Multidisciplinary Engineering Research Articles

Identification of Risk Management Techniques for Use in Dismantling Ships and Offshore Structures

Objective: To identify risk management techniques that can be applied to the dismantling of ships and oil platforms, which will result in improved risk management of this activity in Brazilian shipyards designed for this purpose, using a methodology adapted to existing dismantling models. Method: The research developed is considered qualitative, using complex conceptual approaches and analyses, through the interaction between variables present in the context, with methodological conclusions for practical application. Results and Discussion: The intention of the dismantling methodology is to list the stages in a practical way, indicating, in each stage, the techniques that are best applied and that allow for more effective risk management. Identifying the risks of each stage of the dismantling ensures that the result is safe and sustainable, as it takes into account all the nuances involved in the process. Research Implications: Decommissioning activities, based on the identification of the most appropriate risk management techniques to support implementation, planning, monitoring and measurement, can be better developed at each stage of the methodology, since the application of the techniques encompasses the entire process, from the initial budget to the separation and disposal of the removed parts, considering the risks of the activities at all stages. Originality/Value: The study contributes with an innovative approach by including appropriate risk management techniques in the decommissioning activities of ships and offshore structures, in order to support multidisciplinary engineering at all stages of decommissioning.

An Approach of Artificial Intelligence in Multidisciplinary Engineering Applications (Part II)

An Approach of Artificial Intelligence in Multidisciplinary Engineering Applications (Part II)

Integrating Entropy-based Data Reduction and Machine Learning in Multidisciplinary Engineering Systems for Enhanced Response Prediction

This research presents a framework that aims to capture and model streamlined design variables in multidisciplinary engineering systems, particularly when uncertainties are present. In multidisciplinary domains, there may be correlated design variables that are surplus, leading to data redundancy and potentially affecting the prediction of system responses. To address this issue, the framework utilizes data reduction techniques based on the correlation degree of random design variables, which are evaluated using an entropybased correlation coefficient (e). By doing so, the framework enables a more precise prediction of system responses. The data reduction process is dependent on the value of e and employs two distinct approaches. For strong correlations (high e values), feature extraction techniques such as Principal Component Analysis and the Auto-encoder algorithm are applied. On the other hand, for weak correlations, feature selection is implemented using the Independent Features Test. To effectively predict the complex responses of multidisciplinary systems while enhancing computational efficiency, the framework integrates an Artificial Neural Network. The efficacy of the proposed framework is demonstrated through examples, including a cantilever beam with randomly distributed materials and an electro-mechanical stretchable patch antenna.

A Systematic Literature Review of Policy Analysis and Modeling in Systems Engineering

AbstractThe International Council on Systems Engineering (INCOSE) defines systems engineering as “a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods.” The evolution of engineering practices requires new research in the disciplinary intersections of scientific, technological, and management methods, especially when considering the INCOSE System Engineering Vision of 2035, which identified political, economic, social, technical, environmental, and legal factors as becoming modern tenets of system engineering success. Because vast amounts of research have been performed in multidisciplinary engineering areas, this paper examines the research landscape at the intersection of policy modeling and systems engineering by providing a systematic review of the literature to help guide future research based on trends and various guiding considerations. The results of this study will help identify gaps in the field while clarifying future research needs. We have applied the preferred reporting items for systematic reviews and meta‐analyses (PRISMA) protocol, which yielded 38 peer‐reviewed papers related to policy modeling and systems engineering.

Instilling SDG Considerations in Undergraduate Design Capstone

Engineering education in universities often focuses on theoretical problems, with limited opportunities for students to consider the societal and environmental impact of their designs. Senior engineering design capstones typically involve industry partners providing the problem and context, further restricting students' ability to explore implications. Despite being aware of the United Nations Sustainable Development Goals (SDGs), students prioritize personal over professional implications. This study aims to incorporate SDGs into the Engineering Capstone experience by introducing them in a senior student-driven, multidisciplinary Engineering Capstone Design class. Students receive empathy training and use Canadian indicators of UN SDGs to align their designs with positive and negative indicators. They engage with users for feedback on the impact of their choices on SDGs, bridging the "blind spot" in their design work and enhancing understanding of the broader context of their designs. Incorporating empathy training and a co-design approach can improve students' understanding of the potential impact of their designs on SDGs.

