Industrial Design Engineering Research Articles

Improved marine predators algorithm for engineering design optimization problems

The Marine Predator Algorithm (MPA) has unique advantages as an important branch of population-based algorithms. However, it emerges more disadvantages gradually, such as traps to local optima, insufficient diversity, and premature convergence, when dealing with complex problems in practical industrial engineering design applications. In response to these limitations, this paper proposes a novel Improved Marine Predator Algorithm (IMPA). By introducing an adaptive weight adjustment strategy and a dynamic social learning mechanism, this study significantly improves the encounter frequency and efficiency between predators and preys in marine ecosystems. The performance of the IMPA was evaluated through benchmark functions, CEC2021 suite problems, and engineering design problems, including welded beam design, tension/compression spring design, pressure vessel design, and three-bar design. The results indicate that the IMPA has achieved significant success in the optimization process over other methods, exhibiting excellent performance in both solving optimal parameter solutions and optimizing objective function values. The IMPA performs well in terms of accuracy and robustness, which also proves its efficiency in successfully solving complex industrial engineering design problems.

Computer Aided Industrial Design Technology for Integrating Feature Point Coordinate Calculation in Toy Design

Computer Aided Industrial Design Technology for Integrating Feature Point Coordinate Calculation in Toy Design

Election Optimizer Algorithm: A New Meta-Heuristic Optimization Algorithm for Solving Industrial Engineering Design Problems

This paper introduces the election optimization algorithm (EOA), a meta-heuristic approach for engineering optimization problems. Inspired by the democratic electoral system, focusing on the presidential election, EOA emulates the complete election process to optimize solutions. By simulating the presidential election, EOA introduces a novel position-tracking strategy that expands the scope of effectively solvable problems, surpassing conventional human-based algorithms, specifically, the political optimizer. EOA incorporates explicit behaviors observed during elections, including the party nomination and presidential election. During the party nomination, the search space is broadened to avoid local optima by integrating diverse strategies and suggestions from within the party. In the presidential election, adequate population diversity is maintained in later stages through further campaigning between elite candidates elected within the party. To establish a benchmark for comparison, EOA is rigorously assessed against several renowned and widely recognized algorithms in the field of optimization. EOA demonstrates superior performance in terms of average values and standard deviations across the twenty-three standard test functions and CEC2019. Through rigorous statistical analysis using the Wilcoxon rank-sum test at a significance level of 0.05, experimental results indicate that EOA consistently delivers high-quality solutions compared to the other benchmark algorithms. Moreover, the practical applicability of EOA is assessed by solving six complex engineering design problems, demonstrating its effectiveness in real-world scenarios.

Preparing Future Designers for their Role in Co‐Design: Student Insights on Learning Co‐Design

AbstractThe state‐of‐the‐art literature indicates an increasing need for co‐design education as it is imperative to equip future designers with the co‐designing mindset. This derives from the significance of involving ‘people with lived experience’ in co‐design processes to better meet their needs. However, the traditional design education system seems to include mostly individual designing skills, causing a lack of skills in design students to facilitate the active participation of people in co‐design. This paper reports on a case study carried out in a third‐year Bachelor industrial design engineering course with design students (n = 32) and design educators (n = 4) to find an effective and efficient way of preparing future designers for their role in co‐design and to gain insights into design students' experience with learning about co‐design. As an instructional method, a co‐design workshop including the game‐play, game‐modding and game‐design approaches is introduced. The obstacles and confusion of the design students regarding co‐design and co‐design education, which they have documented throughout the year on their personalised logbooks, are explained to eliminate them in the future for smoother incorporation of co‐design education into design education curricula. Lastly, for future designers' mindfulness of co‐design and their role as facilitators suggestions are provided such as accreditation of curriculum activities regarding co‐design education.

