. [ABSTRACT FROM AUTHOR]

To improve the machinability of Inconel 718, a lot of work has been done in the past decade by modifying tools and machining processes. However, a recently developed cryogenic-ultrasonic assisted turning (CUAT) process influencing the machinability of Inconel 718 as compared to the conventional turning process (CT) has not been conspicuously presented. This paper analyzes the machinability of Inconel 718 using indigenously developed ultrasonic assisted turning (UAT) and CUAT facilities. The influence of the UAT process of Inconel 718 on cutting parameters recommended by the industry has been investigated. Surface roughness (Ra) and power consumption are measured under the UAT process and then compared with the CT process. Particle swarm optimization (PSO) algorithm is used to identify the optimum cutting parameters to achieve minimum Ra and power consumption for UAT and CT processes. The optimized parameters are considered to confirm the usefulness of CUAT as compared to UAT and CT processes. Experimental results of this research work endorse positive effects of the CUAT process over UAT and CT processes in terms of Ra and chip morphology. Ra values under the CUAT process are reduced significantly in comparison to UAT and CT processes, respectively. UAT and CUAT processes resulted in discontinuous chips having smaller chip thickness in comparison to the CT process. The results are being shared with the local SMEs, and the industry is anticipated to be benefited in terms of improving cutting performance using CUAT and UAT. Moreover, a sustainability assessment model is implemented to investigate the effect of CUAT in terms of machining performance as well as sustainability effectiveness in a single integrated approach. [ABSTRACT FROM AUTHOR]

A giant magnetostrictive rotary ultrasonic machine tool (GMRUMT) with a large and stable amplitude output was developed. The purpose of this study was to comprehensively evaluate the performance and technological characteristics of the GMRUMT by conducting large amplitude experiments of rotary ultrasonic machining. Combined with the transducers' characteristic curves of vibration amplitude versus frequency, the GMRUMT has the advantages of greater amplitude, higher power, and better stability compared with the conventional piezoelectric actuated rotary ultrasonic machine tool. The vibration stability of the GMRUMT during the machining process was evaluated by carrying out the rotary ultrasonic face milling of quartz glass and the measurement of the actual ultrasonic amplitude. The processing performance of the GMRUMT was evaluated by obtaining the cutting force, the critical feed rate, and the edge-chipping size at the exit hole via rotary ultrasonic drilling experiments. The tool life was evaluated by observing the abrasive wear of the tool. Finally, the GMRUMT was studied in a stable amplitude output condition via tuning to verify the machining advantages of the GMRUMT. [ABSTRACT FROM AUTHOR]

Intelligent manufacturing, as a pillar of the manufacturing industry, provides crucial support for achieving China’s strategic goal of becoming a manufacturing powerhouse. The operation and management process of intelligent manufacturing enterprises requires a large amount of capital investment, and the efficiency of capital utilization directly affects the economic benefits of intelligent manufacturing enterprises. Relevant enterprises continue to improve the performance evaluation mechanism and enhance their performance evaluation ability, so as to effectively promote the realization of corporate strategic objectives and continue to become a solid support for the steady operation of China’s economy. On this basis, the performance of intelligent manufacturing enterprises was deeply explored, and a set of performance evaluation indicator framework for intelligent manufacturing enterprises was established by using machine learning and big data technology. Through empirical analysis, machine learning methods are introduced into performance evaluation to establish an assessment mechanism for intelligent manufacturing enterprises that is suitable for China’s national conditions. For ridge regression, lasso regression, and elastic network regression in machine algorithm, we have conducted in-depth research and built a set of performance evaluation system using the model of lightGBM. Construct a framework of performance evaluation system for intelligent manufacturing enterprises based on machine learning and big data technology support, and use TOPSIS method to conduct empirical analysis, thus further highlighting the importance of evaluation and feedback mechanism for intelligent manufacturing enterprises. [ABSTRACT FROM AUTHOR]

Tool wear is a key issue in the friction stir welding of high strength materials like steel-, titanium-, and nickel-based alloys. The wear assessment is an important aspect for developing or modifying the existing tool materials and tool designs. In this study, two different grades of tungsten carbide tools, i.e., tool A (WC-6 wt.% Co) and tool B (WC-10 wt.% Co), were used to join DH36 steel plates. Pre- and post-welded tungsten carbide tools were characterized using different techniques like microstructure analysis, weight measurement, profile measurement, and X-ray diffraction phase analysis. It was observed that the degradation mechanisms strongly depend on the tool material composition and welding conditions. During this study, tool A was degraded by intergranular failure caused by the separations of tungsten carbide grains which promoted further cracks inside the tool. Different degradation mechanisms such as adhesion, abrasion, crack initiation, diffusion, and oxidation were observed for tool B. Progressive wear in tool B was strongly affected by the process temperatures. Minimum wear was observed at low rotational speed and high traverse speed. [ABSTRACT FROM AUTHOR]

In most machining operations, cutting fluids are essential to ensure the economical profitability of the process. Turning of common plain carbon and low alloy steels is an example of manufacturing process widely used in several branches of the manufacturing industry, were the use of cutting fluids plays a key role in minimizing tool wear, machining forces and surface roughness, and improving overall process performance. Unfortunately, the cutting fluids, particularly those mineral-based, are considered harmful to the environment and therefore a source of pollution in production lines, as well as being a threat to the health of the operators. An attempt of minimizing environmental pollution is to use cutting fluids which are vegetable-based instead of mineral-based, with many producers offering this option in their portfolios. Doubts though arise on how vegetable-based cutting fluids perform compared with the mineral-based fluids. The present work compares the performance of three concentrations (3%, 7%, and 10%) of two vegetable-based cutting fluids (an emulsion and a synthetic) with one mineral-based fluid (semi-synthetic). The comparisons are made through reciprocating sliding tests, wettability, cooling capacity, viscosity, and cutting force measurement in turning of an AISI 1050 steel. All non-machining tests (friction coefficients, droplet contact angles (wettability), heat exchange coefficient by convection and viscosity) and machining tests (machining forces) were performed with all cutting fluids. This set of rheological and tribological tests performed allowed better understanding of the differences in machinability, regarding the cutting forces, of the cutting fluids evaluated. The results showed that, despite the better thermal and tribological properties of the mineral-based cutting fluids, the vegetable-based emulsion had an overall better performance in relation to the wettability angle and machining forces. These results, together with the greater sustainable appeal of vegetable-based cutting fluids, point to their clear feasibility in the machining of AISI 1050 steel. [ABSTRACT FROM AUTHOR]

