Experience Of Designer Research Articles

Combining deep learning with knowledge graph for macro process planning

The macro process, as the core process content of the whole machining process for a design part, serves as a guide for the complete machining process planning. It determines the final machining quality and machining cost of the part to a large extent. However, due to the various bottlenecks in machining process knowledge representation, matching, and inference, macro process planning still depends heavily on the knowledge and experience of process designers. In this paper, a macro process decision-making approach combining knowledge graph and deep learning technology is proposed. Firstly, based on deep learning, the macro process reasoning function is learned to model the mapping relationship between the process elements of the design part and macro process analysis rules. Then the process elements of the design part are fed into the reasoning function to activate the applicable process analysis rules of the process knowledge graph. Next, according to the association relationship between the activated process analysis rules and the predefined machining methods of the macro process graph, a series of working steps nodes and the directed edges are activated, which constitutes the feasible solution space for the macro process. Finally, the swarm intelligence algorithm is applied to search for an effective and low-cost macro process scheme from the feasible macro process solution space. In experimental studies, the slot cavity parts are taken as examples to verify the feasibility and effectiveness of the proposed approach.

Ontology and Emotion in Reflexive Design Practices

Ontology and Emotion in Reflexive Design Practices

Hyperparameter Optimization of Long Short-Term Memory-Based Forecasting DNN for Antenna Modeling Through Stochastic Methods

This letter presents an impressive optimization method for determining the optimal model hyperparameters of a deep neural network (DNN) targeted to model the characteristics of antennas. In this paper we propose an innovative approach of efficient yield analysis for modeling and sizing antennas. It is based on the long short-term memory (LSTM) DNN aiming to forecast the extended frequency responses, where various stochastic methods are applied for determining the optimal hyperparameters while training a DNN. Among the various methods, the one which models the antenna accurately in terms of input scattering parameter, gain, and radiation patterns is the winner. The proposed method is compact and addresses the problem of heavy reliance to the designer experience in determining the hyperparameters. Additionally, forecasting the future frequency responses of the antenna reduces the designers effort substantially in measuring large frequency band; hence, measuring whole frequency band would not be needed. For validating the effectiveness of the proposed method, the fabricated two element antenna array is used for modeling where the results demonstrate that the Thompson sampling (TS) algorithm can determine optimal hyperparameters with minimum error in comparison with other reported stochastic methods leads to predict the future frequency band accurately.

A Novel Method for Identifying Microservices by Considering Quality Expectations and Deployment Constraints

Nowadays, microservice architecture has become a dominant software development and deployment paradigm. Decomposing a system into loosely coupled, highly cohesive, and fine-grained microservices while meeting various technical constraints and implementing business capabilities is particularly important for microservice system (MS) designers. When an MS has a large number of functionalities and complex interconnections, it is a big challenge to identify microservices solely based on the experience of MS designers. We propose a structured and automated microservice identification method to decompose a system into appropriate microservices for this challenge. We model a system as unified modeling language (UML) class and sequence diagrams. In the identification phase, we take into account not only the traditional coupling-related criteria but also the quality expectation and deployment constraints, both of which have not yet been fully concerned in previous studies. Based on the criteria, a microservice identification algorithm using the clustering technique is designed. A case study of elderly care services illustrates the identification process. Experiments are conducted to evaluate and compare the proposed method against state-of-the-art methods. Results indicate that the proposed method significantly outperforms those compared from the literature.

Research on Innovative Design of Product Packaging Based on Big Data Technology

Traditional product packaging design mainly relies on the designer's personal experience and intuition, but there are problems such as uncontrollable content and lack of knowledge and guidance in the field of product design. With the development of big data technology, product packaging design in the era of big data is carried out under the support of a large amount of real data, which has high predictability, success rate, and short development cycle. Compared with structured data, unstructured data such as text, images, and audio has a higher value. Among them, text big data and image big data have good application prospects in the field of product packaging design due to their easy data acquisition, mature processing technology, and simple operation. This paper proposes a combination of big data technology and neural style transfer model and proposes an innovative design method for product packaging that can generate high-quality images and controllable content. First, the perceptual engineering theory is used to obtain user needs, to build a mapping model between product modeling elements and product semantics, and to guide the selection of product semantics and style maps; second, use neural style transfer models to reconstruct and combine the color features of style maps. After the integration, it migrated to product packaging design, based on big data product packaging innovation design methods, and developed a product innovation design auxiliary prototype system based on actual needs to improve the company’s R&D and innovation capabilities, shorten product development cycles, and reduce R&D costs. Improve product success rate and user satisfaction.

