Search results

Adaptive slicing is a key step in 3D printing as it is closely related to the building time and the surface quality. This study aims to develop an adaptive layering algorithm that can coordinate the optimization of printing quality and efficiency to meet different printing needs.

A multiobjective optimization model is established for printing quality, printing time and layer height based on the variation of surface features, profile slope and curvature of the model. The optimal solution is found by an improved method combining Newton's method and gradient method and adapts to different printing requirements by adjusting the parameter thresholds.

Several benchmarks are applied to verify this new method. The proposed method has also been compared with the uniform layering method, it reduces the volume error by 46.4% and shortens the printing time by 28.1% and is compared with five existing adaptive layering methods to demonstrate its superior performance.

Compared with other methods with only one layered result, this method is a demand-oriented algorithm that can obtain different results according to different needs and it can reach a trade-off between the building time and the surface quality.

This paper aims to establish the predictive equations of height, area and volume of printed solder paste during solder paste stencil printing (SPSP) process in surface mount technology (SMT) to better understand the effect of process parameters on the printing quality.

An experiment plan is proposed based on the response surface method (RSM). Experiments with 30 different combinations of process parameters are performed using a solder paste printer. After printing, the volume, area and height of the printed SAC105 solder paste are measured by a solder paste inspection machine. Using RSM, the predictive equations associated with the printing parameters and the printing quality of the solder paste are formed.

The optimal printing parameters are 175.08 N printing pressure, 250 mm/s printing speed, 0.1 mm snap-off height and 15.7 mm/s stencil snap-off speed if the target height of solder paste is 100 µm. As the target printing area of solder paste is 1.1 mm × 1.3 mm, the optimized values of the printing parameters are 140.29 N, 100.52 mm/s, 0.63 mm and 20.25 mm/s. When both the target printing height and area are optimized together, the optimal values for the four parameters are 86.67 N, 225.76 mm/s, 0.15 mm and 1.82 mm/s.

A simple RSM-based experimental method is proposed to formulate the predictive polynomial equations for height, area and volume of printed solder paste in terms of important SPSP parameters. The predictive equation model can be applied to the actual SPSP process, allowing engineers to quickly predict the best printing parameters during parameter setting to improve production efficiency and quality.

The purpose of this paper is to propose a unified optimization design method and apply it to handle the brake squeal instability involving various uncertainties in a unified framework.

Fuzzy random variables are taken as equivalent variables of conventional uncertain variables, and a unified response analysis method is first derived based on level-cut technique, Taylor expansion and central difference scheme. Next, a unified reliability analysis method is developed by integrating the unified response analysis and fuzzy possibility theory. Finally, based on the unified reliability analysis method, a unified reliability-based optimization model is established, which is capable of optimizing uncertain responses in a unified way for different uncertainty cases.

The proposed method is extended to perform squeal instability analysis and optimization involving various uncertainties. Numerical examples under eight uncertainty cases are provided and the results demonstrate the effectiveness of the proposed method.

Most of the existing methods of uncertainty analysis and optimization are merely effective in tackling one uncertainty case. The proposed method is able to handle the uncertain problems involving various types of uncertainties in a unified way.

Structural performance of additively manufactured parts is deposition path-dependent because of the induced material anisotropy. Hence, this paper aims to contribute a novel idea of concurrently performing the deposition path planning and the structural topology optimization for additively manufactured parts.

The concurrent process is performed under a unified level set framework that: the deposition paths are calculated by extracting the iso-value level set contours, and the induced anisotropic material properties are accounted for by the level set topology optimization algorithm. In addition, the fixed-geometry deposition path optimization problem is studied. It is challenging because updating the zero-value level set contour cannot effectively achieve the global orientation control. To fix this problem, a level set-based multi-step method is proposed, and it is proved to be effective.

The proposed concurrent design method has been successfully applied to designing additively manufactured parts. The majority of the planned deposition paths well match the principle stress direction, which, to the largest extent, enhances the structural performance. For the fixed geometry problems, fast and smooth convergences have been observed.

The concurrent deposition path planning and structural topology optimization method is, for the first time, developed and effectively implemented. The fixed-geometry deposition path optimization problem is solved through a novel level set-based multi-step method.

In general, the optimal reactive power compensation could drastically enhance the performance of distributed network by the reduction of power loss and by enhancement of line loadability and voltage profile. Till now, there exist various reactive power compensation models including capacitor placement, joined process of on-load tap changer and capacitor banks and integration of DG. Further, one of the current method is the allocation of distribution FACTS (DFACTS) device. Even though, the DFACTS devices are usually used in the enhancement of power quality, they could be used in the optimal reactive power compensation with more effectiveness.

This paper introduces a power quality enhancement model that is based on a new hybrid optimization algorithm for selecting the precise unified power quality conditioner (UPQC) location and sizing. A new algorithm rider optimization algorithm (ROA)-modified particle swarm optimization (PSO) in fitness basis (RMPF) is introduced for this optimal selections.

