A Novel Method for Handicrafts Design Based on Fusion of Multi-Intelligent Decision Algorithm

With the rapid development of artificial intelligence, handicraft design has developed from artificial design to artificial intelligence design. Traditional handicraft design has the problems of long time consumption and low output, so it is necessary to improve the process technology. Artificial intelligence technology can provide optimized design steps in handicraft design and improve design efficiency and process level. Handicrafts are regarded as important social products and exist in people’s daily life. In the current society, many people do handicrafts and there are major exhibitions. Furthermore, the display of handicrafts is also very grand and shocking. In the design of handicrafts, the traditional design method cannot completely keep up with the production speed and efficiency of handicrafts. Therefore, this paper adopts the fusion multi-intelligent decision algorithm of multi-node branch design in the design method of handicraft. The algorithm model combination is used to analyze and design the layout of the handicraft, which speeds up the design efficiency and production of the handicraft. In this paper, two intelligent algorithms will be used for fusion; they are genetic algorithm and GA-PSO fusion algorithm obtained by particle swarm optimization and they are embedded in handicraft design method for application through mathematical model construction and function construction. After comparing the performance parameter index data of three intelligent algorithms and GA-PSO fusion algorithm, it is obtained that GA-PSO fusion algorithm is 97% correct and has 82% readability, 72% robustness, and 61% structure, making it have better important indicators. Four algorithms optimize each design problem in all aspects of handicraft design at present. Design efficiency, image distribution rate, image optimization degree, and image clarity are compared by simulation experiments. Compared with three intelligent algorithms, traditional design methods, and manual design methods, GA-PSO fusion algorithm can effectively improve the design method and design effect of handicrafts with 92.1% design efficiency, 82.7% image distribution rate, 94.3% image optimization degree, and 84% layout void rate. Finally, the space complexity experiment of four algorithms shows that GA-PSO algorithm can achieve 9.73 dispersion with 11.42 space complexities, which makes the dimension reduction relatively stable, and the algorithm can maintain stability in the design and application of handicrafts.

Feasibility-Based Design Model For Road Vertical Alignment

Road vertical alignment design is a multi-objective design problem that needs to consider multiple constraints. Intelligent design based on optimization algorithms cannot wholly solve problems, such as multi-objective, uncertainty, and constraint dynamics. The article proposes a model of dynamically transforming design constraints into feasible regions as the design develops, to provide decision information before design actions rather than performing constraint evaluation after the design that reduces the empirical estimation. The design actions are divided into new design actions and modifying design actions, and corresponding feasible regions derived from constraints of design specifications and control elevations are established, respectively. Geometrical equations and program algorithms of feasible regions are described in the graphic environment, which is applied to the vertical alignment design to improve the design efficiency and decision-making level.

Aspects Regarding the Redesign of a Component of the Vertical Lifting Module Used in Sustainable Production Management

To remain competitive on the market with a developed product, it’s very important to analyze the manufacturing costs and times, from the concept stage of the product. Design for manufacturing and assembly (DFMA) is one of the engineering methods that can be applied to reduce manufacturing costs and times, right from the design stage, without compromising product performance and reliability. The 3D modeling of the tray was made in Solidworks, and for the analysis of it’s manufacture and assembly, the Boothroyd and Dewhurst principle and recommendations from the DFMA software were followed. This paper presents a case study for a subassembly called a tray, used in automatic vertical storage systems. For the redesigned model, substantial improvements were obtained, through cost reductions of 12% and an increase in design efficiency from 4.86 to 12.03. Product analysis using DFMA has proven to be a key point in the development of a product that meets engineers.

Research on the rapid design technology of automotive inspection structure based on MBD model

In view of the specificity and low efficiency of the design of automobile inspection fixture, a deformation design method of inspection fixture based on BP neural network algorithm is proposed. BP neural network algorithm is used to realize the learning and classification of case knowledge, and FCM (fuzzy c-means) algorithm and kernel principal component analysis are used to optimize the information source to improve the retrieval efficiency and accuracy. Based on the analysis of the existing fixture design case structure, the case structure is skeletonized to increase the applicability of the case structure. At the same time, the case frame structure is associated with the size chain, the priority deformation rule is proposed, and the relationship of each size chain is established to realize the mutual adjustment of each size chain. From the similarity of retrieval cases, the paper proposes the design scheme of inspection tools to improve the design efficiency. Finally, taking the front bumper model as the experimental object, the deformation rules are compared, and the priority deformation rule is more accurate than the ordinary basic rule. Compared with the manual design, the design efficiency of this method is improved by 55.71%, which proves the feasibility of this method.

Modularization and Parametric Design of Airborne Electronic Equipment Structure

In order to improve the design efficiency and quality of traditional airborne electronic equipment, the structural forms of traditional equipment are summarized. Based on the creation of basic structure modules, the parametric design of series structure modules and access devices is carried out. According to the functional requirements of the equipment, different series of structural modules are selected, combined and installed in the access device to quickly realize the modular design of airborne electronic equipment. A series of structural modules are repeatedly applied on a variety of equipment to improve the design reliability.