The aim of this paper is to introduce a practice-ready systematic methodology for the management of storage assignments and allocation decisions as well as an assessment of the resulting performance in an order picking system (OPS). Built on extant and well-known metrics of performance this method implements a double cross-analysis through an original visual tool that is easy to understand by warehousing managers and practitioners. This tool is organized in two main steps. The first step is a cross-analysis that combines multiple performance indicators to help the decision-maker understand whether an OPS provides the scope for performance improvement. A comparison with potential storage configurations is then conducted in the second step through a tailored multi-scenario cross-analysis, which attempts to identify the best combination of allocation and assignment policies capable of minimizing the overall traveling performance. The proposed methodology is applied to a significant real-world OPS. The selected case study represents a reference framework for decision-makers and practitioners. [ABSTRACT FROM AUTHOR]

Slicing is the initial procedure in silicon wafer manufacturing process. The cost of slicing process is about 30% of the total cost of chip fabrication. The effective approaches to decrease slicing cost are to reduce the slicing kerf loss and to decrease the thickness and breakage ratio of sliced wafer. The resin-bonded diamond wire saw has the advantages of uniform of abrasive protrusion height and the manufacturing process less impact on the core wire strength. It is expected to achieve a narrow kerf and ultra-thin wafer slicing of silicon crystal ingot with resin-bonded diamond wire saw. The aim of this paper is to develop high-performance resin-bonded diamond wire saw. Based on the analysis of fabrication process of resin bond diamond wire saw, the device for resin-bonded diamond wire saw manufacturing is developed. The mold in the fabrication device ensures the consistency of the wire saw outer diameter and the uniform of abrasive protrusion height. A test device for constant force feed slicing is developed for the slicing performance evaluation of resin-bonded diamond wire saw. The components of the coating layer materials of resin-bonded diamond wire saw are investigated via orthogonal test. Choosing the material removal rate, wire saw wear rate, coating layer binding force, and sliced surface roughness as evaluation indexes, the performance of developed resin-bonded diamond wire saw is evaluated. The optimal component ratio of the coating layer materials of resin-bonded diamond wire saw is obtained, and the verification test of the optimal component ratio of the coating layer materials is performed. The results of this paper are useful for the development of smaller-diameter diamond wire saw and high-quality slicing of optoelectronic crystal ingot. [ABSTRACT FROM AUTHOR]

Water chamber head is an important component of the steam generator in the nuclear power plant AP1000. It is made of 508III, a type of steel with high strength, low hardness, high toughness, and poor machinability. Traditional cutters are not efficient in cutting process, while the layer face milling cutter is able to reduce the cutting force at cutter teeth and, therefore, can prolong the tool life and improve the cutting efficiency thanks to the use of the layered milling technique. In this work, structural parameters of the layer face milling cutter for processing 508III are determined from aspects of the cutter structure, the cutter head diameter, and the cutter tooth density, with regard to characteristics of the heavy-duty cutting process. Next, geometrical parameters of the cutter, including the axial rake angle, the radial rake angle, the cutting edge angle, and the step structure, are optimized by means of single-factor experiment and static analysis. Finally, the performance of the optimized cutter is verified by two-level fuzzy comprehensive evaluation with using the indexes determined in the above experiment. The optimization of the layer face milling cutter can not only raise the cutting efficiency but provide some support, both theoretically and technically, for heavy-duty cutting applications. [ABSTRACT FROM AUTHOR]

The permutation flow shop problem is a complex combinatorial optimization problem. Over the last few decades, a good number of algorithms have been proposed to solve static permutation flow shop problems. However, in practice, permutation flow shop problems are not static but rather are dynamic because the orders (where each order contains multiple jobs) arrive randomly for processing and the operation of any job may be interrupted due to resource problems. For any interruption, it is necessary to reschedule the existing jobs that are under process at different stages in the production system and also any orders that were previously accepted that are waiting for processing. In this paper, a memetic algorithm-based rescheduling approach has been proposed to deal with both single and multiple orders while considering random interruptions of resources. The experimental results have shown that the performance of the proposed approach is superior to traditional reactive approaches. [ABSTRACT FROM AUTHOR]

Haptic rendering in virtual environment provides a powerful training and validation tool for assembly of bolted joints that require accurate assembly forces. This work proposes a staged haptic rendering approach for virtual assembly (VA) of bolted joints. Firstly, by analyzing the stress condition during the actual assembly process, four consecutive stages, namely navigation stage, transition stage, linearity stage, and yield stage, are identified. Then, the force rendering model is set up. Moreover, a prototype VA system is developed to implement and test the approach. Two groups of experiments on a two-stage gear reducer are conducted to verify the feasibility of the approach and evaluate the prototype’s performance. The results have shown that the force calculated by the proposed approach is consistent with the actual assembly and the evaluators are highly positive on the immersion and the guiding ability of the VA process with the haptic rendering provided. [ABSTRACT FROM AUTHOR]

