Improvement Of Design Process Research Articles

Rework in civil construction projects at design phase: Influencing factors and suggested solutions

Among the various project phases, the design phase often contains errors that result in rework in civil construction projects. This rework can lead to budget overruns, schedule delays, and a decline in construction quality. There is rare knowledge of reworks in civil construction projects, especially in the design phase. This paper presents an overview of the influencing factors and solutions for reworks in civil construction projects at the design phase. To achieve this objective, a survey on the causes of rework was conducted with experts experienced in designing and constructing civil projects in southern Vietnam. Civil engineers and investors involved in the project at the design phases were targets of the survey. Five groups, including designers, design managers, investors, subcontractors, and objective conditions, were selected for designing survey questionnaires. Then, the PCA (principal component analysis) was applied to the collected data to reveal the most influencing factors on rework causes. Based on the results obtained, several suggestions are proposed to minimize rework in civil construction projects. These findings can serve as valuable insights for investors and design consultants, fostering learning and process improvements to reduce rework in future projects.

Experimental analysis of the forming behavior of uni- and bidirectional non-crimp fabrics for different geometries

For efficient large-series production and improved process design, a profound understanding of a textile’s forming behavior is crucial to ensure adequate drapability and defect-free components. Woven fabrics have often been the focus of research due to their easier formability, while non-crimp fabrics (NCFs) have been investigated much less despite their higher lightweight potential, resulting in a limited experimental basis for the validation of numerical models. Therefore, forming experiments of a unidirectional and a bidirectional NCF are conducted for different configurations and punch shapes, including hemisphere, tetrahedron, and square box. The macroscopic strains are captured throughout the entire process using digital image correlation (DIC) and comprehensively analyzed in combination with the outer contour and resulting defects. Fundamental differences in the deformation behavior of both textiles are identified. For the balanced Biax-NCF, the tricot stitching couples the deformation of both fiber layers and the fabric mainly deforms under symmetrical shear with limited yarn slippage or defects. For the highly unbalanced UD-NCF, the lack of a second fiber direction results in an asymmetrical deformation behavior. The UD-NCF deforms due to shear parallel to the fiber yarns superimposed with transverse tensile and compressive strains in different deformation modes. The data generated in this study is freely available at https://doi.org/10.5281/zenodo.12516897.

Impact of modern technological methods of knowledge management and total quality management on the performance of educational colleges faculty: A case of Jordan

This research investigates the impact of modern technological methods of knowledge management (KM) and total quality management (TQM) on the performance of faculty members in educational colleges in Jordan. Drawing on a survey conducted with 306 faculty members, the study examines the influence of technology on teaching methodologies and academic quality within the Jordanian higher education context. The study utilizes the Technology Acceptance Model (TAM) to back up the modern technological methods of knowledge management (KM) and total quality management (TQM) models. The findings reveal a generally positive perception among respondents regarding the beneficial effects of modern technological tools on teaching effectiveness, collaboration, and innovation. Additionally, technology-enhanced TQM practices were found to contribute to improvements in curriculum design, student engagement, and administrative processes. Regression and correlation analyses support significant relationships between technology-enabled KM and TQM practices and faculty performance, highlighting the transformative role of technology in shaping the future of higher education in Jordan. Recommendations are provided for educational institutions to enhance the integration of technology and foster a culture of innovation and continuous improvement among faculty members.

Digital Trio: Integration of BIM–EIR–IoT for Facilities Management of Mega Construction Projects

Facility Management (FM) has increasingly focused on integrating Building Information Modeling (BIM) with the Internet of Things (IoT), known as digital twins, in large-scale development projects. Effective BIM integration in FM requires improved cooperation among participants across various project stages. This digital revolution aims to enhance planning, construction, and asset management efficiency, benefiting all parties. However, BIM utilization in FM is limited by incomplete owner understanding, insufficient data accessibility, and stakeholders’ unfamiliarity with BIM procedures and standards. Despite recognizing BIM’s significance, the FM industry faces significant implementation challenges. Facility managers often lack a comprehensive understanding of BIM’s benefits in streamlining operations and enhancing cost efficiency, as well as the necessary skills for its use. Addressing these barriers requires developing an Employer’s Information Requirements (EIR) document at a project’s outset, providing a strategic plan and vision for all involved parties. BIM and IoT are pivotal technologies for transitioning to efficient building operations and crucial for reducing time, costs, and operational challenges throughout any project. This research aims to establish a digital trio workflow, integrating BIM, EIR, and IoT to maximize stakeholder benefits. It explores how preparing the EIR through stakeholder communication can improve design processes, sustainability, efficiency, cost, and time, especially for megaprojects.

