Product Design Process Research Articles

Sensors capabilities as a creativity tool for engineering product design

Smart and connected physical products enable numerous novel value creations based on embedded sensor data. However, during the product design process, it appears that these value-creation opportunities are not sufficiently explored. To address this gap, a general and accessible ideation tool is proposed to structure a systematic exploration. The tool has been developed from the data sheets of a large number of various embedded sensors. A non-exhaustive list of 14 main sensor capabilities was thus structured to form the core of the tool. During the creative phases of product design, these capabilities are combined with a convenient set of inputs to support the generation of value-creation concepts. A focus group to evaluate the tool was carried out with a medium-sized manufacturer of connected shared city bikes. Expert product designers generated concepts with and without the tool. The results of the experiment suggest that the tool enables the generation of concepts that are more novel and of better quality in comparison to traditional ideation approaches. In addition, participants reported a high level of appreciation for the tool. They also noted a high level of creative exploration and collaboration facilitated by the tool.

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

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

Optimal Sustainable Manufacturing for Product Family Architecture in Intelligent Manufacturing: A Hierarchical Joint Optimization Approach

As consumers and governments prioritize cost-effectiveness and ecological sustainability, the limitations of traditional manufacturing paradigms become apparent in the context of constrained resources. The adverse effects of these paradigms on the environment and society hinder the achievement of a sustainable product life cycle. Intelligent manufacturing processes offer a solution by efficiently gathering meaningful data, such as usage and product recycling information, from previous product generations to enhance product design and subsequent sustainable manufacturing processes (SMPs). Modular product family architecture (PFA) design holds promise in promoting product sustainability and addressing diverse consumer needs. PFA design and SMPs are inherently interconnected within intelligent manufacturing frameworks. This paper aims to integrate the decision-making processes underlying PFA with SMPs. We model integrated PFA and SMP decisions as a Stackelberg game, which involves hierarchical joint optimization (HJO) for assessing product modularity and sustainable manufacturing fulfillment. We develop a bilevel 0–1 integer nonlinear programming model to represent the HJO decision-making process and propose a nested genetic algorithm (NGA) to solve the HJO problem. A case study with a laptop is conducted to validate the feasibility and potential of the proposed HJO model for joint optimization problems in PFA design and SMPs.

Process design and economic evaluation for methane and electricity production from Agave bagasse using different pretreatments

Agave bagasse is an agricultural residue that has the potential to be used as feedstock biorefineries. However, its complex structure requires a pretreatment step to facilitate the accessibility to carbohydrates for its subsequent conversion. In this study, the capital and operative expenses (CAPEX and OPEX) were simulated for industrial plants processing 500 ton/d of Agave bagasse using different pretreatment platforms for methane production and power generation on experimental data. The scenarios consisted of i) biological, ii) enzymatic, iii) dilute acid, and iv) steam explosion pretreatments and a case-based scenario without pretreatment. All these scenarios included milling, pretreatment, anaerobic digestion, and cogeneration stages. The results showed that those pretreatments carried out under soft conditions (biological and enzymatic) decreased between 2.1 and 2.8 times CAPEX compared to the highest value obtained in the diluted acid and case-based scenarios. The steam explosion, a pretreatment carried out under severe conditions, was less effective reducing CAPEX by only 1.2 times compared to the highest value. Furthermore, compared to the case-base scenario, only the biological pretreatment reduced the OPEX by a factor of 2, whereas the other pretreatments resulted in OPEX that were 2.0 to 3.5 times higher. Among the utilities (cooling water, steam generation, and energy) the steam generation contributed 47% to 76% of the total OPEX. The energy produced (kW⋅h/yr) was approximately twice the energy consumed for all scenarios. A sensitivity analysis demonstrated the robustness of the platforms since fluctuations in the prices of feedstock and raw materials did not impact the total production cost of methane, except for biological and enzymatic pretreatments. For all platforms, the solid loading was the process parameter with the highest impact on the production cost of methane. Overall, the study showed that biological and enzymatic pretreatments had the best economic performance. However, low substrate conversion and the high cost of enzymes and equipment, respectively, remained the main challenges to address in future research.