Key design characteristics (KDCs) are important information related to the product and part designs, which significantly influence on the product's functions, performances, and quality. Identifying KDCs for a complex product will help designers to focus on key design parameters during the design process and rapidly obtain design schemes based on their close relationships to the product's functions, performances, and quality. Although there are some researches on key characteristic (KC) identification, most of them are focused on key process characteristics (KPCs) and few on KDCs. There also lacks a KDC identification framework to support KDC identification with better completeness and diverse usages. Adaptive design is the most important pattern of complex product design. Therefore, this paper presents a systematic method to identify KDCs for complex product adaptive design, in which KDCs can be determined by two related phases. Firstly, a product design specification (PDS)-KDC Candidates Network (PKCN) is constructed by using existing product instance data, cluster analysis, KC flow-down, and network analysis approaches. Then, the result from the first phase is used as a basis to identify KDCs for adaptive design. Three KDC identification techniques: similarity reasoning technique, breadth-first search (BFS), and the gray relational analysis approach are applied to find out KDCs from the PKCN, which are the most sensitive to the variation of a PDS. These identified KDCs can help designers to understand the relationships between KDCs and PDS and rapidly develop a design scheme. The effectiveness and the feasibility of the proposed method are verified by a case study via the development of an electric multiple unit (EMU)'s bogie. [ABSTRACT FROM AUTHOR]

This paper presents an approximate decomposition method for the performance evaluation of non-homogeneous fabrication/assembly (F/A) systems with multiple failure modes, finite buffers, and a fixed assembly proportion. First, we introduce a mixed flow combined with fund flow and material flow to convert an F/A system to a virtual transfer line. Then, we decompose the virtual transfer line into several two-machine lines and establish a continuous decomposition model. To tackle the new emerging characteristics of the F/A system, we propose an F/A decomposition algorithm (FADA) for solving this model and obtain the throughput and buffer level of the F/A system to evaluate system performance. Also, we demonstrate the validity of the proposed model and algorithmby comparing with the results of simulation-based method and completion time approximation (CTA)-based method. Finally, we analyze the impact of several key parameters, including failure rates, repair rates, and buffer capacities, on the performance of the F/A system. The results show that our analytical method outperforms the existing methods and can help production managers to evaluate the system performance, analyze the possible modifications, and further find the best performance improvement of such F/A systems. [ABSTRACT FROM AUTHOR]

In the last decades, huge efforts have been made to develop innovative solutions supporting the automation of logistics activities. Among the available technologies, autonomous vehicle storage and retrieval systems (AVS/RS) are very promising: they use light vehicles able to independently travel on different axes, and thus perform different tasks at the same time. Despite the increasing diffusion of such systems, there is still a lack of performance evaluation techniques. Furthermore, there are no standards available to provide performance evaluation criteria. In this paper, novel analytical models to assess the performance of AVS/RS pertaining to deep-lane racks. These models extend the state of the art by (i) taking into account the real criteria related to the storage and retrieval of items, (ii) considering the capability of the shuttle and the satellite to simultaneously perform different tasks, and (iii) evaluating the standard deviation of the cycle time, beside its average value. The presented models are validated through simulations performed on different warehouse layouts, in different deployment scenarios. The ultimate aim of such models is to support warehouse equipment designers in evaluating the performance of their systems, considering a multiplicity of realistic scenarios. [ABSTRACT FROM AUTHOR]

In recent years, additive manufacturing (AM) has undergone a rapid growth, therefore several processes based on different working principles (e.g. photopolymerization, sintering, extrusion, material jetting, etc) are now available and allow to manufacture parts using a wide range of materials. Consequently, the so-called benchmark artifacts are necessary to assess the capabilities and limitations of each AM process or to compare the performance of different processes. This paper focuses on the benchmark artifacts for evaluating the geometrical performance of AM processes and proposes an extensive review of the available literature, analyzing the design of such test parts in detail. The investigated test parts are classified according to the process aspect that they are able to evaluate (dimensional/geometrical accuracy, repeatability, minimum feature size) and the combination AM process/materials for which they have been used. In addition, the paper draws a summary of guidelines to design benchmark artifacts for geometrical performance evaluation. [ABSTRACT FROM AUTHOR]

Laser beam welding of austenitic/martensitic dissimilar combination is used in a precision electromechanical product for function design. In order to achieve the better mechanical performance and physical performance of welding joints, process optimization was first carried out according to the Box-Behnken design method, and mathematical response models of weld depth and peak temperature value at special point were developed by multivariate quadratic/linear regression analysis. An optimal group of welding process parameters is obtained. Then, mechanical performance was evaluated by micro-structure analysis, non-destructive test, and uniaxial tensile test, and the influence of cooling style after laser beam welding process was discussed on hardness distribution and fracture force. It is shown that a rapid cooling style can avoid the crack occurrence at the heat-affected zone of austenitic stainless steel and enhance fracture force of weld joint. However, the hardness distribution is not even, and it has the highest value at the heat-affected zone of martensitic stainless steel and the lowest value at the heat-affected zone of austenitic stainless steel. However, the welding joint has a better mechanical performance under the condition of low temperature. [ABSTRACT FROM AUTHOR]

To address the problem of how to build quantitative evaluation index models that reflect the essential characteristics of reconfigurable manufacturing system (RMS) and rank alternative reconfiguration schemes, which possess both advantages and disadvantages, an evaluation method based on the preference ranking organization method for enrichment evaluation (PROMETHEE) is proposed. Based on a consideration of the reconfiguration of the reconfigurable machine components and manufacturing cells, quantitative models of the key characteristics of an RMS (scalability, convertibility, diagnosability, modularity, integrability, and customization) are established, after which the quantitative models are used as the basis for constructing an RMS evaluation index system. The analytic hierarchy process (AHP) is used to assign the weights for these indices. During the evaluation process, PROMETHEE I is first applied to analyze the advantages and disadvantages of each alternative scheme. Then, PROMETHEE II is adopted to analyze the net advantages of the schemes. Finally, all of the alternative configurations are ranked according to the analysis results above. The workshop of an institute that has both research and production capabilities was used as an example to validate the effectiveness and practicability of the proposed method. The example contains 10 alternative reconfiguration schemes, and each scheme consists of six evaluation indices. The computation result shows that quantitative models of six key RMS characteristics are equipped with the ability of quantitative description of the RMS reconfiguration scheme, which gives intuitive decision-making information combined with PROMETHEE, including advantage and disadvantage between alternative schemes, for a decision-maker to select the satisfactory configuration. In addition, only a 7.2 % data loss during the evaluation data processing means the rationality of the selected evaluation index and evaluation algorithm. [ABSTRACT FROM AUTHOR]