Boosting aquila optimizer by marine predators algorithm for combinatorial optimization

Abstract In this study, an improved version of aquila optimizer (AO) known as EHAOMPA has been developed by using the marine predators algorithm (MPA). MPA is a recent and well-behaved optimizer with a unique memory saving and fish aggregating devices mechanism. At the same time, it suffers from various defects such as inadequate global search, sluggish convergence, and stagnation of local optima. However, AO has contented robust global exploration capability, fast convergence speed, and high search efficiency. Thus, the proposed EHAOMPA aims to complement the shortcomings of AO and MPA while bringing new features. Specifically, the representative-based hunting technique is incorporated into the exploration stage to enhance population diversity. At the same time, random opposition-based learning is introduced into the exploitation stage to prevent the optimizer from sticking to local optima. This study tests the performance of EHAOMPA’s on 23 standard mathematical benchmark functions, 29 complex test functions from the CEC2017 test suite, six constrained industrial engineering design problems, and a convolutional neural network hyperparameter (CNN-hyperparameter) optimization for Corona Virus Disease 19 (COVID-19) computed tomography-image detection problem. EHAOMPA is compared with four existing optimization algorithm types, achieving the best performance on both numerical and practical issues. Compared with other methods, the test function results demonstrate that EHAOMPA exhibits a more potent global search capability, a higher convergence rate, increased accuracy, and an improved ability to avoid local optima. The excellent experimental results in practical problems indicate that the developed EHAOMPA has great potential in solving real-world optimization problems. The combination of multiple strategies can effectively improve the performance of the algorithm. The source code of the EHAOMPA is publicly available at https://github.com/WangShuang92/EHAOMPA.

A Practical Approach on the Design of an Interdisciplinary Postgraduate Program: The Case of the “Unmanned Autonomous and Remote-Control Systems” Postgraduate Program

There is a long-standing collaboration between the Department of Industrial Design and Production Engineering of the School of Engineering of the University of West Attica and the Department of Naval Studies of the Hellenic Naval Academy in the fields of research and applications. This collaboration has already led to the creation of a common interest direction in an existing Postgraduate Program. Naturally, the common interest in the subject of Unmanned Vehicles led to relevant discussions. These discussions matured quickly and led to a structured form and a specific goal: the design, production and operation of an interdisciplinary/joint Postgraduate Program. This paper presents the development process of the Curriculum for the Program and the basic assumptions about it that emerged from the combination of a review of the relevant literature and the identification of needs in the Greek and European markets.

To the Problem of Improving the Education of Industrial Design Specialists in Ukraine

New world challenges increasingly require designers to solve social problems of humanity, so designers are entrusted with increasingly complex and impressive tasks. However, the modern system of design education does not always prepare students for these tasks. This article analyses how the educational process of training designers in European countries is built.
 The realities of the development of industrial design in Spain and Ukraine are given, with an immersion in the historical prerequisites for the formation of this field of activity. The development of industrial design in countries is demonstrated, taking into account historical, economic and political prerequisites. The training programs were considered and the content of the training of industrial design engineers in Spain and the content of the training of industrial design specialists in Ukraine were compared. In the process of studying the training programs, significant differences in the understanding of the field of activity and the content of the training of industrial designers in Ukraine and Spain were revealed. This fact is reflected in the demand of students to study in the relevant training programs.
 In order to demonstrate the shortage of industrial design engineers in the production sector of industry, the labour market requirements for these specialists in Ukraine are given. According to the results of the analysis, the inconsistency of the training content of industrial designers with the requirements of the labour market was demonstrated both at the legislative level and at the level of employers’ requirements
 In order to meet the needs of industry and bring Ukrainian education to European requirements, it is proposed to introduce a new interdisciplinary educational program for training engineers in industrial design in Ukraine, taking into account the experience of the Spanish School of Industrial Design, which has incorporated the best English and European practices.
 It should contain two main focuses of training: engineering and aesthetics. At the same time, business awareness and environmental awareness when making decisions should become a mandatory component of the training of industrial design engineers.

