Dynamic Layout Research Articles

Deep Dynamic Layout Optimization of Photogrammetry Camera Position Based on Digital Twin

Deep Dynamic Layout Optimization of Photogrammetry Camera Position Based on Digital Twin

Dynamic content layout optimization for news website front pages

Purpose The home page design of a digital news website is a key factor in determining its attractiveness to readers. This study aims to propose an approach to manage the frequent adjustment of the dynamic layout of the news content on the website home page in a real-time environment to increase its attractiveness to readers. Design/methodology/approach This paper shows that this news website layout design problem can be modeled as an optimization problem based on the information of news contents that change within a multiple-period planning horizon similar to the dynamic facility layout problem. A hybrid genetic algorithm-based approach integrated with local search heuristic methods is also proposed to improve the solution. Findings This paper finds that the DPLP model is effective in modeling the changing layout of a digital news website. The problem can solved in a timely manner using the proposed hybrid genetic algorithm. Research limitations/implications This paper was based on hypothetical data and on the assumption of equal section size. Actual data would help fine-tune the application of the dynamic facility layout model. As well the algorithm could be enhanced for unequal size sections. Practical implications The model should help online newspapers apply sophisticated algorithms to optimize the layout of news websites dynamically in a timely manner. Social implications News websites are increasingly the desired medium to consume news. So it has an important role in educating society. Thus optimizing and improving the process will help in this regard. Originality/value To the best of the authors’ knowledge, this paper is the first one to apply the DPLP model to the digital newspaper website dynamic design problem.

Cognitive task analysis-driven intelligent steering wheel interaction design

With the increasing levels of intelligence and automation, the relationship between humans and vehicles has evolved from a utilitarian perspective to a partnership. Among the crucial factors for enhancing user experiences are the analysis of driving tasks, the construction of user needs models, and the design of intelligent interfaces. Based on this background, this paper proposes a cognitive task analysis model using intelligent steering wheel information interaction design as the vehicle. The model aims to extract key design elements to assist designers in making design decisions, thereby improving the human-machine cooperation performance of intelligent automobiles and enhancing user perceptual experiences. Firstly, within the context of human-machine cooperation systems, a cognitive task analysis method integrating the SRK model is proposed. By analyzing the behavioral decision characteristics between the vehicle and the user, a framework for the human-machine interface (HMI) logic of the steering wheel and a dynamic layout prototype are established. Secondly, the design of the steering wheel’s HMI interaction is based on an analysis of users’ affective needs and rational physiological characteristics. This paper integrates the analysis of users’ affective needs to identify design elements that align with a high level of user satisfaction. Lastly, the design methodology model is applied to a navigation scenario, resulting in the creation of a steering wheel HMI prototype within a human-machine cooperation system. The prototype is then subjected to a combined subjective and objective experimental analysis, thereby validating the superiority of the steering wheel HMI’s detection indicators over those of the central control HMI and establishing the design pattern for the steering wheel HMI.

Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin

AbstractTo meet the requirement of product variety and short production cycle, reconfigurable manufacturing system is considered as an effective solution in addressing current challenges, such as increasing customisation, high flexibility and dynamic market demand. Dynamic factory layout design and optimisation are the crucial factors in response to rapid change in the mechanical structure, software and hardware integration, as well as production capability and functionality adjustment. Nevertheless, in the current research, the layout design for reconfigurable manufacturing systems is usually simplified with autonomous devices being regarded as 2D shapes. Issues such as overlapping and transportation distance are also addressed in an approximate form. In this paper, we present a novel multi-agent cooperative swarm learning framework for dynamic layout optimisation of reconfigurable robotic assembly cells. Based on its digital twin established in the proposed learning environment (constructed in Visual Components and controlled by TWINCAT), the optimisation framework uses 3D digital representation of the facility models with minimal approximation. Moreover, instead of using a traditional centralised learning manner, multi-agent system could provide an alternative way to address the layout issues combined with the proposed decentralised multi-agent cooperative swarm learning. In order to verify the application feasibility of the learning framework, two aerospace manufacturing use cases were implemented. In the first use case, the layout compactness is reduced by 3.8 times compared with the initial layout setting, the simulated production time is reduced by 2.3 times, and the rearrangement cost decreased by 33.4$$\%$$ % . In addition, all manufacturing activity within the cell can be achieved with a feasible robot path, meaning without any joint limits, reachability or singularity issue at each key assembly point. In the second use case, we demonstrated that with the proposed dynamic layout optimisation framework, it is possible to flexibly adjust learning objectives by selecting various weight parameters among layout compactness, rearrangement cost and production time.