This paper reports the results of an investigation carried out to analyse and evaluate the influence of haptic-enabled virtual assembly (VA) training with respect to real assembly tasks. The aim was to determine how well virtual assembly training transfers knowledge and skills to the trainee in order to improve their real-world assembly performance. To demonstrate this, a comprehensive analysis and evaluation of the influence of VA training on the real assembly performance is presented. This influence is assessed in terms of the effectiveness and efficiency when performing the real assembly task after undergoing VA training. The study considers the use of three training modes and several assembly tasks with increasing complexity and number of parts. The results indicate a significant improvement (of up to 80 %) in the real assembly performance of subjects who undertook VA training first when compared to those trained conventionally. Moreover, haptic-enabled VA training led to greater levels of effectiveness than without haptics. The results also revealed that the effectiveness of VA training depended on assembly task complexity, i.e. the greater the task complexity, the greater the effectiveness. Consequently, maximum VA training effectiveness was obtained with a combination of haptic-enabled VA training and high-complex assembly tasks. [ABSTRACT FROM AUTHOR]

This paper describes some of the misconceptions about existing process capability indices (PCIs). Attention has been drawn to their drawbacks. It is shown that the indices have failed to guide the users in the right direction. This is perhaps due to the lack of consistency between the observed index value and the non-conformance levels. We give different examples to elucidate this point. It is also shown that the indices have failed to distinguish between on-target and off-target processes. Such a critical study of process capability analysis has to the best of our knowledge has not been attempted before. The basic argument of the paper is that capability indices are powerful tools, but can inflict heavy damage if used incorrectly. The paper will be welcomed by practitioners and users in the industry and management. [ABSTRACT FROM AUTHOR]

Although the success of forward logistics depends on the performance of reverse logistics, some manufacturing companies are not able to manage their reverse logistics effectively and thus delegate this important process to third-party reverse logistics providers (3PRLPs). In such cases, the decision to evaluate and select an appropriate 3PRLP becomes highly significant. In this paper, we use the analytic network process (ANP) and propose an analytical framework to systematically model the complex nature of interactions among the selection factors. In this model, the factors determining the evaluation of 3PRLPs are initially valued using Likert scale questionnaires. Then, a screening process is implemented using the average alternative method. Finally, the factors selected are structured in a network framework following the ANP. We present a case study to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms. The results have important managerial implications for production managers and illustrate that, in our case study, quality is the most important factor when selecting a 3PRLP. [ABSTRACT FROM AUTHOR]

With the full use of combustion heat from Fe-O reaction, laser-assisted oxygen cutting (LASOX) is able to cut thick mild steel plates by a defocused laser of medium power (approximately 1 kW). The dynamic behavior of oxygen gas flow, determined by nozzle structure and cutting parameters, is the key factor affecting cut ability and quality. It is significant to understand the method to design a suitable supersonic nozzle and to evaluate its performance. A supersonic minimum length nozzle (MLN) was designed and made specially for LASOX. The configuration ( D / D ) of the designed nozzle was chosen based on two-dimensional isentropic calculation of dynamic gas pressure. The divergent section of the MLN was designed in accordance with the method of characteristics (MOC). Numerical simulation and Schlieren visualization were used to observe and compare the flow behavior of the free jet from the designed MLN nozzle and a commercial supersonic nozzle. The MLN nozzle generates a highly uniform and stable supersonic jet extending a longer distance along the axis of nozzle, which is around 1.4 times longer than that from the commercial supersonic nozzle. Mild steel plates in 20 mm thickness were cut to investigate the effect of cutting parameters on LASOX cut quality of two nozzles. The MLN significantly improved cutting quality due to the better performance of gas flow. The optimal cut quality is related to both oxygen pressure and cutting speed. The oxygen content was measured along the cut surface to explain the difference in cut quality. [ABSTRACT FROM AUTHOR]

This paper focused on the analysis of imprecise information in terms of many critical parameters for a multi-objective multi-item vendor selection-order allocation problem with price-breaks. We used both quantitative and qualitative criteria taking into account the economic, technological, social, environmental factors, and the price-breaks that were offered on order quantity following 'all-unit discount schedule.' We developed an optimization model that integrated fuzzy multi-objective integer linear programming and analytic hierarchy process techniques. A weighted possibilistic programming approach was presented to solve the optimization model, which simultaneously minimized (maximized) the best scenario, the likeliest scenario, and the worst scenario for the imprecise objective functions thereby avoiding situations that may force the solution process to divert. The integrated model and the solution approach were tested on the data set of an industrial case study. A detailed performance analysis and comparisons were done to show superiority of the proposed methodology over the existing related fuzzy programming approaches. [ABSTRACT FROM AUTHOR]

The addition of runs-rules has been recommended to improve the performance of classical, normal theory Shewhart-type control charts, for detecting small to moderate size shifts. In this paper, we consider adding both standard and improved runs-rules to enhance the performance of the distribution-free Phase II Shewhart-type chart based on the well-known Mann-Whitney statistic proposed by Chakraborti and Van de Wiel [1]. Standard runs-rules are typically of the form w- of-( w + v) with w > 1 and v ≥ 0, and the improved runs-rules scheme is a combination of the classical 1-of-1 runs-rule and the w- of-( w + v) runs-rules. The improved scheme improves the performance of the charts in detecting larger shifts while maintaining its performance in detecting small to moderate shifts. The in-control and out-of-control performance of the proposed runs-rules enhanced distribution-free charts are examined through extensive simulations. It is seen that the proposed charts have attractive performance compared to some competing charts and are better in many cases. An illustrative example is provided, along with a summary and conclusions. [ABSTRACT FROM AUTHOR]