The Product’s Great Journey: A Multi-triangular Agile Approach

Within a constantly competitive scenario, productive organizations have been looking for alternatives to improve all their internal processes in order to try to stay alive among competitors, in terms of economic, environmental and social sustainability. Thus, it is no longer common for someone or some isolated sector of a company to make a decision on their own. The decisions became collegiate. However, some sectors end up having more relevant arguments at each stage of a product’s great journey. At every moment of the process, from conceptualization (cradle) to disposal (grave or reuse), some departments become protagonists, while others become supporting actors. In this approach, the great journey of a product could be divided into “triangle of forces” structured by stakeholder representatives. The objective of this specific paper is to evaluate the activities of the conceptualization phase of a product that is observed as the first of these triangles whose vertices are formed by representatives from the Marketing, Industrial Design and Product Engineering areas. The proposed triangle model aims to organize the decision-making process during the development of a new product. Assigning leadership responsibilities and support functions to each sector at each stage of the project. This proposal would transform the great product journey into a star formed by these triangles of power, creating an agile and interactive environment of simultaneous engineering. As a result, this study presents a proposal of fundamental activities involved in the initial triangle of the task force conceptualization phase and the interrelationships among the areas of Marketing, Industrial Design and Product Engineering that happen along these processes.

What engineers will Ukraine need tomorrow? Experience of Spain in the formation of the content of the training of industrial design engineers

Purpose. Identify discrepancies and propose ways to eliminate them between the needs of the Ukrainian economy reflected in the requirements of employers, and in the content of the training of industrial design engineers in Ukraine using the European experience of the Spanish school. The methods. Using the method of analysis and synthesis, we made an analysis of the labor market and the content of the training of engineers applying for the position of industrial designer, and also studied the European experience of forming the content of the training of industrial designers. The convergent process of forming judgments is used to find and formulate ways to eliminate discrepancies between the needs of the labor market and the content of specialist training. Findings. The problem is that there is a need to rethink the training of industrial designers. The analysis showed the inappropriateness of the training of industrial design specialists in Ukraine within the framework of the field 02 Culture and art. Today and tomorrow, Ukrainian enterprises need specialists in the engineering profile who are educated in the society of morality and behavior, which are adequate to modern relations between man and the surrounding natural environment under the conditions of sustainable development and who are ready to take responsibility at every stage of the product life cycle and carry out business activities. Therefore, the content of preparation of educational programs should take into account all the needs of the Ukrainian economy. In order to recognize Ukrainian specialists as full members of European society, it is also necessary to take into account the experience of European countries. The originality. Using the convergent process of forming judgments, the peculiarities of the formation of OPs for the training of engineers in industrial design were revealed. The identified features are reflected in the proposed list of competencies of the educational program for training engineers in industrial design, which take into account the needs of the Ukrainian economy and the experience of the Spanish school of industrial design, which has incorporated the best English and European practices. Practical implementation. The proposed list of competencies will allow the formation of educational training programs that are relevant for today.

Enumeration and Identification of Unique 3D Spatial Topologies of Interconnected Engineering Systems Using Spatial Graphs

Abstract Systematic enumeration and identification of unique 3D spatial topologies (STs) of complex engineering systems (such as automotive cooling systems, electric power trains, satellites, and aero-engines) are essential to navigation of these expansive design spaces with the goal of identifying new spatial configurations that can satisfy challenging system requirements. However, efficient navigation through discrete 3D ST options is a very challenging problem due to its combinatorial nature and can quickly exceed human cognitive abilities at even moderate complexity levels. This article presents a new, efficient, and scalable design framework that leverages mathematical spatial graph theory to represent, enumerate, and identify distinctive 3D topological classes for a generic 3D engineering system, given its system architecture (SA)—its components and their interconnections. First, spatial graph diagrams (SGDs) are generated for a given SA from zero to a specified maximum number of interconnect crossings. Then, corresponding Yamada polynomials for all the planar SGDs are generated. SGDs are categorized into topological classes, each of which shares a unique Yamada polynomial. Finally, within each topological class, 3D geometric models are generated using the SGDs having different numbers of interconnect crossings. Selected case studies are presented to illustrate the different features of our proposed framework, including an industrial engineering design application: ST enumeration of a 3D automotive fuel cell cooling system (AFCS). Design guidelines are also provided for practicing engineers to aid the application of this framework to different types of real-world problems such as configuration design and spatial packaging optimization.