Development of Buddhist Cultural Creation based on Cultural Semiotics Theory

Cultural semiotics, as a unique theoretical framework, provides a profound way of thinking for the dissemination and interpretation of culture. This article takes the Dabao'en Temple in Nanjing as an example and explores its application in cultural and creative development from the perspective of Buddhist cultural semiotics theory. As a representative heritage of Chinese Buddhist culture, Nanjing Dabao'en Temple contains rich cultural symbols such as religion, history, and art, which is of great significance for cultural and creative development. Firstly, the research value of cultural semiotics in the development of Buddhist cultural creation was explored. Secondly, it explores how the elements in Da Bao En Temple, as cultural symbols, can be reconstructed in modern society to meet the aesthetic and needs of contemporary people. Through the artistic transformation of cultural symbols and other means, Da Bao En Temple has been able to radiate new vitality in cultural and creative products. In addition, this article also analyzes the strategies used in the design process of Da Bao En Temple's cultural and creative products. Through in-depth research, it can not only help Dabao'en Temple's cultural and creative products better achieve cultural dissemination, but also provide useful reference for the development of other similar cultural heritage. In summary, this article explores how cultural symbols can radiate new vitality in contemporary times by studying the application of cultural and creative development based on the theory of Buddhist cultural semiotics in the Dabaoen Temple in Nanjing. This not only helps to promote cultural inheritance, but also provides useful references for the sustainable development of the cultural and creative industry.

Framing under power asymmetries: A cross-level examination of the early-stage product design process

Framing under power asymmetries: A cross-level examination of the early-stage product design process

Inclusive Design Capabilities of Diploma-Level Industrial Design Students: An Empirical Investigation

This research delves into assessing diploma-level industrial design students’ proficiency in employing design thinking in their projects in Malaysia. The study addresses the difference between practical skills and design thinking, comprehensively evaluating the students’ capabilities. Malaysia’s industrial design diploma program is designed to equip students with the requisite skills and knowledge for a successful career, emphasising creating functional and aesthetically pleasing products that enhance lives. The research seeks to gain insights into the student’s ability to apply design thinking principles throughout the product design process, mainly focusing on their comprehension and implementation at each stage. The study involved observing students working on a project themed “Redefining Local Culture,” which aimed to breathe new life into local traditions through design. The research also incorporated industry mentorship to enhance the student’s practical application of design thinking, highlighting the significance of integrating industry insights into the curriculum. The findings underscore the importance of integrating design processes and design thinking into the curriculum to produce well-prepared graduates for the demands of the design industry. The study proposes curriculum enhancements that focus on aligning academic knowledge with practical application, ultimately aiming to bridge the gap and better prepare diploma students for the industrial design sector in Malaysia.

Optimization of product design process in cloud manufacturing system based on swarm intelligence

ABSTRACT Currently, manufacturing industries in many countries are grappling with an imbalance in the supply and demand of manufacturing resources, encompassing resource scarcity and idleness, as well as insufficient and surplus manufacturing capabilities. To address this issue, cloud manufacturing has emerged, integrating the Internet of Things, cloud computing, and advanced manufacturing technologies. This fusion enables the on-demand allocation of manufacturing resources and capabilities, facilitating efficient networked production. However, in the realm of the Internet, the challenge lies in efficiently aligning abundant information with a company’s manufacturing objectives to genuinely deliver an “on-demand service.” This represents a pivotal issue that demands immediate resolution within the operational framework of cloud manufacturing platforms. To effectively address the optimization challenge in Manufacturing Cloud Services (MCS), this study leverages two dimensions: the fundamental Quality of Service (QoS) of MCSs and the interrelated QoS among these services. A holistic QoS model for assembling MCSs is constructed. In this model, the timely relevance of fundamental QoS data is ensured through the incorporation of a temporal weighting function, while an enhancement in the precision of optimization is achieved by considering the interconnections between service combinations. The final simulation experiments showcase the effectiveness of the proposed approach in this paper.