Despite of the studies in the last decades, there are still some gaps in understanding of the distinctive behaviors of orthogonal turn-milling. In order to improve the performance of this new technology, deeper investigations are required. This work deals with the mechanics in non-eccentric orthogonal turn-milling. The engaged areas of both side edge and end edge are analyzed. Then, the boundary conditions used to extract them are derived. The two sets of cutting force coefficients for the side edge and end edge are calibrated based on slot milling and plunge milling, respectively. The total cutting forces are calculated as a sum of the cutting forces on both side edge and end edge. The proposed cutting force model is validated experimentally on a five-axis machine tool. In addition, comparative experiments have been conducted to investigate the effects of cutting depth and longitudinal feed rate on the cutting force in tool axis direction. [ABSTRACT FROM AUTHOR]

To provide the effective lubrication and thereby to reduce friction at the grinding wheel-work piece interface, resin-bonded grinding wheels impregnated with graphene nanoplatelets were developed. To study the impact of various physical characteristics of graphene nanoplatelets on the grinding performance, grinding wheels with varying graphene nanoplatelet concentrations (0.25, 0.5, 1, 2 and 4 wt%), surface areas (300, 500 and 750 mm/g) and widths (5, 15 and 25 μm) were manufactured. Different aspects of grinding performance (i.e. surface roughness, cutting forcers, grinding temperatures, grinding coefficient, specific grinding energy and grinding wheel wear ratio) are evaluated by grinding 'difficult-to-machine-material' Inconel 718 with these newly developed grinding wheels. The experimental results showed a considerable improvement in grinding process results with graphene nanoplatelets as compared to conventional grinding wheels. Grinding wheels impregnated with 1 wt% graphene are recommended for both extended wheel life and better surface quality. Graphene nanoplatelets with a 750-mm/g surface area and a 15-μm platelet width were found to be effective in improving the quality of the ground surface. [ABSTRACT FROM AUTHOR]

Drivable ground detection contributes to the perfect navigation of unmanned vehicle systems, and this significantly attracted the attention of researchers. Various vision-based techniques have been proposed, and amazing results are accomplished towards drivable ground detection. Despite these achievements, environmental noises like snows, rains and shadows have an effect that can lead to mis-detection of drivable ground. After conducting a brief study on snow, rain and shadow, we introduce filtering algorithms into the drivable ground detection system to overcome the effect of these environmental noises. Experimental comparison was carried out qualitatively and quantitatively. Quantitative experiments were carried out using these following schemes: accuracy rate (ACC), error rate (ERR), true positive rate (TPR), false negative rate (FNR), true negative rate (TNR), false positive rate (FPR) and precision (PRE). These schemes are used for a comparison between the system with and without a filtering algorithm. The results from all experiments show improved performance of the system with a filtering algorithm over other systems, and these massively contributed to perfect navigation for the unmanned vehicle system. [ABSTRACT FROM AUTHOR]

This paper discusses the performance of preconditioned Krylov subspace methods at solving large-scale finite-element-formulated contact problems based on a finite element analysis program (FEAP) and portable, extensible toolkit for scientific computation (PETSc). Different combinations of the common preconditioners and Krylov subspace methods, namely conjugate gradient, generalized minimal residual, conjugate residual, biconjugate gradient, conjugate gradient square, biconjugate gradient stabilized, and transpose-free quasi-minimal residual method, are tested on the problems with rising size. Numerical experiments are carried out in respect of time consumption, parallelism, memory usage, and stability. The results show time consumption for most of combinations increases linearly with the growth of problem size, and block Jacobi and Jacobi-preconditioned conjugate gradient and conjugate residual methods have better potential for large-scale problems in the given and similar case. [ABSTRACT FROM AUTHOR]

This paper investigated the effect of nanofluid MQL with vegetable-based oil and ester oil as base fluids on cutting force and temperature in cylindrical turning of AISI 1045 medium carbon steel. Comparative experiments were carried out under different cooling/lubrication conditions, i.e., dry cutting, minimal quantity lubrication (MQL) with LB2000 vegetable-based oil, MQL with PriEco6000 unsaturated polyol ester, graphite-LB2000 nanofluid MQL, and graphite-PriEco6000 nanofluid MQL. For this research, graphite-LB2000 and graphite-PriEco6000 nanofluids were prepared by a two-step method, and their thermophysical properties such as viscosity, surface tension, wettability, and thermal conductivity were measured. The experimental results show that application of graphite oil-based nanofluid MQL reduced the cutting force and temperature significantly. Furthermore, graphite-LB2000 nanofluid MQL showed better performance than graphite-PriEco6000 nanofluid MQL in terms of reduction in cutting force and temperature, especially at a high cutting speed. Therefore, compared with PriEco6000 unsaturated polyol ester, LB2000 vegetable-based oil was optimal base oil for graphite oil-based nanofluid MQL machining. [ABSTRACT FROM AUTHOR]

In this study, the problem of scheduling jobs on unrelated parallel machines with sequence-dependent setup times under due-date constraints is considered to minimize the total cost of tardiness and earliness. A new mathematical model is presented for considered problem and due to the complexity of the problem; an integrated meta-heuristic algorithm is designed to solve the problem. The proposed algorithm consists of genetic algorithm as the basic algorithm and simulated annealing method as local search procedure that follows the genetic algorithm to improve the quality of solutions. The performance of the proposed algorithm is evaluated by solving a set of test problems. The results show that the proposed integrated algorithm is effective. [ABSTRACT FROM AUTHOR]

