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Sustainability in Industrial Design Engineering for Industry 4.0

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 10657

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Special Issue Editor

Prof. Yu-Hung Chien

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Guest Editor

Department of Technology Application and Human Resource Development, National Taiwan Normal University, Taipei 106
Interests: interior Design; computer-aided design; principles of shaping; introduction to design; products design; 3D modeling

Special Issue Information

Dear Colleagues,

The world has gone through industrial revolutions 1.0 to 3.0. Each revolution has driven the development of industry due to major technological inventions, and at the same time changed the social and economic structure. In the era of Industry 4.0, technologies such as cyberphysical systems, cloud computing, automated production, cognitive computing, Internet of Things (IoT), and big data, and flexibility and individualized production help companies to stay competitive. Industry 4.0 is in full swing. In industrial design engineering, the two main activities of design and manufacturing have to further develop in response to the changes of the industrial revolution. In addition, industrial design engineering at the age of Industry 4.0 also requires a new paradigm that deals with the sustainability of product and service, user experience, and human satisfaction. This Special Issue will address recent advances in industrial design engineering in the age of Industry 4.0. Original papers with an explicit relevance to issues of industrial design engineering—either theoretical or practical—are welcome, as are state-of-the-art reviews, new perspectives, and outlooks on future research directions.

Prof. Yu-Hung Chien
Guest Editor

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Keywords

advanced technology in industrial design engineering
product, engineering, and industrial design
design in engineering subject areas
industrial design engineering for sustainability
design management
design support tools
design innovation
human behavior and industrial design engineering
design methods
sociotechnical issues in industrial design engineering
education for industrial design engineering
research methods for industrial design engineering
ergonomics in industrial design engineering
others

Published Papers (4 papers)

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Research

14 pages, 567 KiB

Open AccessArticle

Combining PCA-AHP Combination Weighting to Prioritize Design Elements of Intelligent Wearable Masks

by Zibin Chen, Xi Zhang and Jaehwan Lee

Sustainability 2023, 15(3), 1888; https://0-doi-org.brum.beds.ac.uk/10.3390/su15031888 - 18 Jan 2023

Cited by 3 | Viewed by 1811

Abstract

Intelligent wearable masks are gaining increasing interest due to COVID-19 and the problems and limitations of existing masks. This paper prioritizes the design elements of personal protective equipment-intelligent wearable masks from the perspective of the product design domain. Using principal component analysis (PCA), the principal components of the design elements were selected first in this paper. Using the combined weights (PCA-AHP) method, the intelligent wearable masks’ prioritized design elements at each level were determined. The highest priority among the primary elements is comfort (0.3422), with the adjustable ear strap (0.1870) receiving the highest priority among the primary elements of comfort. The highest priority in functionality (0.2733) is anti-respiratory droplets/air purification (0.1097), the highest priority in usability (0.1686) is the easy removal and replacement of filters (0.0761), the highest priority in the aesthetic design (0.1192) is styling (0.0509), and the highest priority in material (0.0967) is flexible fabric material (0.0355). Finally, the six prioritized design elements were evaluated using fuzzy comprehensive evaluation (FCE), and overall, 76% of the experts considered them “appropriate” or “very appropriate” and 18% considered them “fair.” Therefore, this study’s six most prioritized design elements proposed for intelligent wearable masks can satisfy users’ needs. Full article

(This article belongs to the Special Issue Sustainability in Industrial Design Engineering for Industry 4.0)

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18 pages, 3436 KiB

Open AccessArticle

Sustainable Recognition Methods of Modeling Design Features of Light and Micro Vehicle-Mounted UAV: Based on Support Vector Regression and Kano Model

by Hao Yang, Yunxiang Huo, Ruoyu Jia, Feng Sha, Naiqi Hu, Linglan Yu and Yueran Wang

Sustainability 2022, 14(13), 8210; https://0-doi-org.brum.beds.ac.uk/10.3390/su14138210 - 05 Jul 2022