Assessment of Knowledge & Awareness among the Professionals Regarding the Concept of Safety by Design

Purpose: Recently safety by design is widely used globally in the design phase of the project itself as a proactive approach to safety management. so the overall objective of this research is to assess the knowledge & awareness among Nepalese professionals regarding the concept of Safety by Design. Design/Methodology/Approach: The study covers a systematic review of a wide range of papers using content analysis followed by a scheduled questionnaire survey. Constructivism philosophy of research was used. Piloting assures the quality of five ranking Likert scale questionnaire before the survey. ANOVA test was used to analyze the response collected. Cronbach’s alpha assures reliability and literature comparison assures validity. Findings/Result: Most of the design professionals have heard of SbD from 2011 to 2020 during the college only as satisfactory to a good understanding. Understanding of the Clients was found to be satisfactory whereas that of Contractors and Engineers in abroad was having good understanding. They rarely get to address the worker's health and safety during the design phase even after realizing high importance. Lack of sufficient guidelines, manuals, online resources, or other materials that facilitate using of the SbD approach was found. Limited knowledge regarding SbD was considered as the most important factor that restricted the use of SbD in the construction industry. Also, no regulatory provisions and designer's limited experience were the ones to restrict the use of SbD. Regarding the factors contributing to the success of SbD, design professionals agreed that legislative force is the most important factor followed by tools and guidelines related to SbD. Apart from them engaging the SbD experts and support from industry are equally important for the success of SbD. Originality/Value: It is action research. This study helps in motivating and creating awareness among the design professionals working not only in transmission lines but also to study and use the concept of safety by design in their respective fields to eliminate the hazards. Paper Type: Ex-Post Facto Research

Designing moulded pulp packaging using a topology optimization and superimpose method

AbstractMoulded pulp is a paper‐based packaging solution that is fully biodegradable and has been growing in demand due to environmental considerations. While demand has been growing, many moulded pulp packaging designs are based on the experience and knowledge of the package designer, which can lead to avoidable design issues. To solve this issue, this paper introduces a moulded pulp packaging design method using topology optimization. Topology optimization provides a systematic way to find the conceptual optimum design by minimizing strain energy. Taking the results of the topology optimization and implementing a superimpose method, the design process can be more efficient than the conventional design method. As a result, the proposed method provides a design that reduces the maximum stress of the packaging structure. With the reduction in stress, an exhaustive search method is then used to reduce the thickness of the package to decrease material usage while maintaining stress reduction.

Regional jet retrofitting through multidisciplinary aircraft design

Multidisciplinary collaborative aircraft design is applied to a 90 passengers regional jet aircraft retrofit, highlighting the impact on costs and performance. Two retrofitting packages have been considered: the re-engining of conventional power-plant platform with advanced geared turbofan and the on-board-system modernization, considering different level of electrification. Starting from a reference existing aircraft, the impact of retrofitting process has been carefully evaluated on capital costs and savings at industrial level through a developed methodology. At aircraft level, masses, performance, noise, and emissions have been computed with dedicated competences increasing the estimation reliability. Overall process is implemented in the framework of the AGILE 4.0 research project in a collaborative remote multidisciplinary approach. Results show that such retrofitting activities are expensive and must be evaluated since the design stage with a bottom-up approach requiring competences coming from designer experience to correctly define the process work-breakdown-structure and its implications.

The Rule-based Specification of the Datum-based Model for Geometric Dimensioning & Tolerancing

Geometric dimensioning & tolerancing (GD&T) is an important step in product design and manufacturing. A good GD&T design is vital to ensure the quality and manufacturability of a product. So far, a datum-based model has been utilized to expedite the GD&T design. Even though the speed has been increased, the quality of the GD&T design is still largely dependent on designer's previous experience, such as the experience in part design, machining, and measuring. Without more detailed guidance, engineering novices are likely to make a variety of common mistakes while they use the datum-based model. To address this issue, the authors collected and analyzed the typical errors from the previous GD&T designs and set up a specification that instructs the GD&T designer what should be and should not be done in each layer of the datum-based model. This rule-based GD&T design specification was piloted in 2021. The result shows that the quality of the GD&T design has been considerably improved. The ruled-based specification introduced in this paper does not only help produce high-quality designs, which are required by front-end research, such as autonomous machining, but also signifies a step forward in achieving the full automation of the GD&T process.