Exploring the connection between deep learning and learning assessments: a cross-disciplinary engineering education perspective

It is widely accepted that student learning is significantly affected by assessment methods, but a concrete relationship has not been established in the context of multidisciplinary engineering education. Students make a physiological investment and internalize learning (deep learning) if they see high value in their learning. They persist despite challenges and take delight in accomplishing their work. As student deep learning is affected by the assessment system, it is important to explore the relationship between assessment systems and factors affecting deep learning. This study identifies the factors associated with deep learning and examines the relationships between different assessment systems those factors. A conceptual model is proposed, and a structured questionnaire was designed and directed to 600 Queensland University of Technology (QUT) multidisciplinary engineering students, with 243 responses received. The gathered data were analyzed using both SPSS and SEM. Exploratory factor analysis revealed that deep learning is strongly associated with learning environment and course design and content. Strong influence of both summative and formative assessment on learning was established in this study. Engineering educators can facilitate deep learning by adopting both assessment types simultaneously to make the learning process more effective. The proposed theoretical model related to the deep learning concept can support the key practices and modern learning methodologies currently adopted to enhance the learning and teaching process.

Human Resource Management Digitalisation in Multidisciplinary Ship Design Companies

Abstract The digitalisation in the ship design sector is currently applied to the design process itself and is well defined, partially standardised and practically implemented by both independent design companies and the design departments of shipyards. The situation is similar in other sectors of engineering. However, the requirements for the digitalisation of other processes in design and engineering companies have not previously been studied, and the limited financial resources of ship design companies mean that there is a need for research on the digitalisation needs of multidisciplinary ship design companies. The implementation of building information modelling (BIM) solutions is costly for design companies and generates benefits mainly for shipyards and shipowners. The lack of benefits for design companies leads to the hesitation of managers whenever digitalisation is considered; the scope and scale of the digitalisation, as well as the selected software and BIM level, are defined by the shipyard requirements. The participation and support of management in the digitalisation process is one of the key success factors; the expected benefits caused by digitalisation for the organisation will increase the motivation of managers to invest limited resources in digitalisation. There are no data that indicate the processes with a high potential for digitalisation and the scale of expected improvements in ship design companies; therefore, research in this area was performed with a group of project managers from design and engineering companies. The research focused on collecting the opinions and experiences of the managers related to the manual management of resources and comparing the poll results with the conclusions from the enterprise resource planning (ERP) system data analyses. The paper analyses if the digital automation of the resource management process can lead to the substantial improvement of the operations of multi-project, multidisciplinary engineering ship design companies.

Involving students in engineering course design: a combined approach based on constructive alignment and multi-criteria decision-making

ABSTRACT Empowering students to actively shape their learning is essential. Various student involvement models, such as design-based research, participatory design, and co-creation, emphasise students’ growing role in shaping educational activities. Engaging students in course design, as seen in student co-creation, can enhance agency, improve the student experience, and boost outcomes. Considering this, we propose a systematic approach combining multi-criteria decision-making with constructive alignment theory to involve students as co-creators in course design. This approach aims to engage students in the course design process and co-create intended learning outcomes, which can be regarded as the primary participatory phase in developing a co-created course. By involving students, our approach aims to gain insight into their needs, prioritise their views, and guide the formulation of appropriate course specifications throughout the course design process. The approach is applied to a new multi-disciplinary engineering course, and the results are summarised following its corresponding steps. Students’ feedback indicates that the approach positively influenced their motivation, engagement with course objectives, collaboration with teachers, and overall achievement of intended learning outcomes. This study’s significance lies in its contribution to higher education, offering a more integrated and systematic approach to support co-creation between educators and learners in academic course design.