Generative Shopfloor Layout Design: Challenges and Proposed Modelling Approach

This paper explores the transformative impact of generative design principles on layout design and organization. The paper provides insights into the practical use of generative design in layout environments, emphasizing the optimization of spatial arrangements, workflow efficiency, and human-machine collaboration. The paper presents a novel generative approach proposed for optimizing manufacturing shop floor layouts, utilizing a three-stage process that integrates Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs). The first stage focuses on exploration and learning using VAE to generate a diverse pool of solutions, guided by a fitness profile encompassing characteristics such as travel distance, adjacency score, space utilization, ergonomic score, and aesthetics. The second stage employs GANs for intensive layout improvements, introducing a competitive training process where the generator aims to produce layouts surpassing the quality of previous iterations. The third stage fine-tunes the best layouts identified by the GAN.A much more detailed model is required, and a VAE with higher resolution than the one used in the first phase. The manuscript presents a comprehensive methodology, paving the way for future research into dynamic layout adaptation in manufacturing settings.

Research on rural landscape garden planning and plantscape construction method based on digital twin technology under rural revitalization strategy

Abstract This paper integrates the landscape information model, designs the digital twin rural landscape architecture, and analyzes the advantages of the digital twin rural landscape model. The practical application of digital twin technology is examined from the planning and design stage to the construction stage. Considering the actual construction site layout and the consumption of construction materials, the NSGA-II algorithm is selected to optimize the dynamic layout of temporary facilities by combining multi-objective optimization theory. Using the digital twin to drive the dynamic layout of the construction site, a digital twin-driven construction site layout mechanism is proposed in combination with BIM technology. The actual construction scheduling tasks are used to analyze the feasibility of the construction site layout scheme generated using digital twin technology. Analyze the construction of rural landscape gardens planned using digital twin technology in terms of ecological, social, and economic benefits. The convergence minimum is achieved at 0.15 and 0.09 when comparing the number of iterations between the initialized layout and the digital twin-driven layout. The corresponding scheme reaches its optimal state during the construction stage and can provide the most suitable site arrangement scheme during that stage. The rural landscape garden planned by the digital twin technology can generate an economic return value of 71.756 yuan/m² per year, which can further promote rural revitalization.

COMPAD: A heterogeneous cache-scratchpad CPU architecture with data layout compaction for embedded loop-dominated applications

The growing trend of pervasive computing has consolidated the everlasting need for power efficient devices. The conventional cache subsystem of general-purpose CPUs, while being able to adapt to many use cases, suffers from energy inefficiencies in some scenarios. It is well-known by now in the academic literature that the utilization of a scratchpad memory (SPM) can help reducing the overall energy consumption of embedded systems. This work proposes a hybrid cache-SPM architecture with support logic for semi-transparent data management and spatial locality improvement. Selected data are transferred and stored in the SPM in a compact form using dynamic layout transformation. As a second major contribution, we introduce a methodology to identify memory access sequences that make an inefficient use of the cache, marking them as candidates to be moved to an SPM of constrained space. The methodology does not require access to the source code of the target applications, relying on binary instrumentation and offline profiling. The resulting mapping policies have been tested on a simulated system, showing a mean memory dynamic energy reduction of 43% and a mean speed gain of 13% with a representative benchmark set.

Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction

ABSTRACT Photogrammetry systems are widely used in industrial manufacturing applications as an assistance measurement tool. Not only does it provide high-precision feedback for assembly process inspection and product quality assessment, but also it can improve the flexibility and robustness of manufacturing systems and production lines. However, with growing global competition and demands, companies are forced to enhance production efficiency, shorten production lifecycle and increase product variety by incorporating reconfigurable factory design that can meet challenging timeline and requirements. Although dynamic facility layout is widely investigated, the position selection for the photogrammetry system in dynamic manufacturing environment is usually overlooked. In this paper, dynamic layout of the V-STARS photogrammetry system is investigated and optimised in a digital-twin environment using deep reinforcement learning. The learning objectives are derived from the field of view (FoV) evaluation from point clouds 3D reconstruction, and collision detection from the digital twin simulated in Visual Components. The application feasibility of the proposed dynamic layout optimisation of the V-STARS photogrammetry system is verified with a real world industrial application.