A Method for Human Systems Integration Requirements within Model Based Systems Engineering

AbstractThe Department of Defense (DoD) employs broad human factors requirements across various applications, resulting in a universal application of the same standards to a multitude of DoD acquisition systems. In unconventional warfare, specifically within missions conducted by US Special Operations Command (USSOCOM), operators face intensified workloads and domain‐specific challenges that current human factors considerations do not adequately address. The objective of this paper aims to introduce a novel framework, the Relational and Technological Capstone (RTC), designed to expand existing Human Systems Integration (HSI) requirements. The objective is to enhance the consideration of human factors in USSOCOM missions by addressing the unique challenges posed by intensified workloads and domain‐specific ontologies. The RTC employs a methodology‐driven approach utilizing both architectural and parametric diagrams. It integrates with Model Based Systems Engineering (MBSE) to improve the design of human‐system interactions, incorporating a Special Operations Task List and Performance Shaping Factors (PSFs) into aggregated parametrics. The results of this paper demonstrate the efficacy of RTC within MBSE, showcasing its value through improved design processes and as a foundation for new programs. The containment tree format aids in developing USSOCOM MBSE and opens possibilities for automation tools. Continual use of RTC contributes to the maturity of MBSE models and diagrams, fostering the evolution of a federation‐of‐models and Program of Record standards. This not only benefits subsequent SOCOM programs and projects but also facilitates cross‐cooperation with other nations in optimizing special operation acquisitions. The ultimate goal is to center the RTC around the operator, ensuring compatibility and optimization across cooperative nations' special operation acquisitions.

Double-diode model carrier lifetime-based internal recombination parameter analysis and efficiency prediction of crystalline Si solar cells

With the continuous and significant advancements in the performance of crystalline silicon (c-Si) solar cells, an effective method for a detailed analysis of the efficiency loss factors is increasingly important. Specifically, a detailed analysis of recombination parameter (J0) is crucial for devising strategies to approach the theoretical efficiency limit. In this study, we propose an analysis method that utilizes minority carrier lifetime based on the double-diode model and predicts the performance efficiency of c-Si solar cells. The analysis, conducted through the p-PERC structure, examines the contributions to J0 from different recombination areas. The advantages of this method include: (i) its relative simplicity and reliance on non-destructive analysis techniques; (ii) its capability to extract internal recombination parameters, such as J0,total emitter, J0,rear, and J02, from a fully assembled solar cell with metal contacts. Furthermore, this method serves as a diagnostic tool to identify the sequence in which parameters should be adjusted to enhance solar cell efficiency effectively and to pinpoint areas within the solar cell that significantly limit performance efficiency. Using this method, the diagnosis of the p-PERC cell revealed that the main cause of performance limitation was the emitter in the front region. The carrier lifetime analysis showed that for overcoming cell performance limitations, it is more effective to design process improvements in the following order: i) front emitter region (J0,em), ii) space charge region (J02), iii) rear surface region (J0r).

Performance benchmark of different cell clones in discontinuous and continuous bioprocesses reveals critical impact of cellular diameter

Therapeutic proteins such as monoclonal antibodies are usually manufactured either in continuous processes such as steady-state perfusion or in discontinuous processes like fed-batch (FB). Thereby, both process formats have fundamentally different requirements for the utilized cell factories. This poses a problem as common cell line development programs are designed to select cell clones to perform well in FB cultivation. The aim of this study was to identify critical and easy to access cell line attributes for each process format and with that for the transfer of clones from fed-batch to perfusion. As a result, increased cell-volume specific productivity could be identified as beneficial within the FB not only impacting performance but as well diminishing media utilization and host-cell-proteins level. Within the perfusion, a stable cell diameter was identified as major beneficial characteristic, positively influencing cell viability, metabolite and glycan profile, as well as equipment utilization. Consistent with this, our data suggest that the inclusion of cell volume in the screening parameters is important for clone selection for both process formats and can lead to improved process design and robust cell line process transfer. Overall, this work gives valuable new insights in cell behaviour across discontinuous and continuous process formats to improve clone cell selection for both process strategies and streamline the process transfer from discontinuous towards continuous.

