Entire Design Research Articles

Product innovation design process combined Kano and TRIZ with AD: Case study.

In the era of rapid product iteration, companies need simple and effective methods to guide the entire process of product innovation design and enhance their product innovation capabilities. Most research focused on improving one or several steps in the product design process. Although some scholars have proposed methods that guided the entire process, they combined more than three different theories, which increased the difficulty of theoretical learning and the complexity of practical implementation. This paper proposed a product innovation design process composed of three theoretical methods: Kano, Axiomatic Design (AD), and Theory of the Solution of Inventive Problems (TRIZ). This new process guided the entire product design process with fewer theoretical methods, reducing the difficulty of learning and implementation. The paper demonstrated the effectiveness of this method through the design practice of a portable two-wheeled self-balancing vehicle. Additionally, the discussion section explored the method's potential from the design management perspective.

Fast finite-time control for a class of stochastic low-order nonlinear system with uncertainties

This work explores the challenge of adaptive fast finite-time control for stochastic low-order nonlinear systems with uncertainties. It introduces an improved practical finite-time criterion that aims to achieve accelerated convergence. The criterion aims to extend to a larger range of stochastic nonlinear systems, accommodating state uncertainties and integrating Lyapunov functions with varying powers to ensure rapid convergence in the presence of uncertainties. The entire control design approach is based on the backstepping method. Specifically, fuzzy logic systems are employed in the recursive design of controllers and adaptive laws to address complex uncertain terms. Additionally, the desired magnitude target powers of the Lyapunov function in the criterion are effectively obtained by a clever overlapping selection of parameters. Finally, this study demonstrates the practical finite-time stability of stochastic low-order uncertain nonlinear systems and validates the effectiveness of the proposed approach through simulation example, highlighting its ability to achieve fast convergence.

A Novel Piezoelectric Energy Harvester for Earcanal Dynamic Motion Exploitation Using a Bistable Resonator Cycled by Coupled Hydraulic Valves Made of Collapsed Flexible Tubes.

Scavenging energy from the earcanal's dynamic motion during jaw movements may be a practical way to enhance the battery autonomy of hearing aids. The main challenge is optimizing the amount of energy extracted while working with soft human tissues and the earcanal's restricted volume. This paper proposes a new energy harvester concept: a liquid-filled earplug which transfers energy outside the earcanal to a generator. The latter is composed of a hydraulic amplifier, two hydraulic cylinders that actuate a bistable resonator to raise the source frequency while driving an amplified piezoelectric transducer to generate electricity. The cycling of the resonator is achieved using two innovative flexible hydraulic valves based on the buckling of flexible tubes. A multiphysics-coupled model is established to determine the system operation requirements and to evaluate its theoretical performances. This model exhibits a theoretical energy conversion efficiency of 85%. The electromechanical performance of the resonator coupled to the piezoelectric transducer and the hydraulic behavior of the valves are experimentally investigated. The global model was updated using the experimental data to improve its predictability toward further optimization of the design. Moreover, the energy losses are identified to enhance the entire proposed design and improve the experimental energy conversion efficiency to 26%.

An In-Depth Comparison of Straight and Wavy Microchannel Heat Exchangers

Abstract This paper presents extensive fluid flow and Heat-Transfer studies conducted using a commercial computational fluid dynamics (CFD) package known as CFD-ACE® to elaborate and expand on the reference studies available for ceramic-compact counterflow microchannel heat exchangers (MCHEs). The computational 3D model was developed using an experimentally tested MCHE and validated with experimental data with 3–5% variation for hot fluid and 6–12% variation for cold fluid for the entire design of experiments (DoEs). This study aimed to identify the performance of novel microchannel shapes using numerical analysis. The MCHE has good heat exchange properties, a compact design at industrial throughput, and a lower inner volume. During the study and identification of novel channel shapes, the segmented wavy MCHE was evaluated. The results were compared with those of the same volume and area straight MCHE baseline design under various identical operating conditions. Although the performance in terms of effectiveness is increased up to ∼12–25% in wavy MCHE with respect to straight MCHE simultaneously, the pressure drop is also increased by ∼60–80% under the same operating conditions. Therefore, performance and trade-offs are required to make the correct decision regarding feasibility. The effectiveness of the heat-transfer enhancement was also evaluated by plotting the heat-transfer coefficient ratio with respect to the pressure ratio of the two designs under identical operating conditions. This numerical study clearly indicates that wavy channels are better from the thermal performance point of view, whereas straight channels are better from the pumping power point of view, and the quantitative values are presented in graphical form.