Estimation methodology for three-dimensional acoustic modeling: Predicting surf noise soundscapes in coastal urban environments

This research develops an estimation methodology for coastal surf noise soundscapes for implementation in three-dimensional acoustic modeling to improve communication of acoustic design and for assessment with sustainability, wellness and acoustic standards. As sustainability standards include more parameters relating to soundscapes, it is becoming increasing important to develop methods of communicating acoustics to designers in the built environment. Three-dimensional acoustic modeling provides a graphical tool for designers to engage with and understand the impacts multidisciplinary engineering and design decisions have on the soundscape of different parts of a project. As a nation with many coastal urban environments, the view, scents and sounds are all marketing and wellness points for residential and commercial projects. The methodology includes consideration of typical software-agnostic three-dimensional modeling inputs, capabilities and graphical outputs as well as the primary variables that influence measurement and prediction of coastal surf noise in relation to the constant environmental noise. Coast surf noise measurements have been collected and undertaken as part of this work and the data within the method may be updated for most locally measured data. This research aims to enhance the demonstration of soundscapes, facilitating more informed decision-making fostering sustainable development in acoustics, engineering and design.

Quantifying Radiation Induced Vaginal Stenosis for the Development of a Novel Dilator Device: A Prospective Cohort Study of Patients with Cervical Cancer Treated with Definitive Chemoradiation Therapy

Chemoradiation therapy (CRT) is the standard of care for the treatment of locally advanced cervical cancer (LACC). Vaginal stenosis (VS) is a common side effect of CRT and leads to sexual dysfunction, pain, and difficulty with vaginal intercourse, resulting in decreasing quality-of-life (QOL). However, there is scant data on the timeline of VS development, and patient use and satisfaction with a standard vaginal dilator (VD). In this study, we plan to develop a standardized technique to assess VS using physical exam measurements at specified timepoints after CRT. Secondarily, we will assess patient preferences and use of available VDs with the goal of developing a novel VD device with our multidisciplinary engineering team. We report the rationale, methods, and objectives of this clinical study. Patients with LACC treated with CRT and brachytherapy are eligible. CT-based imaging pre-CRT and 3-months post-CRT to assess radiographic changes in the vaginal length and width will be collected. Vaginal measurements and physical exam will be recorded at baseline and 3-, 6-, and 12-months following CRT. Patients will also be given a set of VDs that range in diameter and length. Patient vaginal capacity, defined as the largest VD that can be comfortably accommodated in the vagina during pelvic exam, and compliance with VD use will be recorded at each visit. Patients will be given the EORTC Sexual Health Questionnaire (EORTC SHQ-22). Toxicity grading will use the CTCAE v5. We plan to assess patient preference using a VD-specific questionnaire to help guide the development of a personalized VD. For the primary analysis, we will examine the VS CTCAE v5 toxicity at baseline vs 1 year for 20 patients. The sample size we propose is sufficient to achieve at least 80% power at 5% significance level for detecting a significant non-zero proportion with a margin of 20%. For the secondary analysis, we will test the Spearman's coefficient and Kendall's tau between VS CTCAE and EORTC questions: "has the treatment affected your sexual activity?"; "have you felt pain during/after sexual activity?"; "have you been sexually active?" We will use permutation tests in which the ID will be permuted for vaginal stricture but kept as original for the EORTC questions. We will test the null hypothesis of no correlation by comparing the observed Spearman's coefficient and Kendall's tau to the permutation distributions. We plan to incorporate the specific VD questionnaire responses into the development of a novel device using qualitative measures. This clinical trial is an observational cohort study that aims to quantify CRT-induced VS, obtain patient reported sexual health, and understand specific preferences and compliance with VD use for the development of a novel engineered device.

Emerging Applications of Biomedical Science in Pandemic Prevention and Control: A Review.