Radiation Damage Mechanisms and Research Status of Radiation-Resistant Optical Fibers: A Review.

In recent years, optical fibers have found extensive use in special environments, including high-energy radiation scenarios like nuclear explosion diagnostics and reactor monitoring. However, radiation exposure, such as X-rays, gamma rays, and neutrons, can compromise fiber safety and reliability. Consequently, researchers worldwide are focusing on radiation-resistant fiber optic technology. This paper examines optical fiber radiation damage mechanisms, encompassing ionization damage, displacement damage, and defect centers. It also surveys the current research on radiation-resistant fiber optic design, including doping and manufacturing process improvements. Ultimately, it summarizes the effectiveness of various approaches and forecasts the future of radiation-resistant optical fibers.

Application of Simulation-Based Metrics to Improve the Daylight Performance of a Secondary School, An Approach for Green Building Designers and Architects

Visual comfort affects the quality of classrooms as well as student learning. A practice-oriented approach discovers how the gap between academic research and its application in building design can be addressed. Nevertheless, the physical characteristics design of daylighting systems, including window sizes, shapes, dimensions, and materials, are considered fundamental challenges for their practicability. In this study, the physical characteristics design of daylighting systems, including window sizes, shapes, dimensions, and materials, are considered in a designed sample school, and the daylight metrics were analyzed to achieve more trustworthy and applicable daylighting systems. Grasshopper (Honeybee-Ladybug), as a parametric control method, was applied to simulate the daylighting quality for various educational spaces in a secondary school in Sanandaj City, based on average ‘Daylight Factor’, ‘Daylight Autonomy’, ‘Useful Daylight Illuminance’, and ‘Annual Sunlight Exposure’. These metrics were examined to discover the relationship between window size and positions on visual comfort. The results indicate daylighting assessments are a solid approach to revising the architectural design mistakes at the primary designing phase. Architects and other building designers or energy consumption assessors can apply the design improvement process to present more sufficient and successful architectural details. This is a fundamental step toward the implementation of green buildings.

Design improvement for suction shape in rotary compressor

Rotary compressors applied to heating and cooling cycles accounts for a large proportion of the total energy consumed in the system. Therefore, improving compressor efficiency is crucial in order to reduce energy consumption. Design review and improvement efforts have primarily focused on compression and discharge parts with high pressure. However, due to the limitations in design improvements for the compression and discharge parts, enhancements for other components are necessary to further increase compressor efficiency. In this study, the design of the suction part of the rotary compressor was modified using FSI (Fluid-Structure Interact) analysis scheme. In order to improve the design of the suction shape, new suction shape types were devised as alternatives to the existing through type. Both the newly devised C-type and E-type suction shapes presented an increase in cooling capacity due to reduced suction resistance, with the E-type demonstrating greater improvement compared to the C-type. Consequently, a verification of the effect based on the detailed design dimensions was further conducted for the E-type suction shape. The final selected improved model increased the suction flow rate by approximately 2.5% compared to the base model. This indicates that significant improvement for the compressor efficiency can be achieved through modifying designs in parts other than the compression and discharge sections. In addition, a design improvement process was established to analyze internal flow using FSI analysis.

Removal of nitric oxide in bioreactors: a review on the pathways, governing factors and mathematical modelling.