Tests of Glass Insulating Panels with Embedded Laminated Point Connections

Embedded laminated point connections represent a progressive way of glass structures connecting. However, detail information about their performance is not available yet and the design procedure is mostly based on experimental work and previous experience of designers. Within an ongoing research at the Faculty of Civil Engineering of the Czech Technical University in Prague, a set of real-scale insulating glass panels with embedded laminated point connections was tested. The goal of the experiment was to determine the load bearing capacity and characteristics of this type of glass panel under short-term and long-term loads. There were three different types of panels used for the experiment. The specimens consisted of different combinations of glass plies (ESG, TVG) and plies of different thicknesses. However, all the specimens were identically sized and there was one embedded steel countersunk bolt liners in each panel’s corner. The laminated glass plies were bonded by two layers of an EVA foil in all cases. During the experiment, all the samples were placed horizontally using the embedded point connections. The applied load was gradually increasing until the collapse. Vertical deflections in specific points of the samples were measured. The temperature and the humidity were monitored as well.

ЕКОЛОГІЧНІСТЬ ЯК СВІТОВИЙ ТРЕНД: НАПРЯМИ ТА ПЕРСПЕКТИВИ В ДИЗАЙНІ ОДЯГУ

The study is devoted to the analysis of theoretical aspects of ecological design, the study of methods of secondary use of materials and things in the fashion industry, the analysis of the practical experience of designers and specialists in the textile industry regarding innovations in ecological directions. It was determined that the priority directions of the modern fashion industry are the search for ways to solve global environmental problems, the preservation of natural resources, the harmonious comparison of fashion trends and ecological approaches to their implementation. The relevance of this study is explained by the aggravation of environmental problems at this stage of the development of society, the increased attention of designers to ecological design practices in the fashion industry and, in connection with this, the need to find sustainable solutions and methods of creating an ecological design product. An analysis of the categories "upcycling" and "recycling" was performed, the features of the global trend of abandoning natural fur and leather and the production of alternative materials for the creation of clothes, shoes and accessories were determined. The latest practices of famous Ukrainian and foreign designers and their approaches and methods of secondary use of textiles and things are considered. The foreign experience of creating alternative materials from such natural raw materials as coconut and hemp fiber, winemaking waste, orange peel, marine plants, as well as the results of secondary processing of plastic to obtain a new form of textile was analyzed. Conclusions were made regarding the need for future designers to focus their efforts on cyclical design processes in the fashion industry, on the condition of finding ways to access the latest materials, introducing their own technologies for their creation in Ukraine, to overcome the contradiction between the high cost of the latest ecological materials and the urgent need to switch to their use.

A compliance modeling method of flexible rotary joint for collaborative robot using passive network synthesis theory

Collaborative robots have become a research focus because of their wide applications. However, the previous compliance design method of the flexible rotary joint for collaborative robot mainly relied on experience of designers, and “trial and error” method is usually adopted, no feasible and systematic theory for the designer to select numerical value and series-parallel connection mode of the springs and dampers for the flexible rotary joint. Thus, developing a feasible compliance modeling theory to guide the design of the flexible rotary joint is a particularly challenging task. The main contribution of this paper is to present a novel and effective compliance modeling theory of the flexible rotary joint for collaborative robot based on electrical and mechanical passive network synthesis, to provide theoretical and systematic guidances for compliance design of the flexible rotary joint. First, inerter element is introduced into the mechanical system, and the compliance of the flexible rotary joint is expressed as an angular velocity admittance function using electrical and mechanical network analogy. Then, by passive network synthesis theory, the three kinds of compliance realization forms of rational function and four-element compliance realization conditions of biquadratic function for the flexible rotary joint are given using inerters, springs, and dampers. Moreover, numerical examples and simulations are conducted to illustrate effectiveness of the proposed compliance realization method. Finally, discussions are given to illustrate advantages of the proposed compliance modeling and design methods compared with the previous method.