Wet cutting is the most common cooling method used during the cutting of titanium alloys. However, this method is associated with high costs, pollution, and hazards to operators. Minimal quantity lubrication (MQL) is an effective environmentally friendly cooling method, but is not suitable for difficult-to-machine materials because of its low heat transfer capacity. Using cryogenic air mixed with MQL (CAMQL) for cooling has better heat transfer, but high equipment costs and noise pollution limit its industrial application. This paper proposes the use of oils on water (OoW) as a cooling method for the turning of Ti-6Al-4V alloy and aims at exploring the effect of OoW cooling. Both external oils on water (EOoW) and internal oils on water (IOoW) methods are considered. The effects of EOoW spraying location and the amount of water required for IOoW are compared with respect to chip morphology, cutting temperatures, cutting forces, surface roughness, and tool wear. The use of CAMQL at different air temperatures is compared with wet and dry cutting. The results show that the chips created by OoW and CAMQL are continuous spirals. Compared with CAMQL, use of IOoW cooling with an appropriate amount of water or EOoW cooling from a proper location yields lower surface roughness and slower flank wear rate, and bare areas on the cutting tool substrate were absent because of better lubrication. The properties of the lubricants have an influence on IOoW and CAMQL, but not on EOoW. A suitable cutting tool coating should be selected to ensure the best cutting performance under these cooling methods. [ABSTRACT FROM AUTHOR]

In this article, we consider the T control chart for bivariate samples of size n with observations that are not only cross-correlated but also autocorrelated. The cross-covariance matrix of the sample mean vectors were derived with the assumption that the observations are described by a first-order vector autoregressive model-VAR (1). To counteract the undesired effect of autocorrelation, we build up the samples taking one item from the production line and skipping one, two, or more before selecting the next one. The skipping strategy always improves the chart's performance, except when only one variable is affected by the assignable cause, and the observations of this variable are not autocorrelated. If only one item is skipped, the average run length (ARL) reduces in more than 30 %, on average. If two items are skipped, this number increases to 40 %. [ABSTRACT FROM AUTHOR]

The groove profile of ball-bearing raceway is of vital importance to ensure the bearing transmission accuracy. It is an attempt to apply electrolytic in-process dressing (ELID) groove grinding for the ball-bearing raceway finishing process. The wear rate of the grinding wheel is directly related to the profile accuracy of the bearing raceway. In order to maintain a high-forming accuracy, the interrupt truing has to be performed at the grinding interval. However, how to rationally plan the grinding interval for high-forming accuracy is hard to resort to the general concept of the wear of the grinding wheel. This study recorded the raceway profile variation on axial direction and radial direction by monitor points. The results show that the raceway profile variation (monitor points) on the axial direction could be omitted, because it is far less than the profile variation (monitor points) on radial direction. An evaluation method was proposed to plan the interrupt truing based on the raceway profile variation (monitor points) on radial direction. Finally, the feasibility of the proposed evaluation method was verified by the experimental results. The evaluation method of forming accuracy could provide a reference for selecting the truing interruption during ELID groove grinding process. The approach that incorporates the interrupt truing with the ELID groove grinding enriches bearing manufacturing method. The ELID groove grinding has a great potential for application in precision machining of ball bearing ring raceway. [ABSTRACT FROM AUTHOR]

Nowadays, every business organization has to execute all decisions in a highly competitive and uncertain scenario for improving its performance. One of such decision that every organization has to undergo is to select best suppliers for timely delivery of good quality parts at minimum cost. Therefore, effective and cost-efficient supplier selection in a stochastic or uncertain scenario helps an organization in achieving its goal. Hence, this paper deals with the supplier selection problem under stochastic environment. In the present work, an attempt is made to model Stochastic Multi-objective Supplier Selection Problem (SMoSSP) applying chance constraint approach. The proposed model considers operational risks involving uncertainties-related supplier's capacity, product demand, transportation and variable costs and lead time probability distributions. The SMoSSP is solved using non-preemptive goal programming and weighted aggregate function technique. To validate the proposed model data is generated randomly and solved in LINGO 10. Illustrative examples are presented to demonstrate the SMoSSP. [ABSTRACT FROM AUTHOR]

In this paper, we study the effect of classical additive measurement error model on the most commonly used control charts for monitoring simple linear profiles with random explanatory variable. We showed that the in-control and out-of-control performances of these methods are significantly affected when measurement error is present in the explanatory variable. The average run length criterion is applied to represent the performance of the methods. For instance, we can clearly see that even a small amount of measurement error introduced in the explanatory variable of a profile can increase the false alarm rate about 55 %. With the same negligible amount of error, the out-of-control average run length of the exponentially weighted moving average chart (EWMA)-3 method in detecting a moderate-size shift in the slope parameter increases 15 %. Two different strategies on the basis of control limit modification have been proposed to compensate for the undesired effect of measurement error. Results indicate that the proposed strategies substantially offset the poor performances of the control charts resulted from the presence of measurement error. [ABSTRACT FROM AUTHOR]

Minimum quantity lubrication (MQL), which is to apply a minimum amount of lubricant directly into the contact zone, is a promising alternative to substantially reduce the lubricant cost caused by conventional flood cooling. In order to advance the MQL technique into grinding situations, understanding of the process and evaluation of the performance is necessary. Most documented studies thus far concerning MQL grinding are built upon experimental observations with individual and separate treatment of grinding performance measures such as grinding force, temperature, wheel wear, and surface roughness. This paper develops the analytical understanding of mechanical and thermal effects of MQL in grinding and profiles the MQL performance as functions of process and fluid application parameters. Physics-based predictive models are formulated to quantitatively describe the grinding force considering the lubrication effect of MQL. The friction coefficient under MQL condition is first predicted based on boundary lubrication theory, followed by the single grit force and grit distribution analysis. Further, surface roughness is calculated from the results of undeformed chip thickness distribution through probabilistic analysis. Additionally, energy partition and temperature distribution in the workpiece have been developed based on the moving heat source model. Material constitutive model are utilized to capture the influence of temperature and strain rate on the material flow stress. Experimental measurements of force, temperature, and surface roughness have also been pursued to calibrate and validate the predictive models. [ABSTRACT FROM AUTHOR]