Grid-scale crop dynamic layout optimization model considering stakeholders' cropping preferences and practice behaviours

Rapid population growth has led to an increasing demand for food, accompanied by an increase in the resources invested in producing food, and the extensive food production practices have placed a huge burden on the environment. There is an urgent desire of need to find a sustainable model of food production. Therefore, this study attempted to develop a dynamic regional grid-scale crop layout model (ABCAMODP-Crop) combining agent-based model, multi-objective programming, dynamic programming and cellular automata model to promote more sustainable food production from a supply-side perspective. The model can: (1) take into account the planting preferences and practical behaviours of government and farmer as stakeholders in crop layout; (2) further weigh the conflicts among the various objectives that stakeholders are concerned with from resource, environmental, nutritional and economic dimensions; (3) consider the impact of the previous year's crop layout on the next year's crop placement; and (4) obtain grid-scale accurate crop layout solutions by considering the spatial variability of optimization parameters and the neighborhood effects of crop layout cells. The model was applied to the Shiyang River Basin in China to verify its usefulness. Over the entire planning period, crop layout schemes optimized with the objective of integrating irrigation water productivity, environmental impact, nutrient availability and economic benefits have higher comprehensive benefits than the original scheme, with an increase in average irrigation water productivity per unit area of 14.55%, an increase in total yield of 14.45%, an increase in total carbohydrate availability of 7.39%, an increase in total calcium availability of 18.74%, an increase in total net carbon sequestration of 8.05%, an increase in total net benefit of 20.08%. The model developed allows for a holistic view of crop layout and guides decision-makers in a rational distribution of regional crops, thus promoting more sustainable food production. It can equally be extended to other regions as a generic modelling framework.

Variations in the Spatial Distribution of Smart Parcel Lockers in the Central Metropolitan Region of Tianjin, China: A Comparative Analysis before and after COVID-19

The COVID-19 pandemic has led to a significant increase in e-commerce, which has prompted residents to shift their purchasing habits from offline to online. As a result, Smart Parcel Lockers (SPLs) have emerged as an accessible end-to-end delivery service that fits into the pandemic strategy of maintaining social distance and no-contact protocols. Although numerous studies have examined SPLs from various perspectives, few have analyzed their spatial distribution from an urban planning perspective, which could enhance the development of other disciplines in this field. To address this gap, we investigate the distribution of SPLs in Tianjin’s central urban area before and after the pandemic (i.e., 2019 and 2022) using kernel density estimation, average nearest neighbor analysis, standard deviation elliptic, and geographical detector. Our results show that, in three years, the number of SPLs has increased from 51 to 479, and a majority were installed in residential communities (i.e., 92.2% in 2019, and 97.7% in 2022). We find that SPLs were distributed randomly before the pandemic, but after the pandemic, SPLs agglomerated and followed Tianjin’s development pattern. We identify eight influential factors on the spatial distribution of SPLs and discuss their individual and compound effects. Our discussion highlights potential spatial distribution analysis, such as dynamic layout planning, to improve the allocation of SPLs in city planning and city logistics.

GNN at the Edge: Cost-Efficient Graph Neural Network Processing Over Distributed Edge Servers

Edge intelligence has arisen as a promising computing paradigm for supporting miscellaneous smart applications that rely on machine learning techniques. While the community has extensively investigated multi-tier edge deployment for traditional deep learning models (e.g. CNNs, RNNs), the emerging Graph Neural Networks (GNNs) are still under exploration, presenting a stark disparity to its broad edge adoptions such as traffic flow forecasting and location-based social recommendation. To bridge this gap, this paper formally studies the cost optimization for distributed GNN processing over a multi-tier heterogeneous edge network. We build a comprehensive modeling framework that can capture a variety of different cost factors, based on which we formulate a cost-efficient graph layout optimization problem that is proved to be NP-hard. Instead of trivially applying traditional data placement wisdom, we theoretically reveal the structural property of quadratic submodularity implicated in GNN’s unique computing pattern, which motivates our design of an efficient iterative solution exploiting graph cuts. Rigorous analysis shows that it provides parameterized constant approximation ratio, guaranteed convergence, and exact feasibility. To tackle potential graph topological evolution in GNN processing, we further devise an incremental update strategy and an adaptive scheduling algorithm for lightweight dynamic layout optimization. Evaluations with real-world datasets and various GNN benchmarks demonstrate that our approach achieves superior performance over de facto baselines with more than 95.8% cost reduction in a fast convergence speed.