Global design methodology for semi-submersible hulls of floating wind turbines

Designing the support structures for floating wind turbines (FWTs) involves a step-by-step process, typically in three phases, i.e., starting from concept selection and determining the overall dimensions for a given configuration, and finally, determining the detailed specifications. The global design of the hull is used to select the floater concept and determine the global dimensions for the subsequent detailed design. This global design process is a crucial part of the entire design cycle because it has a significant impact on the detailed design, which can be computationally expensive. However, because FWTs are still in the infancy stage of development, there is a lack of effective methods and procedures for determining the global dimensions of floaters. Additionally, the global response characteristics of different hull layouts are not yet well understood. To address these limitations, this paper deals with a global design of semi-submersible floaters to support large-scale wind turbines (using a 10-MW turbine as an example). The paper proposes and describes a methodology and procedures for the global design in detail, specifying criteria and values for a case study. Furthermore, a sensitivity study is conducted to determine the global dimensions of the floaters. Then, intact stability is studied to evaluate their safety in operation under wind loads. Subsequently, global aspects of structural design are analyzed based on wave-induced response amplitude operators (RAOs) of cross-sectional forces and moments, taking into account representative environmental conditions for an offshore site. These analyses provide a foundation for the subsequent detailed design. The results indicate that the spacing of the column centerline and the outer column radius are the most critical design variables for the global response of the semi-submersible hull. Moreover, increasing the outer column radius or freeboard can effectively enhance intact stability. In addition, the study highlights the importance of critical wave periods that cause splitting or prying force on the hull columns in the structural design. Finally, the main findings and conclusions are summarized. This study presents a simplified yet innovative methodology for the global design of mainstream semi-submersible hulls for FWTs. It addresses the lack of effective methods for determining global dimensions and provides valuable insights into the structural design considerations.

ARTIFICIAL INTELLIGENCE (AI): PRACTICES AND PROBLEMS EXPERIENCED BY INTERIOR DESIGNERS

The development of artificial intelligence (AI) has swept the globe. Tools of artificial intelligence are now readily available to everyone due to the advancement of new and more refined AI every day, and they carry the potential to fundamentally alter the way one lives, works, and interacts with their surroundings. The interior design strategy based on artificial intelligence technology is being used to optimize the entire interior design work to increase technological innovation in space. Designers can input their preferences and design ideas into artificial intelligence systems for interior design and receive suggestions for furniture, colour palettes, and other design elements. These AI applications are helpful to optimize the work management of an interior designer as well as appease the clients. The main aim of the research study is to find out the practices and problems experienced by Interior designers regarding the applications of artificial intelligence in professionally managing and completing interior design projects. Data was collected from 80 respondents using a questionnaire through the purposive sampling method. The results of this investigation were valuable for Interior Design professionals, to get refined knowledge about the development of Artificial Intelligence tools used in professional management of Interior Design. Through this study various informative programmes can be conducted about the latest trends in Artificial Intelligence technology, its use and applicability.

Security Enabled New Term Weight Measure Technique with Data Driven for Next Generation Mobile Computing Networks