Surface texture technology is widely used in various friction pairs to obtain good lubrication. However, ever present researches are mainly focused on regular and simple texture shapes such as dimples and grooves. Few works on complex micro texture have been reported due to preparing difficulty. In this paper, two surfaces with complex micro texture, which are micro scale textured (MST) surface and micro furrow textured (MFT) surface, are prepared by ultrasonic vibration-assisted milling (UVAM) method. Also, their tribological behaviors under starved oil lubrication and reciprocating sliding condition are experimentally investigated with a smooth sample as comparison. Experimental results indicate that although the application of ultrasonic vibration leads to the increase of roughness of MST and MFT surfaces, both the two machined micro textures contribute to the improvement of lubricant film strength, and MFT surface has better tribological performance than that of MST surface. As a result, under test conditions, micro texture formed by UVAM method can greatly improve the tribological property of friction surface, especially for its bearing capacity and wear resistance. [ABSTRACT FROM AUTHOR]

Location errors are considered as one of the fundamental errors of five-axis machine tools. For the improvement of machine accuracy, it is important to propose an efficient and accurate identification method of location errors. This paper proposes an identification method of location errors on a five-axis machine tool with a tilting head by a set of machining patterns. The machining patterns are proposed under the assumption that the influence of motion errors of each axis on the measuring results is sufficiently small. Location errors of both linear and rotary axes can be decoupled and identified. During the measuring of linear axes squareness errors, a new machining method that significantly increases the moving distances of linear axes without additional removal of material or enlarged volume of the workpiece is proposed. Also, a decoupling method of linear and rotary axes squareness errors relevant to this new machining method is introduced. The measuring accuracy of linear axes squareness errors is greatly improved based on these measuring schemes. The machining tests are performed on a commercial five-axis machine tool with a tilting head. The measurement results are acquired on a coordinate measuring machine, and the identification results are validated by comparing the geometric characteristics of workpieces before and after compensation. [ABSTRACT FROM AUTHOR]

This paper aims to review and discuss the empirical research that investigates the relationships among integration, uncertainty, information quality (IQ), and firm performance. A conceptual framework to classify the reviewed works is also proposed. The scope of the review comprises papers from 2001 to 2013, but some older publications were reviewed in order to recall some classical definitions of the constructs. A comprehensive look at these studies revealed the fragmented nature of this body of knowledge as well as dissimilarities in the definition of the constructs. Most of the research focuses on the dyadic relationship between integration and performance, moderated or not by uncertainty. Thus, the literature lacks more empirical evidence regarding the integration-IQ and the uncertainty-IQ relationships. This paper contributes to the scientific field by the following: considering all these four constructs together in a literature review; synthesizing the growing body of knowledge on these topics; and presenting a critical analysis. Researchers that want to further investigate this subject may use this paper as a starting point. Managers' understanding of these empirical relationships can be improved. [ABSTRACT FROM AUTHOR]

As an underactuated mechanism, the accuracy analysis of the spherical 3 degrees of freedom (3-DOF) parallel underactuated robot wrist becomes an important issue. However, current researches in the accuracy analysis always focus on the full-actuated mechanism. In this paper, the loop incremental method is applied to the accuracy analysis of the spherical 3-DOF parallel underactuated robot wrist. After the novel underactuated robot wrist is introduced, this paper presents the loop selection rules. According to the above rules, four loops are selected from the underactuated robot wrist. After error model of each loop is proposed, the error model of the underactuated robot wrist, including both position error and orientation error, is then established by the loop incremental method. After the accuracy analysis of the underactuated robot wrist is verified with the experiments on coordinate measuring machine, the robot wrist is then guided to be assembled with the minimum global error. The result is testified to demonstrate that the methodology is helpful for robot design. [ABSTRACT FROM AUTHOR]

This paper presents an experimental evaluation of the performance of cubic boron nitride (CBN) tools in the machining of high-chromium white cast iron. Two types of CBN tool materials were evaluated in the tests, including polycrystalline cubic boron nitride (pCBN) and binder-less crystalline cubic boron nitride (bCBN). Performance in terms of the levels of cutting forces, tool wear, surface roughness and process stability was evaluated during and after cutting tests. The work materials used in the cutting tests included two groups with chemical compositions of two levels of carbon silicon (lower C-Si and higher C-Si) in as-cast and hardened states, respectively. Test results indicate that the cutting tool materials clearly exhibited different behaviour in the machining of high-chromium white cast iron. The pCBN tools demonstrated lower tool wear rates than the bCBN tools but had higher roughness levels on the workpiece surfaces. The cutting tools also behaved differently according to the different levels of C-Si content and heat treatment of the work materials. In addition, the study reveals the mechanism of the interactions between CBN tools and high-chromium white cast iron under a range of machining parameters. [ABSTRACT FROM AUTHOR]

The flow of commercial returns, products returned by customers for any reason within 90 days of sale, is a significant concern for many manufacturers. The total value of these returns is estimated at about $100 billion a year in the USA. In order to reduce their negative impacts on the environment and prevent high disposal costs, these returned products need to be properly handled, processed, and, if applicable, remanufactured, recycled, or reused. However, since the primary focus of most manufacturers is the forward supply chain, a large proportion of the returned products' value is lost. Two key decision policies affecting the performance of such systems are the target quality for components used in the primary product and duration of the time returned products are accumulated before they are remanufactured. High targeted quality increases the production cost but cuts on product return rate. Long accumulation time, on the other hand, increases production lot sizes for remanufacturing that results lower remanufacturing costs per unit product. When there is a market for remanufactured products the tradeoff between profit from selling primary products and that of remanufactured units may justify targeting a lower than perfect quality and still maximize the total profit. And this could be achieved without negative effects on environment. In this work, a model for a forward/reverse supply chain is developed to satisfy a fixed demand with a combination of new and remanufactured products. The objective is to maximize the total profit as a function of two above decision factors. The application of the proposed model has been demonstrated by several numerical examples. [ABSTRACT FROM AUTHOR]

The problem dealt with in this study has job sequence-dependent setup times under suitable machine constraints and due date constraints. The performance criterion for this problem is to minimize the sum of makespan and total tardiness. In the literature, an application of ABC algorithm for the problems which includes all the properties that we have dealt has not been discussed. Because there is no appropriate test data, a real-life data was collected from a factory. In this study, a new approach has been proposed for the solution with meta-heuristics of unrelated parallel machine scheduling problems which is a combinatorial problem. This new neighborhood approach provides different machine assignments for every candidate job sequences. This approach is used by integrating into ABC and GA. To evaluate the performances of the algorithms, the real-life problem was solved by using ABC and GA algorithms under similar conditions. It was found that all jobs can be completed in two shifts without the need for a third shift. Computational results show that ABC algorithm has better performance than GA. [ABSTRACT FROM AUTHOR]