Dynamic Layout Optimization of Stiffeners in Plate Structures Based on Power Flow Response

By minimizing power flow response, a method of moving asymptotes was adopted to optimize the power flow model by adding and deleting corresponding elements and changing the material setting position in the configuration. To improve the dynamic performance of the whole structure under the premise of slightly increasing the mass of the whole structure, the Rayleigh damping model under the combined action of the environment and the characteristics of the material is established, and the SIMP (Solid Isotropic Material With Penalization) model of the coupling structure is used to calculate the power flow response of the plate-reinforced coupling structure, so that the vibration response of the structure is more accurate.By solving the sensitivity of power flow response, it is concluded that the essence of stiffened layout optimization is to optimize the position of coupling beam on the substrate. Through numerical example analysis, the optimal configuration and power flow response results under different boundary conditions, different shapes and different loading frequencies are compared, which is of great significance for the optimization design of stiffened plate structure layout.

Analyzing the Level of Detail of Construction Schedule for Enabling Site Logistics Planning (SLP) in the Building Information Modeling (BIM) Environment

As Building Information Modeling (BIM) becomes the predominant technology in the construction industry, contractors, amongst other activities, need to conduct Site Logistics Planning (SLP) in the BIM environment during different project phases. 4D BIM modelling is an important step towards developing BIM models ready for the construction execution phase. However, in developing such models, currently no standard exist which would guide contractors towards a thorough analyses of site logistics. Moreover, there is a scarcity of studies and research on level of detail of construction schedules, which makes SLP hard to implement in a BIM environment. We addressed this problem by employing a case-study method for understanding how 4D BIM models should be designed to enable effective SLP and dynamic site layout creation. The results show that the following input data for SLP in the BIM environment is needed: hierarchically structured 3D BIM model, Work Breakdown Structure (WBS), detail schedule, resources constraints, and defined onsite temporary facilities. Additionally, we have found that the activities should be further divided into work operations to enable SLP. Our results enable contractors to create a dynamic site layout according to the BIM principles. Moreover, the findings are an initial step for the further standardization of the BIM model for the SLP in the BIM environment.

Grouping Maching using Genetic Algorithm for Dynamic Cell Layout Design

Changes in the manufacturing sector due to changes in shorter product life cycles, market demands and also use of the latest technology in the company, this will result in changes in process flow and also change the layout in the production section, causing dynamic layout problems. Dynamic layout problems can be solved by using a manufacturing cell formation method which has a high degree of flexibility. In this study, algorithms used for grouping machines into manufacturing cells are Direct Clustering Algorithm and Rank Order Clustering. Then it will be improved by using Genetic Algorithm. The Dynamic Modified Spanning Tree Algorithm is also used to sort machines into a layout with a single-row structure and determine the length of the planning time window in the future. The goals of this research is to get the best solution from the two methods of grouping machines/parts into manufacturing cells and to obtain improvement results using Genetic Algorithms. For the design industry, the resulting dynamic cell layout is expected to reduce production costs, save material handling, be efficient in material flow, which in turn will be able to compete globally.

Dynamic Layout Design Optimization to Improve Patient Flow in Outpatient Clinics Using Genetic Algorithms

Evolutionary algorithms, such as genetic algorithms have been used in various optimization problems. In this paper, we propose to apply this algorithm to obtain the layout design/redesign in order to improve the patient flow in an outpatient clinic. Layout designs are planned considering long-term requirements whereas the layout keeps modifying as per short-term demands. Over a period of time, the layout often does not remain efficient. Therefore, there is a need for such a model that helps in decision making on layout redesigns, and it must also optimize workflow by incorporating the flow constraints. In this study, we propose to minimize the waiting times by obtaining optimal and sub-optimal layout designs. A genetic algorithm is implemented to redesign the layouts based on the changing dynamics of patient demand, clinical pathways and services offered. The workflow is simulated with current layout and optimized layouts, and the results in terms of waiting time and cycle time are compared. The study shows that when layout design or redesign incorporate the workflow and pathways along with associated constraints, improves waiting time and cycle time of patients in the outpatient clinic. The distance between the departments/locations is translated to travelling time and overall travel distance/time is minimized by rearranging the allocations of departments to the location through genetic algorithms.