A modified smell agent optimization for global optimization and industrial engineering design problems

Abstract This paper introduces an Improved Smell Agent Optimization Algorithm (mSAO), a new and enhanced metaheuristic designed to tackle complex engineering optimization issues by overcoming the shortcomings of the recently introduced Smell Agent Optimization Algorithm. The proposed mSAO incorporates the jellyfish swarm active–passive mechanism and novel random operator in the elementary SAO. The objective of modification is to improve the global convergence speed, exploration–exploitation behaviour, and performance of SAO, as well as provide a problem-free method of global optimization. For numerical validation, the mSAO is examined using 29 IEEE benchmarks with varying degrees of dimensionality, and the findings are contrasted with those of its basic version and numerous renowned recently developed metaheuristics. To measure the viability of the mSAO algorithm for real-world applications, the algorithm was employed to solve to resolve eight challenges drawn from real-world scenarios including cantilever beam design, multi-product batch plant, industrial refrigeration system, pressure vessel design, speed reducer design, tension/compression spring, and three-bar truss problem. The computational analysis demonstrates the robustness of mSAO relatively in finding optimal solutions for mechanical, civil, and industrial design problems. Experimental results show that the suggested modifications lead to an improvement in solution quality by 10–20% of basic SAO while solving constraint benchmarks and engineering problems. Additionally, it contributes to avoiding local optimal stuck, and premature convergence limitations of SAO and simultaneously.

The EMI content lecturer as a street-level bureaucrat: discretionary actions and coping mechanisms in micro-level language policy-as-produced

ABSTRACT The field of English as a Medium-of-Instruction (EMI) research in tertiary education is undergoing a context-specific turn, focusing attention on how the official medium of instruction interacts with local languages, as well as the multi-faceted interplay between national and/or institutional language policies and classroom practice. This article reports on findings from linguistic ethnographic fieldwork at a Belgian higher education institution: for two semesters, the interactions between a lecturer and his students in an English-medium Industrial Design Engineering course were observed. The lecturer’s micro-level didactic choices are studied through the lens of Lipsky’s Street-Level Bureaucracy. This reveals a systematic pattern of on-the-ground language policy construction which is evidenced in classroom practice. While the findings of this study problematise the pillarized ‘either/or’ language choices that continue to dominate a polarised language policy debate, they equally underline the micro-level agency of the disciplinary EMI instructors in shaping public policy. For EMI-contexts more generally, our analysis suggests the viability and sociolinguistic relevance of an enactment-of-policy-in-interaction perspective which is equally a matter of disciplinary induction. The study of ‘coping mechanisms’ thus becomes an arena for policy development and teacher training.

Romatoid Artrit Hastaları için Zihin Haritası Yöntemi ile Bardak Tasarım Kriterlerinin Geliştirilmesi

Rheumatoid arthritis, which is primarily seen in small joints (hand joints, wrist and foot joints) and elbows, causes chronic (more than 6 weeks) joint damage. It is an autoimmune inflammatory joint disease that can occur in many organs and systems. When we look at the female / male ratio of this disease, which is seen at a rate of 1% in the society, it appears as 3/1. Although the reason for its emergence is unknown; it is stated that biological and hereditary factors are the main cause. In addition, it is claimed that psychological and social factors also play a role in the onset and course of the disease. RA causes negative situations in both physical and psychosocial life of the person. Symptoms can result in restriction of daily activities, decreased effectiveness in work life, problems in sexual life, social isolation, dependence on others. As a result of these, a decrease in the self-esteem of the individual, changes in body image, depression, anxiety and anger feelings may develop. One of the situations in which daily activities are restricted in people with RA is the restriction or complete termination of the use of daily products. Rheumatoid arthritis patients with the daily products were investigated and it was determined that one of the most problematic products to use was glasses. It was aimed to solve the problems identified in glass designs with industrial design methods. In this direction, the design criteria and mind maps presented by 50 students who successfully completed the 'Design Theory and Methods' course at Erciyes University, Department of Industrial Design Engineering were examined. This study, which is presented at the intersection of medical and industrial design, is important in terms of creating an interdisciplinary study area.