This work concentrated on the machined surface properties produced by the multi-axis ball-end milling process in order to enhance the high-performance application of multi-axis ball-end milling technology. The cutting speed of the engaged cutting edges and machining characteristics under various inclination angles were analyzed. The effects of inclination angles on the machined surface hardness, residual stresses, surface textures, topographies, and roughness were investigated under up-milling and down-milling conditions. Under up-milling condition, the machined surface hardness with regard to various tilt angles are larger than the ones under corresponding lead angles, and the variations of surface hardness with increasing lead angles are not apparent. In down-milling condition, double-peaks shape appears in the changing curve of surface hardness with increasing tilt and lead angles. The residual stresses present the overall trend of firstly increasing, then decreasing, and finally increasing with the increasing tilt angle from −45 to 45°. The surface residual stresses in both feed and cross-feed directions firstly decrease, and then increase with the increasing lead angle. Under both up-milling and down-milling, the compressive residual stresses significantly appear at the tool inclination angles near 0° due to extrusion action of the cutting edges close to tool tip and the low effective cutting speed. For down-milling condition, the surface textures are approximately parallel with the feed direction when using tilt angles with large values, and are approximately perpendicular to feed direction under varying lead angles. The apparent machining marks under negative tilt angles with relatively larger absolute values and obvious regular surface patterns corresponding to positive tilt angles could be observed. More surface pits and burrs and circular arc textures probably appear under small tilt angles and lead angles near 0°. [ABSTRACT FROM AUTHOR]

A naïve Bayes classifier method for tool condition monitoring is described. End-milling tests were performed at different spindle speeds and the cutting force was measured using a table-mounted dynamometer. The effect of tool wear on force features in the time and frequency domains was evaluated and used for training the classifier. The amount of tool wear was predicted using the naïve Bayes classifier method. Two cases are presented. First, the tool wear is divided into discrete states based on the amount of flank wear and the probability of the tool wear being in any state is updated using force data. Second, a continuous case is considered and the probability density function of the tool flank wear width is updated. The results are discussed. [ABSTRACT FROM AUTHOR]

Flexible manufacturing system (FMS) is a programmable manufacturing system, and the performance of the system an important factor determined by the layout of the machines. The main aim is to find out an optimal design of a unidirectional loop layout network. Evaluation of this layout is usually performed by estimating the traffic congestion, which is defined as the number of times a part traverses the loop before its processing is completed. In this paper, sheep flock heredity algorithm (SFHA) is proposed for solving the unidirectional loop layout problem with the consideration of both min_sum and min_max objectives. In SFHA, the pairwise mutation process is replaced by single-point mutation process, which guarantees the feasibility of the solutions in the local search domain. Chromosomal crossover is replaced by robust-replace heuristic to enhance the global search. Metaheuristic procedure is tested on small-sized bench mark problems, and two large-sized hypothetical problems are randomly generated. The computational results show that the SFHA algorithm is efficient in solving the small-sized bench mark problems with min_max approach and produces good quality solutions comparatively. The min_sum approach outperforms the min_max approach for two large-sized hypothetical problems. [ABSTRACT FROM AUTHOR]

The abrasive water jet (AWJ) taper inside the cut material is one of the characteristic phenomena of the AWJ cutting. The taper, together with a retardation of the jet inside the kerf, causes deformation of workpieces, especially in corners and curvatures. Some deviations of the side walls from the plains perpendicular to the material surface can be observed and measured even in the straight line parts of trajectories. This paper is aimed at experimental research of this phenomenon on steels because precision cutting of stainless and hard steels with thicknesses over 10 mm is a serious problem in practice, and the AWJ cutting can solve this problem quite well. The experiments were performed on three sets of steel plates with thicknesses close to 30 mm. The steels of the first and the second set were identical (1.2379, 1.3343, 1.4307, 1.4404 and 1.4845). The steels of the first set were cut in their normal states, and the steels of the second set were subjected to cooling in the liquid nitrogen prior to cutting (marked 1.abcd/N). The third set of samples consisted of steels with very different composition and brittle/ductile behaviour cut in their normal states (1.0036, 1.2767, 1.3379, 1.7225 and 1.7733). The model for calculation of the limit traverse speed from both the jet parameters and material properties has been used for determination of the proper traverse speed scale. The widths of the cuts were measured both on the top and on the bottom of the slots. The difference between these widths has been used for evaluation of the inclination angle, i.e. the wall deviation from the plane perpendicular to the material surface, referred also as the taper. This angle can be used for determination of the tilting angle for compensation of the negative influence on workpiece. The influence of brittle/ductile behaviour and the influence of cooling in liquid nitrogen have been tried to find out. The results were also compared with the theoretical relationship between traverse speed and inclination angle (the taper) on steels presented as a result of previous investigations in scientific articles. The difference between the inlet and the outlet width of kerf made by AWJ in tested steels ranges from 5.2 to 35.4 % for the traverse speed of 5 mm min and from 25.5 to 44.9 % for the traverse speed of 50 mm min. [ABSTRACT FROM AUTHOR]

In this paper, a new and innovative method for the patterning of grinding wheels is presented. The patterns are machined with a patterning tool by using fly-cutting kinematics. By changing the patterning process parameters, different pattern sizes and densities can be machined in a flexible way. Surface and cylindrical grinding experiments show that grinding with patterned grinding wheels can significantly reduce process forces, grinding burn, and grinding power. The surface roughness increases because less active cutting edges remain when grinding with patterned wheels. But especially for roughing processes, the results show great potential for increasing the overall grinding performance. [ABSTRACT FROM AUTHOR]