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The purpose of this paper is to study the corrosion resistance and the insulating characteristics of an environment‐friendly chromium‐free coating on electrical steel.

A water‐based semi‐inorganic environment‐friendly insulating coating on electrical steel was developed. The coating system of silane coupling agent and rare earth salt were used first in this coating to replace the chromate containing coating. In this study, it provided a successful combination of coating and passivation.

Several test results, such as insulating ability, corrosion resistance, adhesion strength and hardness, showed that the performance of the film complied fully with the industry standards, particularly excellent in its corrosion resistance and the maximum corrosion resistance (neutral salt‐spray test) time up to 20 h.

There have been few reports on the chromium‐free insulating coating on electrical steel, and described in the paper, this environment‐friendly insulating coating on electrical steel was found to be highly effective.

In shield tunneling projects, human, shield machine and underground environment are tightly coupled and interacted. Accidents often occur under dysfunctional interactions among them. Therefore, this paper aims to develop a multi-agent based safety computational experiment system (SCES) and use it to identify the main influential factors of various aspects of human, shield machine and underground environment.

The methods mainly comprised computational experiments and multi-agent technologies. First, a safety model with human-machine-environment interaction consideration is developed through the multi-agent technologies. On this basis, SCES is implemented. Then computational experiments are designed and performed on SCES for analyzing safety performance and identifying the main influential factors.

The main influential factors of two common accidents are identified. For surface settlement, the main influential factors are ranked as experience, soil density, soil cohesion, screw conveyor speed and thrust force in descending order of influence levels; for mud cake on cutter, they are ranked as soil cohesion, experience, cutter speed and screw conveyor speed. These results are consistent with intuition and previous studies and demonstrate the applicability of SCES.

The proposed SCES provides comprehensive risk factor identification for shield tunneling projects and also insights to support informed decisions for safety management.

A safety model with human-machine-environment interaction consideration is developed and computational experiments are used to analyze the safety performance. The novel method and model could contribute to system-based safety research and promote systematic understanding of the safety performance of shield tunneling projects.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

Additive manufacturing (AM) has been increasingly used in various applications in recent years. However, it is still challenge when it comes to selecting a suitable AM process. This is because the outcome may vary due to not only different materials and printers but also different parameters and post-processes. This paper aims to develop an efficient method to help users understand trade-offs and make right decisions.

A hybrid method is proposed to help users select appropriate options from a large-scale and discrete option space in an interactive way. First, the design-by-shopping approach is applied to allow users exploring and refining the option space. The analytical hierarchical process method is then used to capture customers’ preferences. After analyzing the results of different normalization methods, a modified Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach is proposed to rank solutions and provide suggestions.

The usefulness of proposed method is illustrated in a case study. The results show that it can help customers understand performance distributions and find most suitable options accurately. The ranking of the modified TOPSIS method is more reasonable.

Due to the complexity of AM technologies, the process selection is considered at the parameter level. A new system framework is proposed for decision support. The TOPSIS method is modified to achieve a stable performance.

The purpose of this paper is to provide an optimization schedule of structural parameters for the sound absorption performance of a cellular ceramic foam in the sound frequency range of 200–4,000 Hz.

The cellular ceramic foam with porosity of about 60–75% and the pore size of about 1–7 mm was successfully prepared by using natural zeolite powder as the main raw material. For this ceramic foam, the sound absorption performance was measured, and the absorption structure was optimized by some important structural parameters. With orthogonal experiment, optimization of structural parameters was found for absorption performance. By means of the range analysis method, the main factor is known to influence the performance of ceramic foam.

The present ceramic foam may have good absorption performance although at relatively low frequencies of 400–4,000 Hz while structural parameters of sample are appropriately combined. With orthogonal experiment, optimization of structural parameters for the absorption performance was found to be as follows: sample thickness, 25 mm; porosity, 73.5%; pore size, 4–5 mm and air gap depth, 20 mm. To influence the performance, sample thickness is the main factor, air gap depth is the second and both of pore size and porosity would have a relatively slight effect.

This paper presents a method to optimize the structural parameters of a cellular ceramic foam for sound absorption performance by means of orthogonal experiment.

The grasping task of robots in dense cluttered scenes from a single-view has not been solved perfectly, and there is still a problem of low grasping success rate. This study aims to propose an end-to-end grasp generation method to solve this problem.