In the field of ASIC and FPGA, Machine Learning (ML) techniques play a major role and become predominant for accurate results for different applications like big data analysis and automotive electronics, and driverless vehicles which are required speed and power savings. Due to increasing the demand for higher accuracy, low power, low area consumption, and higher throughput for the complexity of the designs in the latest technology, the proposed system is fulfilling these demands in ASIC and FPGA domains, reconfigurable hardware architecture has been proposed it consists of an ML-based Support Vector Machine (SVM), high-speed AHB protocol and Floating point (FP) operations and also the system has the flexibility to communicate with I2C and I2S protocols. In order to increase throughput with minimal latency, the proposed architecture with AHB protocol and AHB to APB bridge is incorporated between the fabric dynamically reconfigurable multi-processor (FDPM) and peripherals along with security algorithms using SHA-256bits and AES. In order to perform ML-based applications, the proposed system is incorporated double-precision floating point (DPFP) arithmetic operations. The overall proposed architecture is developed in Verilog HDL and quality checking using the LINT tool and Clock Domain Crossing (CDC) using Spyglass tool and synthesized using DC compiler for ASIC and Vivado Design Suite 2018.1 for FPGA implementation and verification. The entire design is interfaced with the Zynq processor and SDK tool to verify data transfer between hardware and software. The obtained results show the generated custom accelerator is able to compute any complex ML classifiers for a larger amount of data. The obtained results are compared with existing state-of-art results and found that 18 % improvement in throughput, a 21 % improvement in power consumption savings, and a 34 % reduction in latency.

Education & Practice in Open Design. Improving the Learning Experience Through Knowledge Connections

Learning complex disciplines traditionally requires the adoption of equally articulated methods and strategies. Design does not escape this principle, on the contrary it enhances some of its peculiar characteristics: very different skills, often not aligned development and application times, tools complexity, declare an environment where methods and practice had always defined a non-linear educational scenario (Cennamo et al., 2011). The paper discusses the matter while bringing a case study specifically defined with the purpose to test a new educational scenario where a student is put into conditions to experiment the entire Design process by himself, being connected with different competences inside a complex multidisciplinary environment, in order to develop a physical Design solution for a user with disabilities.

Exploring FPGA Switch-Blocks without Explicitly Listing Connectivity Patterns

Increased lower metal resistance makes physical aspects of Field-Programmable Gate Array (FPGA) switch-blocks more relevant than before. The need to navigate a design space where each individual switch can have significant impact on the FPGA’s performance in turn makes automated switch-pattern exploration techniques increasingly appealing. However, most existing exploration techniques have a fundamental limitation—they use the CAD tools as a black box to evaluate the performance of explicitly listed switch-patterns. Given the time needed to route a modern circuit on a single architecture, the number of switch-patterns that can be explicitly tested quickly becomes negligible compared to the size of the design space. This article presents a technique that removes this fundamental limitation by making the entire design space visible to the router and letting it choose the switches to be added to the pattern, based on the requirements of the circuits being routed. The key to preventing the router from selecting arbitrary switches that would render the final pattern excessively large is to apply the same negotiation principle used by the router to remove congestion, just in the opposite direction, to make the signals reach a consensus on which switches are worthy of being included in the final switch-pattern.

Full-Custom 90 nm CNTFET Process Design Kit: Characterization, Modeling, and Implementation

As the semiconductor industry enters the post-Moore era, the carbon nanotube field-effect transistor (CNTFET) has become a powerful substitute for silicon-based transistors beyond 5 nm process nodes due to its high mobility, low power consumption, and ultra-thin-body electrical advantages. Carbon-based transistor technology has made significant progress in device manufacture and preparation, but carbon-based process design kits (PDKs) that meet the standards of commercial design tools are still an important bottleneck hindering the development of carbon-based integrated circuits. For the first time, a complete full-custom 90 nm CNTFET PDK is proposed in this paper, which includes Pcells for transistors, resistors, and capacitors; a compact model; DRC/LVS/PEX rules; and a standard cell and timing library. It can support the entire design flow of analog, digital, and mixed-signal carbon-based integrated circuits. To achieve an accurate compact model, the back-gate effect of CNTFETs and the influence of gate/drain voltage on transport probability are analyzed. Then the theoretical formulas for mobility and channel current are established. The comparison of the simulation and test results of CNTFET characteristics proves the accuracy of the compact model. Using this PDK, combined with standard IC design tools and design flow, the circuit and layout of an operational amplifier, SRAM, and 8-bit counter are completed. The simulation results verify the correctness and effectiveness of the PDK, laying a solid foundation for the large-scale industrialization of carbon-based integrated circuits.