EMI and its sociolinguistic entanglement with local languages

Abstract Against the backdrop of inter-institutional competition and transnational ambitions, the prevalence of English-medium instruction (EMI) programs in higher education and their relative distribution across various national, regional, and institutional contexts is rapidly growing. When studying the increasingly globalized phenomenon of EMI, there is a tendency to adopt macro-pedagogical perspectives, with comparatively little attention being devoted to disciplinary differences which may warrant intra-institutional differentiation through situationally adaptable approaches to EMI policy and implementation strategies. The present study attempts to further enhance and nuance our understanding of the influence of disciplinary knowledge structures and literacies on lecturers’ and students’ linguistic needs in EMI courses. This article reports on linguistic ethnographic fieldwork at a Belgian higher education institution in which graduate students in international bio-science engineering and industrial design engineering programs were observed during the 2021–2022 academic year. Differences in disciplinary knowledge structures and literacies are explored through means of survey, interview, and classroom observation data. Results corroborate earlier findings on the interplay between disciplinary knowledge structures and attitudes towards EMI. Additionally, the data illustrate how the active inclusion of local languages alongside English can be considered disciplinarily relevant in certain programs.

Opposition-based Laplacian distribution with Prairie Dog Optimization method for industrial engineering design problems

Prairie Dog Optimization is a population-based optimization method that uses the behavior of prairie dogs to find the optimal solution. This paper proposes a novel optimization method, called the Opposition-based Laplacian Distribution with Prairie Dog Optimization (OPLD-PDO), for solving industrial engineering design problems. The OPLD-PDO method combines the concepts of opposition-based Laplacian distribution and Prairie Dog Optimization to find near-optimal solutions. This causes faster convergence to the optimal solution and reduces the chances of getting stuck in a local minimum. The OPLD-PDO method was tested on several benchmark problems to validate its performance. The results were compared with other methods, and the OPLD-PDO method was superior regarding solution quality. The results of this study demonstrate the potential of the OPLD-PDO method as a useful tool for solving industrial engineering design problems and photovoltaic (PV) solar problems.

Research on the Application of Computer-Aided Industrial Design and 3D Printing Technology: A Comprehensive Perspective Analysis

With the continuous development and popularization of computer-aided industrial design technology and 3D printing technology, the integration of the two is also receiving more and more attention. Starting from the basic principles and development history of computer-aided industrial design technology and 3D printing technology, this paper introduces the advantages and current situation of the integration of the two, and focuses on exploring the integration of computer-aided industrial design and 3D printing technology in product design, process analysis, and manufacturing process optimization. Finally, the development trend and future prospects of integration application are summarized.

Evaluation of Work Posture When Assembling a Study Chair in Industrial Engineering Design Practicum 2

In a study chair assembly workstation facility at Industrial Engineering Design Practicum 2 (IEDP2), practicum students experienced difficulties, including rotating fixtures, separating bolt and nut components, and changing assembly positions. Kinetics analysis through evaluation of work postures is needed to redesign assembly stations. This paper compares the before and after redesigning of a study chair assembly workstation in IEDP2 based on work posture with kinetic analysis through 3D motion with Kinect and LightBuzz Vitruvius sensors. As many as 20 students were involved, including practicum assistant students and practicum students at the Laboratory of Product Planning and Design (LPPD). Comparison of assembly workstation redesigns was measured using fair and maximum moments, testing through paired t-tests. The significant differences between before and after redesigning a study chair assembly at workstation facilities were statistical (p < 0.001). Kinetic analysis showed an increase in improving students' working posture by redesigning workstation facilities, showing a different workload on the upper limbs when assembling.