Comparative analysis of static and dynamic facility layouts design using the modeling of plantain flour as case study

AbstractProfit optimization at the expense of minimal resource utilization for product development has been the major focus of prospective investors. In an attempt to realize this goal, the present research consideration is tailored towards investigating the effect of introducing dynamic facility layout design. Therefore, this research study uses an existing designed plantain flour processing plant that consists of a washing machine, grating machine, dryer, milling machine and sieving machine. Modeling techniques incorporated with software development were employed on the existing static plant layout to optimize production time and cost of each of the processing units along with the layout. Also, dynamic constraints were introduced into the layouts while mathematical models were formulated to visualize how the output and production process would be. With these models, software for the optimization of static and dynamic layouts was developed. The comparative study was carried out based on the processing time, the number of machines needed for each layout type, the cost of operation and machine procurement cost for both static and dynamic layouts. The constraints introduced ensured that the system improved within the cost limit based on the current market situation and prevented unnecessary enlargement in the plant facility size while minimizing material congestion in the system. The distinction between static and dynamic layout configurations was further established by comparing the results from the layout configurations for a set of throughput masses ranging from 50 kg to 250 kg. Results showed that the cost of operation drops drastically by 69.6 % under dynamic layout configuration.

Dynamic Simulation and Conceptual Layout Study on a Quad-Plane in VTOL Mode in Wind Disturbance Environment

Quadrotor fixed-wing hybrid vertical take-off and landing (VTOL) UAV, the so-called Quad-Plane, is susceptible to wind disturbance during the VTOL mode, which reduces its stability and limits its application. In order to dynamically analyze its response characteristics to wind disturbance and effectively optimize the wind disturbance rejection performance in VTOL mode, a dynamic flight simulation system based on the 6-DoF equations is established, in which the aerodynamic model of the Quad-Plane is established based on the wind tunnel test, the axial and lateral forces and moments of the rotor in wind disturbance are obtained through CFD simulation, and the Brushless DC (BLDC) motor, wind disturbance, and flight controller are modeled based on actual characteristics. The simulation system is verified and validated by comparing the simulation results with test results of a 5 kg real Quad-Plane. Using this system, the response characteristics of the Quad-Plane to the discrete and continuous wind disturbance are studied. In addition, the influences of major conceptual layout parameters that affect the wind disturbance rejection performance, such as take-off weight, weight distribution, Center of Gravity (CG) position, rotor incline angle, arm length, and arm angle, are studied. Finally, the approaches on designing a Quad-Plane with better wind disturbance rejection performance during the conceptual layout design are presented.

Multistage and Dynamic Layout Optimization for Electric Vehicle Charging Stations Based on the Behavior Analysis of Travelers

Electric vehicles (EV) are growing fast in recent years with the widespread concern about carbon neutrality. The development of charging infrastructures needs to be in phase with EV both in terms of quantity and charging time to decrease the range anxiety of EV users and resource waste. This paper proposed a multistage and dynamic layout optimization model based on mixed integer linear programming (MILP) for EV charging stations (CSs) to minimize the total social costs (TSC) consisting of the detour cost of EV users and the construction, relocation, and operating cost of CSs. The charging satisfaction coefficient and M/M/S/K model of queuing theory has been introduced to determine the desirable charging supply. The spatial-temporal distribution of charging demand was modeled based on the behavior analysis of travelers and over the discrete-time intervals for a day. Comparison studies based on the Sioux Falls network reveal that TSC with a multistage optimization strategy will drop 8.79% from that with a one-time optimization strategy. Charging service quality, relocation cost, and road network scales have a significant impact on the optimization results according to the sensitivity analysis.

THE USE OF ANALYTICAL TOOLS IN RESHAPING THE SHOPPING EXPERIENCE OF THE FUTURE

Purpose: The goal of the research was to discover the key metrics needed to shape next-generation retailing in India using predictive analytics. Design/Research Methodology/approach: The aims of the research study were investigated using factor analysis. Findings: The article emphasises the importance of merchants adopting a new approach to keep their customers for extended periods of time. Providing customers with a product or service has become almost a commodity. In order to fully satisfy their customers, retailers are expected to step up their game in the ever-growing retail market. Research Implications: In order to fully satisfy their customers, retailers are expected to step raise their efforts in the ever-growing retail market. Scope for future work / Research limitations: Consumer transformation has indeed begun to have a significant impact on the future of retailing in India. As a result, retailers must adopt a strategy to understand what their customers want from them in relation to their product or service, and delicate their processes more effectively. Originality/value: The majority of research on predictive analytics or big data analytics has focused on the value of their application in the retail business. As a result, the focus of this research is to investigate the core aspects identified with the help of predictive analytics that the retail business must embrace in order to thrive during times of dynamic layout. Keywords: Retailing, span of time, retailers, shopping pattern Paper Type: Research Paper

Inverse Markov Process Based Constrained Dynamic Graph Layout

Inverse Markov Process Based Constrained Dynamic Graph Layout