A user-centred collective system design approach for Smart Product-Service Systems: A case study on fitness product design

Emerging technologies have significantly contributed to the evolution of traditional product-service systems (PSS) into smart PSS. This transformation demands a fresh perspective and a more inventive design approach. In response, this study proposes a new User-Centred Collective System Design (CSD) framework and process for Smart PSS design, aiming to enhance stakeholder engagement during the entire design process, thus promoting highly effective and creative design solutions. A case study, titled ‘Next-G Smart Fitness PSS Design’, was carried out to test and implement this approach, contrasting the results of the CSD method with a designer-centred method. The outcomes showed a marked improvement in product novelty and user desirability of the design outcomes when using the proposed design framework. The proposed CSD framework could offer beneficial insights and user-centric viewpoints for practitioners dealing with complex challenges linked to smart PSS design.

INCREASING THE LEVEL OF COMPETENCIES OF OSH MANAGERS TO ENSURE HIGHER SECURITY AND PROSPERITY OF BUSINESSES

The essence of the contribution is to present the results of the analysis of current trends in the Occupational Health and Safety (OSH) managers' competencies and to propose a competence framework for OSH managers for the study program Crisis Management at the Faculty of Security Engineering (FSE UNIZA). The proposed framework respects the legislative, normative, and managerial requirements imposed on this position, resulting from current practice in Slovakia and global trends. The authors created a framework with the requirements for basic professional knowledge and skills in the field of OSH. Managerial knowledge, skills, tasks, responsibilities for performing activities, and the entire OSH management process are described. The position of OSH manager should be moved toward strategic management. OSH manager should bear responsibility for the entire OSH management process, i.e., design, manage, and control processes associated with the OSH management process. Increasing the competence of health and safety managers will help companies minimize adverse impacts and increase prevention, safety, and company prosperity.

Data-driven two-dimensional integrated control for nonlinear batch processes

Two-dimensional control has been considered as an effective strategy to accomplish high-accuracy tracking for batch processes because of its excellent learning ability and time-domain stability. However, being a model-based control method, the performance of the two-dimensional control system will inevitably decrease due to unknown uncertainties or unmodeled dynamics. In addition, the high computational cost and complex design process of the control system severely limit its application in batch processes. For this reason, this paper proposes a new data-driven two-dimensional integrated control (DDTDIC) method for nonlinear batch processes. In the presented control scheme, the P-type iterative learning control (ILC) is adopted along the batch-axis to ensure the convergence of the system, and the proportional-integral-differential (PID) control is used in the time-axis to reject the influence of real-time disturbance. The parameters of the PID controller are obtained by utilizing the virtual reference feedback tuning (VRFT) method. The entire design process of the control system only requires the input and output (I/O) data of the batch processes and does not depend on any explicit model information. The simulation results show that compared with the ILC and the two-dimensional control, the presented control method not only has faster convergence speed and smaller tracking error, but also the computational efficiency is improved by more than 40% and 50% respectively.

Open-source design of integrated circuits

This paper presents the design of a self-clocked 12-bit non-binary fully differential SAR-ADC using the SKY130 open-source PDK. The entire mixed-signal circuit design and layout were created with free and open-source software. The ADC reaches a sample rate of up to 1.44 MS/s at 1.8 V supply while consuming 703 μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}W of power on a small 0.175 mm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${}^{2}$$\\end{document} area. A configurable decimation filter can increase the ADC resolution up to 16 bits while using an oversampling factor of 256. A 9‑bit thermometer-coded and 3‑bit binary-coded DAC matrix using a 448 aF waffle-capacitor results in a total capacitance of 1.83 pF per input. Realizations of configurable analog functions using the form factor of SKY130 high-density standard cells allow the parametrization of an analog circuit in a hardware description language and hardening of the macro in an intentionally digital workflow.