The COVID-19 pandemic has made it abundantly clear how crucial biomedical science is to pandemic control and prevention on a global scale. The importance of biomedical science in the fight against pandemics has increased with the appearance of new, deadly infectious diseases. Biomedical science and engineering have been presented as possible areas for combating the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to the unique challenges raised by the pandemic, as reported by epidemiologists, immunologists, and doctors, including thesurvival, symptoms, protein surface composition, and infection mechanisms of COVID-19. These multidisciplinary engineering concepts are applied to design and develop prevention methods, diagnostics, monitoring, and therapies. An infectious disease outbreak that has spread over a sizable region, such as several continents or the entire world, and is affecting a sizable number of people is referred to as a "pandemic. While current knowledge about the SARS-CoV-2 virus is still limited, various (old and new) biomedical approaches have been developed and tested. Here, we review the emerging applications of biomedical science in pandemic prevention and control, including rapid diagnosis tests, the development of vaccines, antiviral therapies, artificial intelligence, genome sequencing, and personal protective equipment. Biomedical science and nanotechnology are two fields that have the potential to combine to develop emerging applications for combating pandemics. In this review, we also discuss the intersection of biomedical science and nanotechnology in pandemic prevention and control.

Failure Mode and Effect Analysis with a Fuzzy Logic Approach

Failure mode and effect analysis (FMEA) is one of the most used techniques in risk management due to its potential to solve multidisciplinary engineering problems. The role of experts is fundamental when developing the FMEA; they identify the failure modes by expressing their opinion based on their experience. A relevant aspect is a way in which the experts evaluate to obtain the indicator of the risk priority number (RPN), which is based on qualitative analysis and a table of criteria where they subjectively and intuitively determine the factor level (severity, occurrence, and detection) for each of the failures. With this, imprecision is present due to the interpretation that each one has regarding the failures. Therefore, this research proposes a fuzzy logic evaluation system with a solid mathematical basis that integrates these conditions of imprecision and uncertainty, thus offering a robust system capable of emulating the evaluation form of experts to support and improve decision making. One of the main contributions of this research is in the defuzzification stage, adjusting the centroid method and treating each set individually. With this, the RPN values approximate to the conventional technique were obtained. Simulations were carried out to test and determine the system’s best structure. The system was validated in a textile company in southern Guanajuato. The results demonstrate that the system reliably represents how experts perform risk assessment.

MINING-VIRTUAL: A comprehensive virtual reality-based serious game for occupational health and safety training in underground mines

Mining is a multi-disciplinary engineering activity considered as having risks that are related to workers and equipment. The mitigation of these risks and preparedness for the possible risk factors are commonly based on traditional training that is nowadays enriched with new training materials, simulations and serious games. In this study, a detailed and realistic serious game —MINING-VIRTUAL— developed in Unity3D for computer and virtual reality environments is introduced. The game enables users to experience an underground coal mine in a virtual environment for training purposes. Hazard detection and knowledge about critical information about occupational health and safety are evaluated by interactions and questions within the game. Target groups of 30 participants from mining engineers and game developers were invited to test MINING-VIRTUAL, and the technology acceptance and usability aspects were evaluated by questionnaires. As a result, both mining engineers and game developers assessed the game as excellent based on system usability scores and agreed on the fact that the game has a considerably high technology acceptance level. Paired t-tests were performed to evaluate the effects of experience in using gaming technology and the frequency of gaming on technology acceptance. The evaluation revealed that the developed game could serve as an efficient tool in occupational health and safety training for the mining industry.

Characteristics, causes, and consequences of technical debt in the automation domain

Technical Debt (TD) is a significant concern in software development, particularly when interdisciplinary teams collaborate and interact. The goal of the study is to investigate TD causal chains and patterns in the industrial automation sector by analyzing 123 mechatronic TD incidents from 47 expert interviews across ten companies. Findings reveal that Requirements, Process, and Test TD are most common, while Build, Versioning, Manufacturing, Code, and Maintenance/Service TD are less frequent. Key causes include ”other priorities”, ”lack of time”, ”historically grown products”, ”lack of market analysis” and ”copy-paste-modify without revising tolerances.” The research identifies correlations between TD subtypes and causes/consequences in relation to company size, experts’ experience, and position, utilizing the Chi-square test and PrefixSpan algorithm. The study also maps the contagious character of TD using Neo4J graphical representation. This first in-depth analysis of TD causal chains in industrial automation contributes qualitatively to understanding TD patterns, helping researchers and practitioners assess TD contagiousness, comprehend its effects, prevent diffusion, and develop repayment strategies To the best of our knowledge, this study’s quantitative analysis approach provides the foundation that will enable future research identifying TD metrics and TD management in multidisciplinary engineering.