The Material Film Costume: Encountering the Mink Dress of Lady in the Dark (Leisen, 1944)

Over the last three decades, the study of film costume design has become a burgeoning field that predominantly engaged with the cinematic costume and its relationship with the female spectator. As film scholars have seldom looked at or worked with the actual garments, little to no academic attention is spent on the knowledge, experience, and invisible work of the costume designers and executers working in this field. This article implements the research methodology of material culture analysis, established in the field of fashion studies, but neglected in the area of film costume design studies. By stepping into the physical world of costume objects, the material culture analysis allows us to look beyond film costumes as kinetic, immaterial film images, and enables us to elucidate the histories and esthetics of garments that were created for specific film performances. Through an archival encounter with an extant costume object, an understanding of the creative and collaborative work conducted in the wardrobe department is facilitated. The central case of this paper is the mink dress of Lady in the Dark, a lavish musical drama set in the fashion industry, and directed by Mitchell Leisen, who started his career as a costume designer.

Structural form-finding of bending components in buildings by using parametric tools and principal stress lines

This paper aims to provide an efficient and straightforward structural form-finding method for designers to extrapolate component forms during the conceptual stage. The core idea is to optimize the classical method of structural form-finding based on principal stress lines by using parametric tools. The traditional operating process of this method relies excessively on the designer's engineering experience and lacks precision. Meanwhile, the current optimization work for this method is overly complicated for architects, and limitations in component type and final result exist. Therefore, to facilitate an architect's conceptual work, the optimization metrics of the method in this paper are set as simplicity, practicality, freedom, and rapid feedback. For that reason, this paper optimizes the method from three aspects: modeling strategy for continuum structures, classification processing of data by using the k-nearest neighbor algorithm, and topological form-finding process based on stress lines. Eventually, it allows architects to create structural texture with formal aesthetics and modify it in real time on the basis of structural analysis results. This paper also explores a comprehensive application strategy with internal force analysis diagramming to form-finding. The finite element analysis tool Karamba3D verifies the structural performance of the form-finding method. The performance is compared with that of the conventional form, and the comparison results show the practicality and potential of the strategy in this paper.

Classification and Inverse Design of Metasurface Absorber in Visible Band

AbstractMetasurface absorber (MA) has been a research hotspot in the field of artificial electromagnetic structural material due to its dual advantages of high performance and compact design. Usually, the design of MA depends on the designer's professional knowledge, experience and physical inspiration. The desired optical response can be obtained by using electromagnetic simulation software to carry out hundreds or thousands of numerical calculations. Thus, it is still a challenge to quickly retrieve the optimal structure according to the desired optical response and realize the on‐demand inverse design. Besides, limited by the inner physics of the MA, it is not always possible to find the structural parameters corresponding to the desired spectrum. This paper not only takes the planar geometry and thickness of the structures into account but also realizes the probability classification of the desired spectra through the classification network. According to the classification results, the prediction network of the corresponding is selected to realize the on‐demand inverse design of MA. The proposed network model can design MA rapidly and accurately in a data‐driven way and can be flexibly applied to the design of other data‐enabled photonic devices, which is promising to become a comprehensive and effective design tool.

Analysis of basic concepts of advanced engines for supersonic civil aircraft on the basis of foreign designers’ experience

The work contains the results of a study of the basic design concepts of advanced engines for supersonic civil aircraft, carried out in order to make a forecast for the development of aviation technology, taking into account the experience of foreign designers. Engine designs are presented that are considered to be the most rational ones from the point of view of achieving high technical and economic parameters in the range of cruise Mach numbers from 1.2 to 5. Advantages and disadvantages of various engine designs, as well as issues of engine regulation at different flight modes, are discussed. The parameters of some engines being developed and studied at present for supersonic civil aircraft are presented. The analysis of the designs shows that an increase in the cruise Mach number leads to a complication of engine designs in the direction of an increase in the number of controlled elements, the number of working fluid flow paths, a complication of the architecture of turbomachines, as well as in the direction of using combined schemes and alternative fuels. The aspiration to meet new reinforced ecological requirements through the use of new, complex engine designs that differ significantly from traditional gas turbine engines will inevitably entail additional technical risks due to the insufficient level of technological readiness of most of the new controlled units.

Children’s Clothing Virtual Simulation Immersive Design and Show Based on Machine Learning

In view of the inconvenient display of children’s clothing, the poor experience of designers when modifying sample clothes, and the immature display of children’s clothing, which affects the rational judgment of fashion buyers, this paper puts forward the modular design method of children’s clothing virtual fitting. This research uses Lectra CAD software to make children’s clothing pattern, Clo3D for virtual modular design, and “Insanda children’s clothing virtual design and show” for virtual try-on and show. The simulation results show that the research can effectively improve the efficiency of designers and buyers, can save costs, and can be effectively applied in the commercial field. At the same time, it provides a practical basis for the development of children’s clothing virtual display technology and the formulation of standards related to children’s clothing in the future.