The constant surge in nitric oxide in the atmosphere results in severe environmental degradation, negatively impacting human health and ecosystems, and is presently a global concern. Widely used physicochemical technologies for nitric oxide (NO) removal comes with high installation and operational costs and the production of secondary pollutants. Thus, biological treatment has been emphasized over the last two decades, but the poor solubility of NO in water makes it a challenging issue. The present article reviews the various technical aspects of biological treatment of nitric oxide, including the removal pathways and reactor configurations involved in the process. The most widely used technologies in this regard are chemical adsorption processes followed by biological reactors like biofilters, biotrickling filters and membrane bioreactors that enhance NO solubility and offer the flexibility and scope of further improvement in process design. The effect of various experimental and operational parameters on NO removal, including pH, carbon source, gas flow rate, gas residence time and presence of inhibitory components in the flue gas, is also discussed along with the developed mathematical models for predicting NO removal in a biological treatment system. There is an extensive scope of investigation regarding the development of an economical system to remove NO, and an exhaustive model that would optimize the process considering maximum practical parameters encountered during such operation. A detailed discussion made in this article gives a proper insight into all these areas.

Designing a Model of Factors Influencing Marketing and Competitiveness in the Automotive Industry in Iran

Competitiveness is among the critical topics that has been emphasized in the management and marketing literature in recent years. The increasing competition and the abundance of products produced by automotive groups both domestically and internationally have presented Iranian customers with a wide range of choices. This study seeks to identify, categorize, and model the factors influencing the marketing and competitiveness of the automotive industry in Iran by employing the qualitative thematic analysis research method. In this regard, interviews were conducted with 14 professors and senior experts in the automotive marketing field, each with a minimum of 10 years of work experience and at least a master's degree. According to the qualitative model, 11 main categories were identified and classified under contexts, processes, and outcomes as follows: The context category includes domestic and foreign investment attraction, proper policymaking, sanctions, state ownership, and monopoly. The process category includes marketing and competitiveness in the automotive industry, knowledge and technology development, improvement of design and production processes, and improvement of services. The outcomes of the presented model include customer satisfaction and increased market share. Additionally, the variables of proper policymaking and domestic and foreign investment attraction had the highest frequency, indicating the greater importance of these variables in the research model.

In-process monitoring and direct simulation of Argon shielding gas and vapour dynamics to control laser-matter interaction in laser powder bed fusion additive manufacturing

Laser powder bed fusion (L-PBF) additive manufacturing (AM) enables the fabrication of parts with precise dimensional control, freedom of design and material properties similar to or better than those fabricated using traditional manufacturing approaches. AM quality control depends upon the fundamental of the laser-matter interaction during metal AM using L-PBF to exploit the potential use of the materials and process control. In this work, thermal-fluid dynamics in gas chamber experimentally and computationally is used to elucidate the interplay between vapour, liquid, and solid phases in L-PBF. It is revealed that the argon (Ar) shielding gas flow with varied inlet velocities by different nozzles has a pronounced effect to minimise the laser-fume interaction, resulting in the reduction in unstable metal vapour flow and enhancing laser absorptivity. In-process monitoring via high-speed visualisation has been used to understand the simultaneous gas plume dynamics as a result of vapourisation and subsequent laser-fume interaction, backed up by thermal-fluid flow simulation. Unfavourable process dynamics associated with unwanted defects such as lack of fusion can be avoided to improve process design and enhance process stability.

Evaluating large-language-model chatbots to engage communities in large-scale design projects

Abstract Recent advances in machine learning have enabled computers to converse with humans meaningfully. In this study, we propose using this technology to facilitate design conversations in large-scale urban development projects by creating chatbot systems that can automate and streamline information exchange between stakeholders and designers. To this end, we developed and evaluated a proof-of-concept chatbot system that can perform design conversations on a specific construction project and convert those conversations into a list of requirements. Next, in an experiment with 56 participants, we compared the chatbot system to a regular online survey, focusing on user satisfaction and the quality and quantity of collected information. The results revealed that, with regard to user satisfaction, the participants preferred the chatbot experience to a regular survey. However, we found that chatbot conversations produced more data than the survey, with a similar rate of novel ideas but fewer themes. Our findings provide robust evidence that chatbots can be effectively used for design discussions in large-scale design projects and offer a user-friendly experience that can help to engage people in the design process. Based on this evidence, by providing a space for meaningful conversations between stakeholders and expanding the reach of design projects, the use of chatbot systems in interactive design systems can potentially improve design processes and their outcomes.