A SysML-centric integration framework for helicopter fuel system development

Data and model exchange between SysML (Systems Modeling Language) Modeling tools and other system development tools is a critical aspect of Model-Based Systems Engineering (MBSE). This paper introduces an application of the SysML-centric integration framework, which allows integrating multi-disciplinary engineering models into a SysML Modeling environment. A design practice of helicopter fuel system is then presented to illustrate how to combine the external simulation models within the SysML Models to explore the performance and verify corresponding requirements. In this case, FMI (Functional Mock-up Interface) based co-simulation creates a bridge between SysML Modeling tools and simulation tools in the SysML-centric integration framework. According to the practice, we believe it will significantly improve model consistency and traceability to provide early evaluation of concepts during conceptual design phase.

Multi-disciplinary engineering design of a high-speed nature-inspired unmanned aquatic vehicle

Recently, small unmanned vehicles have increased their technological importance and practical relevance in private and public interest maritime applications. However, due to this technology's novelty and early stages, complex challenges in engineering design remain unsolved. Therefore, the purpose of this article is to demonstrate the development of an innovative high-speed Unmanned Aquatic Vehicle (UAV) with the inclusion of robust and multi-objective optimization-based methods. This work implemented four robust optimization methods (e.g., efficient low drag generation, theoretical calculation, the production of hydrodynamic forces, and fluid-structure interaction) to design, components, performance, and material optimization. Furthermore, robust computational simulations and mathematical modelling were applied during the engineering design process. The main research findings show that the version of the UAV developed is optimized and able to operate in several working conditions in oceanic applications. Findings also complement previous related studies and offer novel technological alternatives for maritime applications and species detection in complex oceanic conditions. Finally, the aspects of theoretical significance and application value of the research are discussed in the paper.

Roadmap to inclusive curriculum: a step towards Multidisciplinary Engineering Education for holistic development

Abstract : One of the key aspects to measure the prosperity of any nation in this global economy can be its leadership in technology & innovation. Engineering is applied everywhere; from the design and development of novel products and processes to providing solutions to complex challenges. Engineering education is therefore of key significance to a growing economy. With a prime focus on improving qual i ty and providing hol i sti c development of learners, developments are taking place worldwide in Engineering education & research. The term 'learners' indicate students and has been used interchangeably in the entire script. Purpose: National Education Policy 2020 of the Government of India proposed reforms to the existing education framework of the country and emphasized on introducing multidisciplinary undergraduate programmes with multiple exit options. This study proposes an inclusive curriculum with different course types from multiple disciplines for anundergraduate engineering programme and articulates the relevance of the framework to foster holistic development. Research Methodology: The study incorporates a structured design approach where inputs from senior leaders of 60 Universities offering undergraduate programmes formed the basis of the preliminary work. The academic framework was designed under the regulations and guidelines of the statutory body for t echni ca l programmes. On succ essful implementation, a research instrument was administered to a cohort of learners of an undergraduate engineering programme, and the data collected was then analysed. Findings: From the findings, we infer that a multidisciplinary engineering programme would enhance research skills and enable the learners to selfmanage to a great extent along with developing their critical thinking skills. The results are statistically significant with p<0.05. Implications of the Study: This study would help Universities and Higher Education Institutions to explore the possibilities of provisioning courses from diversified disciplines in an Engineering curriculum to promote multi-disciplinarity. The findings from the study would be beneficial to the learners to realize the potential of multidisciplinary education and accordingly pursue their career aspirations. The studyprovides an insight into competencies to be developed through the framework of a four-year undergraduate engineering programme thereby enabling Industry practitioners to reorient the job roles that thrive in the future. Keywords: Multidisciplinary Education; academic curriculum; holistic education; Engineering Framework; Learners.