Efficient NC Process Scheme Generation Method Based on Reusable Macro and Micro Process Fusion

Process reuse technology has been widely studied and applied in manufacturing industry. However, the current NC process reuse generally assumes that the micro process is compatible with the macro process, but in fact, the reusable processes from the similar local structures of multiple parts are usually difficult to be compatible with each other under the overall manufacturing requirements of the query parts, which leads to the fact that a large amount of user interactions are still required for modification and adjustment in practical engineering applications, so it is not significant to improve the design efficiency. Therefore, an efficient NC process scheme generation method based on reusable macro and micro process fusion is proposed in this paper. Firstly, according to the calculation of semantic distance of process design intention, the micro processes are mapped to the macro process to realize the fusion of the macro process and the micro process, and a compatibility credibility evaluation model is established to evaluate the compatibility of fusion results. Then, when the fusion result is credible, the machining areas corresponding to the process scheme are adjusted and optimized from the geometric level. The adjustment and optimization of machining areas mainly realize the integration of machining areas and the optimization of machining sequence. Finally, the effectiveness and feasibility of the proposed method are verified by the test of actual parts.

Effects of Brace Stiffness and Nonlinearity of Viscous Dampers on Seismic Performance of Structures

In the applications of supplemental dampers for seismic hazard mitigation, the supporting braces for the dampers are considered an important component for ensuring an efficient energy dissipation in the structure. Despite their importance, studies on the effects of the brace stiffness and the velocity exponent in the case of nonlinear viscous dampers are rather limited. In this paper, a numerical time-stepping method is developed for computing the seismic response of the structure with supporting braces and nonlinear viscous dampers. Using the proposed method, effects of the parameters of the nonlinear damper-brace systems are investigated, using first a single-story structure, followed by multi-story buildings. Results indicated that the design parameters for the dampers and supporting braces may be combined in numerous ways to satisfy a given set of structural performance objectives, but the brace stiffness can be minimized to achieve design efficiency in the range of velocity exponent commonly used for seismic applications of nonlinear viscous dampers. Results also indicated that for a set brace stiffness, if the dampers are optimally designed, the velocity exponent has an insignificant effect on the structural seismic performance objectives considered in this paper.

Constructing robust and efficient experimental designs in groundwater modeling using a Galerkin method, proper orthogonal decomposition, and metaheuristic algorithms

Estimating parameters accurately in groundwater models for aquifers is challenging because the models are non-explicit solutions of complex partial differential equations. Modern research methods, such as Monte Carlo methods and metaheuristic algorithms, for searching an efficient design to estimate model parameters require hundreds, if not thousands of model calls, making the computational cost prohibitive. One method to circumvent the problem and gain valuable insight on the behavior of groundwater is to first apply a Galerkin method and convert the system of partial differential equations governing the flow to a discrete problem and then use a Proper Orthogonal Decomposition to project the high-dimensional model space of the original groundwater model to create a reduced groundwater model with much lower dimensions. The reduced model can be solved several orders of magnitude faster than the full model and able to provide an accurate estimate of the full model. The task is still challenging because the optimization problem is non-convex, non-differentiable and there are continuous variables and integer-valued variables to optimize. Following convention, heuristic algorithms and a combination is used search to find efficient designs for the reduced groundwater model using various optimality criteria. The main goals are to introduce new design criteria and the concept of design efficiency for experimental design research in hydrology. The two criteria have good utility but interestingly, do not seem to have been implemented in hydrology. In addition, design efficiency is introduced. Design efficiency is a method to assess how robust a design is under a change of criteria. The latter is an important issue because the design criterion may be subjectively selected and it is well known that an optimal design can perform poorly under another criterion. It is thus desirable that the implemented design has relatively high efficiencies under a few criteria. As applications, two heuristic algorithms are used to find optimal designs for a small synthetic aquifer design problem and a design problem for a large-scale groundwater model and assess their robustness properties to other optimality criteria. The results show the proof of concept is workable for finding a more informed and efficient model-based design for a water resource study.

Bone morphological feature extraction for customized bone plate design

Fractures are difficult to treat because of individual differences in bone morphology and fracture types. Compared to serialized bone plates, the use of customized plates significantly improves the fracture healing process. However, designing custom plates often requires the extraction of skeletal morphology, which is a complex and time-consuming procedure. This study proposes a method for extracting bone morphological features to facilitate customized plate designs. The customized plate design involves three major steps: extracting the morphological features of the bone, representing the undersurface features of the plate, and constructing the customized plate. Among these steps, constructing the undersurface feature involves integrating a group of bone features with different anatomical morphologies into a semantic feature parameter set of the plate feature. The undersurface feature encapsulates the plate and bone features into a highly cohesive generic feature and then establishes an internal correlation between the plate and bone features. Using the femoral plate as an example, we further examined the validity and feasibility of the proposed method. The experimental results demonstrate that the proposed method improves the convenience of redesign through the intuitive editing of semantic parameters. In addition, the proposed method significantly improves the design efficiency and reduces the required design time.