A new grasp representation method is proposed, which cleverly uses the normal vector of the table surface to derive the grasp baseline vectors, and maps the grasps to the pointed points (PP), so that there is no need to add orthogonal constraints between vectors when using a neural network to predict rotation matrixes of grasps.

Experimental results show that the proposed method is beneficial to the training of the neural network, and the model trained on synthetic data set can also have high grasping success rate and completion rate in real-world tasks.

The main contribution of this paper is that the authors propose a new grasp representation method, which maps the 6-DoF grasps to a PP and an angle related to the tabletop normal vector, thereby eliminating the need to add orthogonal constraints between vectors when directly predicting grasps using neural networks. The proposed method can generate hundreds of grasps covering the whole surface in about 0.3 s. The experimental results show that the proposed method has obvious superiority compared with other methods.

The purpose of this paper is to investigate the effects of parameters on the liquid phase migration (LPM) during the freeze-form extrusion fabrication (FEF) process.

To carry out this study, three factors were systematically investigated using orthogonal design of experiments. These three parameters are the extrusion velocity, the extrusion interval time and the extrusion head length. An orthogonal array with nine test units was selected for the experiments. Range analysis and analysis of variance were used to analyze the data obtained by the orthogonal experiments to identify the order of significant factors on LPM.

It was found that the LPM decreased with the increase of extrusion velocity and increased with the lengthening of extrusion interval time and the length of the extrusion nozzle. The order of significant factors for the LPM were found to be extrusion velocity > extrusion nozzle length > extrusion interval time.

Using an orthogonal design of experiments and a statistical analysis method, the liquid content of extrudate can be predicted and appropriate process parameter values can be selected. This leads to the minimization of LPM during the FEF process. Also, this analysis method could be used to study the LPM in other paste extrusion processes.

This paper suggests that the factors have significant impact on LPM during FEF process. The following analysis in this paper is useful for FEF users when prediction of LPM is needed. This methodology could be easily applied to different materials and initial conditions for optimization of other FEF-type processes. The research can also help to get better understanding of LPM during the FEF process.

The purpose of this paper is to determine the impact level of parameters affecting wing design at low speeds using Taguchi method.

Using brain storming approach airfoil shape, wing angle of attack and Reynolds number are determined as important wing design parameters. Most important parameters over these parameters are determined using Taguchi method. The lift-to-drag ratio (CL/CD ratio) is chosen as the performance criterion and L8 orthogonal index is chosen as experimental study scheme for this study.

Experimental results are examined using Taguchi method. After making experiments and also analyses, Reynolds number is found as the most important and identifier parameter for aircraft wing design.

Taguchi method makes the experimental design for experimental studies. This method reduces the number of experiments substantially using orthogonal indices while keeping effects of uncontrolled parameters to a minimum. Reduction in number of experiments helps save time and also cost.

In this study, with less number of experiments, the most important parameter for aircraft wing design is determined. Moreover, with less number of experiments, not only is time saved but the design stage is also made faster.

The aim of this paper is to circumvent the multi‐distribution effects and small sample constraints that may arise in unreplicated‐saturated fractional factorial designs during construction blueprint screening.

A simple additive ranking scheme is devised based on converting the responses of interest to rank variables regardless of the nature of each response and the optimization direction that may be issued for each of them. Collapsing all ranked responses to a single rank response, appropriately referred to as “Super‐Ranking”, allows simultaneous optimization for all factor settings considered.

The Super‐Rank response is treated by Wilcoxon's rank sum test or Mann‐Whitney's test, aiming to establish possible factor‐setting differences by exploring their statistical significance. An optimal value for each response is predicted.

It is stressed, by example, that the model may handle simultaneously any number of quality characteristics. A case study based on a real geotechnical engineering project is used to illustrate how this method may be applied for optimizing simultaneously three quality characteristics that belong to each of the three possible cases, i.e. “nominal‐is‐best”, “larger‐is‐better”, and “smaller‐is‐better” respectively. For this reason, a screening set of experiments is performed on a professional CAD/CAE software package making use of an L₈(2⁷) orthogonal array where all seven factor columns are saturated by group excavation controls.

The statistical nature of this method is discussed in comparison with results produced by the desirability method for the case of exhausted degrees of freedom for the error. The case study itself is a unique paradigm from the area of construction operations management.