Layout Design and Die Casting Using CAE Simulation for Household Appliances

Due to the development and industrialization of science and technology, aluminum alloys have been developed in various fields. Recently, the government has been pursuing ways to decrease the weight and increase the recyclability of various components in order to conserve resources, energy, and the environmental. In keeping with this trend, cast iron products are being replaced by aluminum products in the foundry industry by using high-pressure die casting (HPDC). Casting layout design, relies on the experience and knowledge of mold designers in the casting industry, which proves insufficient to respond to the rapidly changing needs of the era and to increasing production costs. Designing and producing casting layouts using CAD/CAM/CAE technology has become a critical issue. Computer-Aided Engineering (CAE) technology is rapidly increasing with the development of computer software and hardware. CAE technology not only predicts defects in mass production but also performs filling or solidification analysis during the mold design stage before production, enabling optimal mold design methods. New technologies that combine the emerging casting processes of filling and solidification analysis using computer simulation with existing technology and practical experience in the field are rapidly increasing in the foundry industry. Based on empirical knowledge, the layout and design of casting products has traditionally progressed through trial and error. The solutions achieved through scientific calculation and analysis using CAE technology can save a great deal of money and time in the building of die-casting molds and in their design and fabrication. In this study, numerical analysis of household appliances (cooking grills) quickly and accurately predicts problems arising from the filling and solidification of the melted metal in the casting process, thereby ensuring the quality of the final cast product. These results can be used to quickly establish a sound casting layout with reduced production costs.

Controllable inverse design of auxetic metamaterials using deep learning

As typical mechanical metamaterials with negative Poisson’s ratios, auxetic metamaterials exhibit counterintuitive auxetic behaviors that are highly dependent on their geometric arrangements. The realization of the geometric arrangement required to achieve a negative Poisson’s ratio relies considerably on the experience of designers and trial-and-error approaches. This report proposes an inverse design method for auxetic metamaterials using deep learning, in which a batch of auxetic metamaterials with a user-defined Poisson’s ratio and Young’s modulus can be generated by a conditional generative adversarial network without prior knowledge. The network was trained based on supervised learning using a large number of geometrical patterns generated by Voronoi tessellation. The performance of the network was demonstrated by verifying the mechanical properties of the generated patterns using finite element method simulations and uniaxial compression tests. The successful realization of user-desired properties can potentially accelerate the inverse design and development of mechanical metamaterials.

About the optimization in calculations of internal cold and hot water supply systems

Regulatory literature, namely the DBN "Domestic Water Supply and Sewerage" does not offer an algorithm for obtaining the optimal diameters on all, without exception, the calculated sections of internal networks of cold and hot water supply. In general, it is not proposed to consider the entire network as a single object. It indicates only the maximum velocities of water in the calculated sections, which depend on the material of the pipe, and states that it is necessary "to maximally use the guaranteed head in the city network. These are two mutually exclusive recommendations. When one is implemented, it is impossible to implement the other and vice versa. It is proposed to completely formalize the calculations of internal networks from finding diameters on individual design sections of the internal network of cold or hot water supply. Optimization is performed simultaneously for all sections of the network without exception. For calculations, to find the best network variant, it is suggested to use two parameters: quantity and quality. As it is generally known, only simultaneous fulfillment of these two parameters enables the water supply network to be reliable. The quality of water depends on the time in which it reaches the consumer. The longer the time, the worse the quality of water. This applies to both cold and hot water. The quantity of water depends on the pressure. The greater the head, the higher the speed of movement and accordingly the higher the flow of water, but there is a disadvantage - the higher the head loss on the way to the consumer and the higher the fee for the service. The search for optimality, so that it was both fast and the head loss is minimal and gives the best option for the network. When using the methodology, neither the designer's experience in solving such problems, nor his general professional level has any influence on the result. This, in turn, makes it possible to quickly solve problems of finding the best option in a short time, as well as to further reduce the time when calculating the network to make the software and in this case the professional level of the designer in general will not have any bearing on the quality of calculations.