Cited by 8 | Viewed by 1578

Abstract

In the era of Industry 4.0, intelligent algorithms provide an effective way to make design methods more sustainable through mining people’s demands continuously, especially in the field of evaluating and predicting the user preferences of phasic or interim design schemes. Vehicle-mounted unmanned aerial vehicles (UAVs) are of significance in mobility experience and traffic surveys. However, as a new type of product, UAVs lack general rules in modeling design and the process of development decision making presents some fuzzy characteristics, which make the evolution and iteration of modeling design more complex. Based on the theories of Kansei Engineering, this study utilized support vector regression (SVR) to establish a correlation model between design factors and preference degree. Because the perceptual evaluation knowledge is fuzzy and uncertain, the paper applied cross-validation and grid search methods to find the optimal parameters. The parameters of the SVR model were adjusted to meet the need for stable learning and for endurance of the noise from subjective experience data to improve the prediction effect and generalization ability. In addition, by means of the Kano model, the customers’ cognition of demand types was quantified to obtain the prioritization of UAV modeling design elements, as well as to compare with the preference scores to validate the feasibility of this research. It was found that the SVR model proposed in the study could effectively predict user preference (R² = 0.763, RMSE = 0.057). For the UAVs with a higher preference score, the modeling characteristics were consistent with the attractive, one-dimensional or must-be quality elements in the results of the Kano model, which verified the reliability of the study. The conclusion is expected to provide a sustainable design method for vehicle-mounted UAVs commonly used in citizen travel and outdoor activities. Full article

(This article belongs to the Special Issue Sustainability in Industrial Design Engineering for Industry 4.0)

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17 pages, 2194 KiB

Open AccessEditor’s ChoiceArticle

The Priority Given to Sustainability by Industrial Designers within an Industry 4.0 Paradigm

by Blair Kuys, Christoph Koch and Gianni Renda

Sustainability 2022, 14(1), 76; https://0-doi-org.brum.beds.ac.uk/10.3390/su14010076 - 22 Dec 2021

Cited by 10 | Viewed by 3541

Abstract

Industrial design is intrinsically linked to manufacturing; however, what is required of industrial design to adapt to new changes brought on by Industry 4.0 in manufacturing is unknown. Current literature gives little insight into how industrial designers need to evolve to the current developments in manufacturing to remain value drivers in an Industry 4.0 paradigm. There is minimal research describing the link between industrial design, Industry 4.0 and the effect this will have on sustainability. We conducted an extensive survey of 190 respondents from 53 countries to establish the present state of industrial design practice globally and to better understand the priority sustainability is given by practicing industrial designers. Qualitative data showed a desire for improved sustainable processes; however, quantitative data contradicted this, showing “sustainability” as one of the lowest ranked areas of importance in design practice for industrial designers. While sustainability—especially in manufacturing—demands more prominent change as industrial design adapts to an Industry 4.0 manufacturing paradigm, it seems that junior industrial designers do not currently see this as a priority. Full article

(This article belongs to the Special Issue Sustainability in Industrial Design Engineering for Industry 4.0)

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20 pages, 6018 KiB

Open AccessArticle

The Impacts of Design Heuristics on Concept Generation for a COVID-19 Brief

by Xiaoneng Jin, Hua Dong and Mark Evans

Sustainability 2021, 13(11), 6103; https://0-doi-org.brum.beds.ac.uk/10.3390/su13116103 - 28 May 2021

Cited by 3 | Viewed by 2277

Abstract

Design heuristics (DHS) as a tool can help boost designers’ creativity in early conceptual design phases. We have developed a set of DHS for digital innovation (DHS10). There are numerous studies on DHS impacts/outcomes in the recent years. However, little research has been conducted to identify whether DHS has lasting benefits on designers’ ideation performance. This paper explores whether DHS10 can help designers achieve more creative ideas based on different design briefs, and if DHS has lasting impacts on or benefits for students. An empirical study was conducted with two groups (i.e., 32 students who learned DHS10 five weeks ago, and 24 students who studied DHS10 instantly). They were asked to address an open-ended design brief on COVID-19 and generate as many innovative ideas as possible. The results suggest DHS has impacts on students who learned DHS just now and five weeks ago. The effect is stronger on those who just learned DHS10. We suggest that DHS10 be provided for ideation as it provides texts and visual stimuli for designers. DHS10 also has the potential to help students understand digital innovation and generate ideas accordingly. Full article

(This article belongs to the Special Issue Sustainability in Industrial Design Engineering for Industry 4.0)

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