Analysis of Digital Transformation on Consumer Behavior for Shopping in Offline and Online Store (Case Study: UNIQLO Indonesia)

Uniqlo is one of the world’s largest Apparel Fashion firms. Uniqlo’s business strategy integrates the entire clothing-making process, from planning and design to production, distribution, and retail. Uniqlo expanded its retail operations in Indonesia on February 13, 2013, and presently has 65 stores in 25 cities throughout the country. Uniqlo Indonesia must face obstacles in this digital era shift; during the COVID-19 pandemic, the rate of business owners creating e-commerce stores and customers purchasing online surged rapidly. Uniqlo has the lowest online sales contribution rate among its competitors, with 16% Online Sales Contribution and 84% Offline Sales Contribution. Uniqlo aspires to boost its online sales contribution to 20%. This study offers a maximized omnichannel integration approach between Uniqlo Indonesia’s online store and Uniqlo Indonesia’s offline stores to achieve Uniqlo’s aim of becoming the number one global apparel company. This research includes an internal analysis that includes value chain analysis and resources analysis to evaluate Uniqlo Indonesia’s internal condition and determine strengths and weaknesses, an external analysis that includes general environment analysis, industry analysis, and competitor analysis to evaluate Uniqlo Indonesia’s external conditions and determine threats and opportunities, and a customer journey analysis that includes the five A’s. Following the analytical phase, TOWS Matrix, Business Model Canvas, and Value Proposition Canvas were produced to help improve the formulation of the solution for Uniqlo Indonesia. Uniqlo Indonesia should improve every touchpoint across all integrated channels in the customer journey using Uniqlo Indonesia resources to improve the omnichannel integration strategy. This research’s business strategy and solutions can be utilized by Uniqlo Indonesia to boost customer awareness, sales, and customer loyalty.

A Study on Sustainable Design of Traditional Tujia Village Architecture in Southwest Hubei, China

The rapid urbanization in China in the past four decades has significantly affected traditional villages, resulting in a series of problems such as limited space, damaged style, weak sense of place, and loss of skills. This paper aims to establish a new paradigm for the sustainable development of village architecture in the Tujia ethnic area of southwestern Hubei province in order to address the issues of development and renovation of village architecture in this region. To achieve this goal, first, through field investigations and records of typical villages in the Tujia ethnic area of southwestern Hubei province, the characteristics of Tujia ethnic villages and the real challenges faced by village architecture are summarized. Secondly, the Delphi method is used to conduct expert interviews, construct a multi-level evaluation index system for sustainable development, and use the analytic hierarchy process to determine the weights of each index. Based on this, four design paradigms for sustainable development are proposed, including flexible layout, integrated interface composition, localized housing construction, and modular unit construction. These four paradigms cover the entire design stage from function to form, and from overall scene to structure. At the same time, multiple modular options are provided for each stage. Compared to the traditional experience-based construction model, the comprehensive benefits and promotability are greatly improved. Therefore, the research findings provide a reference for the sustainable development of traditional village architecture in other ethnic areas of China.

Enhancing Real-time Simultaneous Localization and Mapping with FPGA-based EKF-SLAM's Hardware Architecture

Simultaneous Localization and Mapping enable a mobile robot that is exploring an uncharted environment to localize itself and calculate its path within the map. In the context of green technologies and applications, there is a growing need for efficient SLAM solutions that not only provide accurate localization and mapping but also minimize power consumption. EKF-SLAM is a SLAM solution based on the Extended Kalman Filter, it is well known In the domain of robotics for its ability to handle non-linear models, its ability to handle noise related to the sensors, and its extremely high degree of precision. To guarantee real-time performance, the EKF-SLAM implementation requires a high-performance hardware architecture. In light of this challenge, researchers are thinking about using parallel processing platforms like FPGAs, which can provide the required level of performance and meet strict constraints on physics, computing capacity, and electrical power. This study describes a hardware architecture's implementation design for EKF-SLAM on an FPGA platform. The entire design is built on the Cyclone 2 FPGA, which has a maximum speed of 114 MHz and 18577 LUTs, creating a highly efficient hardware architecture.