Through the performance analysis, it is observed that as the iteration increases, there is a gradual minimization of cost function. At the 40th iteration, the proposed method is 1.99 per cent better than ROA and genetic algorithm (GA); 0.09 per cent better than GMDA and WOA; and 0.14, 0.57 and 1.94 per cent better than Dragonfly algorithm (DA), worst solution linked whale optimization (WS-WU) and PSO, respectively. At the 60th iteration, the proposed method attains less cost function, which is 2.07, 0.08, 0.06, 0.09, 0.07 and 1.90 per cent superior to ROA, GMDA, DA, GA, WS-WU and PSO, respectively. Thus, the proposed model proves that it is better than other models.

This paper presents a technique for optimal placing and sizing of UPQC. To the best of the authors’ knowledge, this is the first work that introduces RMPF algorithm to solve the optimization problems.

Although the multi-criteria technique analytic hierarchy process (AHP) has successfully been applied in many areas, either selecting or ranking alternatives or to derive priority vector (weights) for a set of criteria, there is a significant drawback in using this technique if the pairwise comparison matrix (PCM) has inconsistent comparisons, in other words, a consistency ratio (CR) above the value of 0.1, the final solution cannot be validated. Many studies have been developed to treat the inconsistency problem, but few of them tried to satisfy different quality measures, which are minimum inconsistency (fMI), the total number of adjusted pairwise comparisons (fNC), original rank preservation (fKT), minimum average weights adjustment (fWA) and finally, minimum L1 matrix norm between the original PCM and the adjusted PCM (fLM).

The approach is defined in four steps: first, the decision-maker should choose which quality measures she/he wishes to use, ranging from one to all quality measures. In the second step, the authors encode the PCM to be used in a many-objective optimization algorithm (MOOA), and each pairwise comparison can be adjusted individually. The authors generate consistent solutions from the obtained Pareto optimal front that carry the desired quality measures in the third step. Lastly, the decision-maker selects the most suitable solution for her/his problem. Remarkably, as the decision-maker can choose one (mono-objective), two (multi-objective), three or more (many-objectives) quality measures, not all MOOAs can handle or perform well in mono- or multi-objective problems. The unified non-sorting algorithm III (U-NSGA III) is the most appropriate MOOA for this type of scenario because it was specially designed to handle mono-, multi- and many-objective problems.

The use of two quality measures should not guarantee that the adjusted PCM is similar to the original PCM; hence, the decision-maker should consider using more quality measures if the objective is to preserve the original PCM characteristics.

For the first time, a many-objective approach reduces the CR to consistent levels with the ability to consider one or more quality measures and allows the decision-maker to adjust each pairwise comparison individually.

Considers the problem of determining economic statistical np‐control chart designs under the fuzzy environment of closely satisfying type I and II errors. Goes on to model the problem as fuzzy mathematical programming, and uses a heuristic method to obtaining the solution.

Focuses on the inverse problems arising from the simulation of forming processes. Considers two sets of problems: parameter identification and shape optimization. Both are solved using an optimization method for the minimization of a suitable objective function. The convergence and convergence rate of the method depend on the accuracy of the derivatives of this function. The sensitivity analysis is based on a discrete approach, e.g. the differentiation of the discrete problem equations. Describes the method for non‐linear, non‐steady‐state‐forming problems involving contact evolution. First, it is applied to the parameter identification and to the torsion test. It shows good convergence properties and proves to be very efficient for the identification of the material behaviour. Then, it is applied to the tool shape optimization in forging for a two‐step process. A few iterations of the inverse method make it possible to suggest a suitable shape for the preforming tools.

This paper aims to review the literature on carbon trading from the perspective of evolution, finds out the evolution path of these literatures and gives out the future research hotspots in this field.

Uses visualization tools (CiteSpace and HistCite) to systematically categorize the literature on carbon-trading schemes in the Web of Science core collection from 1998 to 2018, comprehensively analyzes carbon-trading schemes from four dimensions, namely, discipline evolution, keyword evolution, citation cluster evolution and citation path evolution.

Research on carbon-trading schemes has a specific development and evolution path along four dimensions, namely, in the discipline dimension, the largest change lies in the mathematics pointed to by at least four different disciplines; the keyword evolution dimension shows a gradual deepening emphasis on coordinated development; citation clusters identify three major clusters – carbon prices, China’s carbon trading, carbon market and supply chain; and citation paths identify three major evolutionary paths, the most important of which shows that “What affects carbon price?” has changed to “What is the impact of carbon prices?”

Reveals the evolution path of carbon trading research studies and proposes four possible development directions for carbon-trading scheme research, which is helpful for future carbon trading-related research and serves as a reference for the promotion of and improvements in carbon-trading schemes.

Discusses the economic designs of np charts for a single assignable cause. Develops a simple algorithm to get the optimum designs of np charts. Twenty numerical examples show that the algorithm is very efficient and accurate indeed.