(Electrodeposition Division Research Award) Electrodeposition as an Enabling Technology in Future Semiconductors, Energy Storage, and Sustainable Metal Production

Electrodeposition is a truly fascinating process. On the one hand, it is highly complex as it entails a myriad of intricately intertwined physiochemical events (transport, kinetics, nucleation, growth, to name a few). Despite this, to a practitioner, electrodeposition can be remarkably simple, easy to control, and safe to operate. Electrodeposition is also extremely versatile, enabling fabrication of various materials (metals, alloys, semiconductors), fabrication onto conductive or resistive substrates, facilitating intricate pattern formation, and providing selectivity in growth. These advantages make electrodeposition a process of choice in a broad range of technologically-important applications: batteries, semiconductor devices, electrometallurgy, and others.1-3 Morphology control is crucial in the industrial practice of electrodeposition. During metallization of nano-scale interconnects in advanced semiconductor devices, metal deposition with near atomic precision is required.1 Similarly, during operation of lithium metal rechargeable batteries, electrodeposition must be controlled to avoid dendritic growth during battery charging.2 Electrodeposition processes in high temperature molten salts, such as those used for electrowinning rare-earth metals, favor spongy deposits which can manifest in entrapment of impurities – here too, controlling morphology is central to overall electrowinning efficacy.3 In this talk, I will discuss and demonstrate how unprecedented morphology control can be achieved in electrodeposition. Such control leverages fundamental understanding of the electrochemical processes at the electrode-electrolyte interface. Specifically, by regulating the electrolyte properties, applied current or potential waveforms, and by employing ‘additives’, the diffusion-reaction processes can be controlled yielding desirable electrodeposit morphologies. Such design of electrodeposition processes is considerably aided by mathematical modeling. I will provide a few examples of how quantitative modeling enables improved process designs in aforementioned applications.During my odyssey in electrodeposition since 2001, I have been fortunate to have exceptional colleagues, collaborators, sponsors, mentors, students and friends, who have made this journey enjoyable and enriching. I am also very thankful for my affiliation to the Electrochemical Society and its electrodeposition division. In my talk, I will provide a few perspectives and anecdotes on how the ECS community has positively impacted me personally and professionally.

Analyzing and Modeling the Municipal Sewage Sludge Drying Process Using Python

The programming language Python offers the opportunity to analyze and model the municipal sewage sludge (MSS) drying process in an illustrative chemical engineering practice. The drying process is performed on a flat plate while maintaining a uniform, parallel drying air speed. The Python program helps to analyze the digitalized weight measurements from each sample. The program enables the sorting of input data, determination of the drying critical point, and evaluation of the first and second drying periods. Moreover, the model calculates the fundamental drying parameter and forms a drying master curve to support the transfer to different drying conditions. The basic parameters calculated are mass transfer coefficient, heat transfer coefficient, and diffusion coefficient. The results are consistent with published data for those coefficients over the drying temperature range of 19.4–52.4 °C and relative humidity range of 8.2–33.6%. The findings of this study demonstrate the potential of Python as a powerful tool for analyzing experimental data and modeling chemical processes, which can lead to improved process design, optimization, and control.

Development and testing of lean simulation game on set-based design

Purpose Set-based design (SBD) is a lean tool widely adopted for improving design processes and providing value maximization to clients. The purpose of this paper is to present the development and testing of a lean simulation game that incorporated point-based and SBD principles. The objective of the game was to enhance learning of lean design management among construction students. Design/methodology/approach After a thorough and comprehensive literature review consisting of secondary data in journal papers, books, thesis references and primary data in the form of interviews with lean practitioners, the simulation game prototype was developed. The testing of the game was carried out with a study group. Data were collected during the gameplay with the help of a questionnaire survey on a confidence scale and Likert scale and assessed using the Wilcoxon signed-rank test, histogram, one-sample t-test and false discovery rate (Benjamini–Hochberg) correction method. Findings The data collected both pre- and post-simulation showed an increase in average confidence in understanding from 3.33 to 3.89, a 16.7% rise. The data was further interpreted by using Wilcoxon signed-rank test, indicating that the post-simulation learning experience was significantly better than the pre-simulation one. Promising positive results were obtained for the questions on game design, engagement and understanding of point-based design and SBD concepts. Originality/value The simulation game helps bridge the gap between knowledge building and real-life by effectively imitating the process. The game facilitates a dynamic and critical approach toward developing new educational simulation games and their successful incorporation in propagating lean principles in the construction industry.