Dynamic Chaotic Opposition-Based Learning-Driven Hybrid Aquila Optimizer and Artificial Rabbits Optimization Algorithm: Framework and Applications

Aquila Optimizer (AO) and Artificial Rabbits Optimization (ARO) are two recently developed meta-heuristic optimization algorithms. Although AO has powerful exploration capability, it still suffers from poor solution accuracy and premature convergence when addressing some complex cases due to the insufficient exploitation phase. In contrast, ARO possesses very competitive exploitation potential, but its exploration ability needs to be more satisfactory. To ameliorate the above-mentioned limitations in a single algorithm and achieve better overall optimization performance, this paper proposes a novel chaotic opposition-based learning-driven hybrid AO and ARO algorithm called CHAOARO. Firstly, the global exploration phase of AO is combined with the local exploitation phase of ARO to maintain the respective valuable search capabilities. Then, an adaptive switching mechanism (ASM) is designed to better balance the exploration and exploitation procedures. Finally, we introduce the chaotic opposition-based learning (COBL) strategy to avoid the algorithm fall into the local optima. To comprehensively verify the effectiveness and superiority of the proposed work, CHAOARO is compared with the original AO, ARO, and several state-of-the-art algorithms on 23 classical benchmark functions and the IEEE CEC2019 test suite. Systematic comparisons demonstrate that CHAOARO can significantly outperform other competitor methods in terms of solution accuracy, convergence speed, and robustness. Furthermore, the promising prospect of CHAOARO in real-world applications is highlighted by resolving five industrial engineering design problems and photovoltaic (PV) model parameter identification problem.

Cultivating Cooperative Relationships: Identifying Learning Gaps When Teaching Students Systems Thinking Biomimicry.

The methodology of biomimicry design thinking is based on and builds upon the overarching patterns that all life abides by. "Cultivating cooperative relationships" within an ecosystem is one such pattern we as humans can learn from to nurture our own mutualistic and symbiotic relationships. While form and process translations from biology to design have proven accessible by students learning biomimicry, the realm of translating biological functions in a systematic approach has proven to be more difficult. This study examines how higher education students can approach the gap that many companies in transition are struggling with today; that of thinking within the closed loops of their own ecosystem, to do good without damaging the system itself. Design students should be able to assess and advise on product design choices within such systems after graduation. We know when tackling a design challenge, teams have difficulties sifting through the mass of information they encounter, and many obstacles are encountered by students and their professional clients when trying to implement systems thinking into their design process. While biomimicry offers guidelines and methodology, there is insufficient research on complex, systems-level problem solving that systems thinking biomimicry requires. This study looks at factors found in course exercises, through student surveys and interviews that helped (novice) professionals initiate systems thinking methods as part of their strategy. The steps found in this research show characteristics from student responses and matching educational steps which enabled them to develop their own approach to challenges in a systems thinking manner. Experiences from the 2022 cohort of the semester "Design with Nature" within the Industrial Design Engineering program at The Hague University of Applied Sciences in the Netherlands have shown that the mixing and matching of connected biological design strategies to understand integrating functions and relationships within a human system is a promising first step.

Multivariate Analysis of Co-creation Activities in University Education

<p style="text-align:justify">This paper investigates the viewpoints and perspectives of 179 undergraduate students engaged in a co-creation project regarding their anticipated progress, exploring, simultaneously, the affecting factors. The students attended the physics course in the Department of Industrial Design and Production Engineering at the University of West Attica, Greece. The investigation is implemented through a questionnaire that appraises the students' co-creation expectations in association with collected demographic data via twenty-two close-ended questions (Q1-Q22). Several statistical data sets are presented, including descriptive and correlation statistics and principal component and exploratory factor analyses. The majority of the replies are provided by male participants in their first year of study, with an average age of between 18 and 19. The correlation coefficient between the questions ranges from -.04 to.73, with the maximum occurring between the questions Q19 and Q20. Factor analysis justified by KMO (.862) and Bartlett’s sphericity (1749.843, p= .000) tests indicates five principal components within the following factors determining the undergraduate co-creation activities: responsible behaviour, feedback, helping, tolerance, and personal interaction. The above findings may contribute to the implementation of students’ co-creation as they are valuable tools for the design and pre-requisites for a successful implementation.</p>