Optimization of re-configurable multi-core processors and security based on field programmable gate arrays

<div align="center">n system-on-a-chip based complex processors has the problem of multithreading and miss-functionality due to their complexity and high-speed operations. In order to minimize these problems, the proposed design has machine learning based algorithms and cryptography systems for security has been incorporated. In the proposed work, the security level has been taken care of in three different stages such as data integrity, data authentication, and private and public keys encryption and decryption. In order to increase throughput with minimal latency, the proposed architecture with advanced high-performance protocol and advanced high-performance and advanced peripheral bus bridge is incorporated between the fabric dynamically re configurable multi-processor and peripherals along with security algorithms using secure hash algorithm (SHA-256) bits and advanced encryption standard (AES). In order to perform machine learning based applications, the proposed system is incorporated double-precision floating point arithmetic operations. The overall proposed architecture is developed in verilog hybrid deep learning (HDL) and quality checking using the LINT tool. The entire design is interfaced with the Zynq processor and software development kit (SDK) tool to verify data transfer between hardware and software. The obtained results are compared with existing state-of-art results and found that 18% improvement in throughput, a 21% improvement in power consumption savings, and a 34% reduction in latency.</div>

Integration and development of modern art design and environmental design in the context of deep learning

Abstract In the rapid development of digitalization, the combination of artificial intelligence technology and environmental art design is expected to gradually change the design process and promote the sustainable development of design. After specifically exploring the application of deep learning technology in the integration of modern art and environmental design, this paper utilizes the generative adversarial network under the deep learning model to design the intelligent color-matching model integrating visual aesthetics and the intelligent environmental art style generating a model based on CycleGAN, respectively and conducts the perceptual intention analysis of the environmental art design works under the intelligent generation to explore its developmental progression. The results of the eye movement experiment show that the correlation coefficients between the perceptual imagery score data of the four groups of environmental art designs are all in the range of 0.433 to 0.599, with a moderate positive correlation. Among them, the correlation coefficients between the total access time, gaze duration, gaze number, and perceptual imagery score are close to 0.6, and the significance coefficients are all less than 0.05, which indicates that the automatic generation of modern art design and environmental design proposed in this paper has a better user aesthetic preference. Introducing AI-assisted sustainable design can ensure the sustainability and effectiveness of the design solutions in practical applications, thus promoting the entire environmental art design industry to develop in a greener and more sustainable direction.

Machine Learning Aided Optimization of Non-Metallic Seals in Downhole Tools

Machine learning-based optimization analysis is conducted to improve the performance and reliability of non-metallic seals that undergo dynamic loading. Non-metallic seals, mostly made from elastomeric materials such as rubber, are widely used in the oil and gas industry due to their combination of hyper-elastic behavior and lack of plastic deformation under pressure and temperature cycles. However, these elastomeric materials could soften at elevated temperatures or during cyclic loading which makes them more prone to extrude from the seal region. For simple seals such as O-rings, thermoplastic anti-extrusion backup rings can be used to resist rubber extrusion. For more complex molded or bonded seals subject to cyclic loads and temperature cycles, minimizing the rubber damage and maintaining the seal integrity becomes more challenging as there may be inadequate room for backup rings. Additionally, the rubber may also experience repeated long stroke lengths during service which can cause surface abrasion. Non-metallic seals are extensively used in Sand Control Tools, a class of completion equipment. In the development of these molded and bonded seals, advanced optimization analysis techniques are important to make the seal design sufficiently robust to meet the stringent requirements of industry codes and regulations. Machine learning-based optimization analysis allows for increasing the seal performance and reliability. The Mullins effect is included in the elastomeric material model to capture the material softening effects under cyclic loading. Machine learning-based optimization starts with a feasible design space that is defined based on the controlling design parameters related to the geometry of the seal. Comprehensive Finite Element Analysis is performed on each design sample under the target cyclic load and temperature cycles. The key response parameters of the non-metallic seal are selected as the principal strain and the contact stress in the rubber which together indicate the damage and seal-ability states of the design. A Performance Objective Index is defined as a function of the key response parameters. The FEA results covering the entire design space provide the simulation-driven training data to build the surrogate model using multi-layer neural networks. The optimum design solution is found from the surrogate model which correlates the Performance Objective Index to the design parameters. The results of this study reveal that the performance of the seal is greatly affected by the ratio of the elastomeric seal volume to the gland volume into which the seal is molded. As opposed to the base design, the optimum design shows a solid performance with no signs of extrusion when the principal strain of the rubber is kept below the elongation limit throughout the load cycles, and when sufficient contact stress is developed to maintain the seal.