Autotrophic Production of the Sesquiterpene α-Humulene with Cupriavidus necator in a Controlled Bioreactor.

Cupriavidus necator is a facultative chemolithotrophic organism that grows under both heterotrophic and autotrophic conditions. It is becoming increasingly important due to its ability to convert CO2 into industrially valuable chemicals. To translate the potential of C. necator into technical applications, it is necessary to optimize and scale up production processes. A previous proof-of-principle study showed that C. necator can be used for the de novo production of the terpene α-humulene from CO2 up to concentrations of 11 mg L-1 in septum flasks. However, an increase in final product titer and space-time yield will be necessary to establish an economically viable industrial process. To ensure optimized growth and production conditions, the application of an improved process design in a gas bioreactor with the control of pH, dissolved oxygen and temperature including a controlled gas supply was investigated. In the controlled gas bioreactor, the concentration of α-humulene was improved by a factor of 6.6 and the space-time yield was improved by a factor of 13.2. These results represent an important step toward the autotrophic production of high-value chemicals from CO2. In addition, the in situ product removal of α-humulene was investigated and important indications of the critical logP value were obtained, which was in the range of 3.0-4.2.

Enhancing Energy Efficiency and Reliability in Floating LNG Operation: A Hydrofluoroolefin-Based SMR Cycle with Thermo-Economic Assessment and Uncertainty Analysis

Natural gas liquefaction is the most energy-intensive technique in floating liquefied natural gas (FLNG) operations. Hence, a hydrofluoroolefin-based single mixed refrigerant (SMR) technology was proposed to achieve energy-efficient and eco-friendly operations. The study was perfomed to enhance the SMR process by substituting expansion valves with hydraulic turbines to improve process reversibility and enhance energy efficiency. The proposed process was optimized using a sine–cosine concept-based algorithm that tuned the design variables which yielded an overall compression energy consumption of 0.2501 (kWh/kg-LNG), resulting in a 21.43% saving as compared to the conventionally used mixed refrigerant-based process. This resulted in a reduction of about 38.81% in overall exergy destruction. The economic analysis results draw curtains that the process saves about 26.02% of total annualized cost as compared to conventional study. Owing to the appropriate mixed refrigerant component mixture ratio and process design improvement. To determine the process reliability under uncertain conditions the optimal compression power and minimum approach temperature were determined. Further, uncertainty analysis reveals that the methane and butane refrigerant flow rates along with evaporation, and condensation pressure, were among the most influential parameters that influence the process most that may affect the whole operation in uncertain process inlet conditions. In summary, our approach presents immense promise for achieving energy efficiency, environmental responsibility, and economic viability in FLNG operations, offering a robust solution for the challenges of offshore plants.

Automobile rear axle housing design and production process improvement using Failure Mode and Effects Analysis (FMEA)

The safety of automobile design is crucial to protect drivers, passengers, and other road users, ensuring reliable performance, accident prevention, and regulatory compliance.The rear axle housing in automobiles serves as a protective enclosure for the rear axle assembly, providing support, protection, and structural integrity for the drivetrain components. This research paper employs Failure Modes and Effects Analysis (FMEA) to comprehensively identify and assess common failures in the design and manufacturing process of rear axle housings in automobiles. The study highlights five critical failure modes, namely less durability, faulty blank, hole position out, burred edges, and bore position out. Through the application of recommended solutions, including design optimization, maintenance of shear blades, and the use of jigs, substantial reductions in Risk Priority Number (RPN) values were achieved. Specifically, the RPN values for the aforementioned failure modes were significantly decreased from 280 to 40, 256 to 48, 378 to 21, 378 to 45, and 392 to 56, respectively. Implementation of these solutions promises several benefits, such as enhanced customer satisfaction, reduced failure rates, elevated product/process quality and reliability, streamlined processes, and optimized resource utilization. This study emphasizes the significance of continuous improvement efforts in the automotive industry and demonstrates the pivotal role of FMEA as an invaluable tool for achieving and sustaining these improvements.