A Decision-making Method for Swarm Agents in Attack-defense Confrontation

The cooperative decision-making of swarm agents has attracted extensive attention from researchers due to its potential applications in multidisciplinary engineering problems. This paper studies a confrontation problem called asymmetric attack-defense confrontation (i.e., considering the difference in capability and quantity between agents and targets). The objective is to develop an effective self-organized swarm confrontation decision-making method. The decision-making process consists of task allocation decision and swarm motion decision. At each decision-making step, firstly, each agent forms a coalition with other agents autonomously by using a proposed hedonic coalition formation algorithm according to the attribute of targets. Thus, the agents assigned to the same target form a coalition, and swarm agents form several disjoint coalitions. Then, based on the allocated results, the agents are steered toward the corresponding target by a combat stimulus and a proposed selected interaction swarm algorithm. Finally, while the targets are within the agents’ attack radius, the agents execute the confrontation decision. Simulation results show the effectiveness of the designed method.

Education 4.0: Integrating Codes, Standards, and Regulations in the Chemical Engineering Curriculum

Education 4.0 is the framework to facilitate the development of skills and competencies of engineering students required for Industry 4.0 through the integration of Industry 4.0 applied concepts, networked approach, digitalization of higher education institutions (HEI), and online advancement of teaching and learning practices. In the chemical engineering curriculum of several HEIs, considerable progress in implementing this framework has been made by including computer-aided design tools, updating manufacturing technologies, using simulation and analysis of virtual models, and implementing data analytics in engineering courses and programs. Process and plant design courses such as Plant Design demand that undergraduate students leverage knowledge from core courses completed during first three years of their degree program by developing a plant's conceptual design. This course clearly sets a pathway to integrate Education 4.0 to Industry 4.0. All stakeholders of this course (students, teaching team, and clients) can progressively identify challenges and opportunities to optimize this integration. Many suggested improvements might require a vertical integration of new concepts in the chemical engineering curriculum, involving courses of different levels throughout the undergraduate curriculum. Nevertheless, we consider that immediate actions shall be taken by teaching teams and industry partners in courses such as Plant Design for students achieving the required competencies and skills before graduating from universities. For instance, running a successful multi-disciplinary engineering team for plant design in the industry will require undergraduate students to become familiar with codes, standards, and regulations. According to our industry partners, this lack of familiarization significantly affects the learning curve of junior engineers at work and shows a disconnection between what is learned at university and what is required in the workplace. To facilitate the transition of our students into the process design industry in the framework of Education 4.0-Industry 4.0, in this work, we describe and present the results of applying a strategy to tackle this challenge by (i) identifying the currently applicable codes, standards, and regulations in the process engineering industry for each technical deliverable (process flow diagram, piping and instrumentation diagram, line list, plot plan, design of equipment, risk management, and safety documents) of the course; (ii) designing and delivering workshops to describe and illustrate their applicability; and (iii) creating a written set of guidelines applicable to the course and the workplace.

Multi-Disciplinary Design Activity for Undergraduate and Graduate Engineering Students

This paper describes a project with common equipment that was adapted and offered to both an undergraduate and a graduate-level course with learning outcomes tailored specifically to each group of students. This project is an immersive, multi-disciplinary engineering design activity with a focus on materials, solid mechanics, and instrumentation. The activity incorporates aspects of fundamental engineering theory, virtual predictive simulation, as well as physical testing and data collection. All of this was done in the context of a material selection and failure analysis of a piece of furniture (cantilever chair) which is a simplistic and recognizable device by the students.
 The project focusses on structural analysis of the chair under a variety of loading conditions, coupled with a virtual simulation model using Finite Element Analysis (FEA). FEA is utilized to identify critical regions of the structure which are prone to failure. The complexity, constraints, and provided resources of the model varied, depending on the specific implementation of the course. Finally, a physical test apparatus was constructed and used to generate experimental responses that the students were able to use to calibrate their predictive model and theoretical hand calculations.
 This activity was created initially for in-person instruction but was adapted for remote delivery during the pandemic. Both qualitative and quantitative data collected from 2nd year and graduate students indicated that the activity was effective in improving several forms of knowledge acquisition. This paper will discuss in detail how a common project platform was adapted for the two academic levels with evidence of its efficacy