Investigating Methods for ASPmT-Based Design Space Exploration in Evolutionary Product Design

Nowadays, product development is challenged by increasing system complexity and stringent time-to-market. To handle the demanding market requirements, knowledge from prior product generations is used to derive new, but partially similar product versions. The concept of product generation engineering, hence, allows manufacturers to release high-quality products within short development times. Therefore, in this paper, we propose a novel approach to evaluate the similarity of two product implementations based on the concept of the Hamming distance. This allows the usage of similarity information in various heuristics as well as in strategies and thus, to improve the product design process. In a wide set of cases, we investigate the quality and similarity of design points. In the experiments, the use of strategies leads to significantly short searching times, but also tends to be too restrictive in certain cases. Simultaneously, the quality of the solutions found in the heuristic design space exploration has been shown to be as good or better than for the search from scratch and considerably closer solutions as part of the non-dominated solution front have been found.

Use of artificial neural networks in architecture: determining the architectural style of a building with a convolutional neural networks

AbstractThe discussion of "can machines think?" which started with the invention of the modern computer, brought along the question of "can machines design?" by researchers in the design field. These developments in information technologies have also affected the architecture. Artificial intelligence applications are encountered in many areas such as pricing estimation, energy conservation security systems of buildings, ventilation systems, user-oriented interactive design solutions, computer-aided programs used in the plan production phase and design process. When the literature on artificial intelligence applications in the architecture is reviewed, it can be seen that it generally includes shape grammars, graph theory, decision trees, constraint-based models, machine learning methods, RNN (Recursive Neural Networks), CNN (Convolutional Neural Network) and GAN (Generative Adversarial Network) algorithms. In this study, the use of artificial intelligence algorithms in architecture was examined, and an example was designed to determine the architectural structures of different periods by using CNN (Convolutional Neural Network). In the study, the open source TensorFlow library developed by Google and the Python programming language were used. Employing a statistical approach and utilizing convolutional neural networks (CNNs), a study has successfully classified the current flow patterns of buildings based on datasets comprising facades of Gothic, Modern, and Deconstructivist architectural styles. The findings demonstrate the efficacy of CNNs in accurately distinguishing the intricate details of diverse architectural styles. Recognizing elements from different periods using the CNN algorithm can examine not only individual buildings but also the relationship of buildings with their environments. It can also gain an important place in the field of conservation of the architectural discipline. The historical processes, aesthetic features and changes of protected buildings can be learned with the CNN algorithm and can guide restoration decisions. As a result of the study, the employed CNN-based model can correctly classify structures with 84.66% accuracy rate.

Data-driven plasma science based plasma etching process design in OLED mass production referring to PI-VM

The production efficiencies of organic light emitting diode (OLED) displays and semiconductor manufacturing have been dramatically improving with the help of plasma physics and engineering technology by utilizing a process monitoring methodology based on physical domain knowledge. This domain knowledge consists of plasma-heating and sheath physics, plasma chemistry, and plasma-material surface reaction kinetics. They were applied to the plasma information based virtual metrology (PI-VM) algorithm with the plasma diagnostics and noticeably enhanced process prediction performance by parameterizing plasma information (PI) in various processes of OLED display and semiconductor manufacturing fabs. PI-VM has shown superior process prediction accuracy, which can trace the states of processing plasmas as an application of data-driven plasma science compared to the classical statistics and machine learning-based virtual metrologies; thus, various plasma processes have been managed and controlled with the help of the PI-VM models. More than this, we have adopted the PI-VM model to optimize the patterning architecture and plasma processes simultaneously. The best combination of the etching pattern structure and plasma condition was adjustable based on the detailed understanding of the angular distribution of sputtered atoms from the etching target surface and their interaction with the plasma sheath based on the PI-VM modeling for etching profile failure prediction.

Enabling digitally integrated product design and production through digital continuity and feedback to design

Due to global and political influence, resilient and versatile production systems are unavoidable. Based on existing Product Lifecycle Management (PLM) systems there is a growing need for a consistent communication between machines and product design to enable integrated product and production process design. Core aspects are integrating the product design information directly into the production equipment and their feedback into the product design as well as into other phases of the product creation and usage. Therefore, a generalized production description language as well as an architecture for the digital integrated product design and production need to be developed. This paper presents the first results of a use case in the automotive industry. The approach of developing the functional architecture is shown. Several feedback to X approaches were researched in literature and analyzed regarding functional requirements for integration in the developed architecture. The results are the main basis for further implementation within the automotive production. Moreover, the main challenges and next steps are discussed.

The Utilization of Critical Thinking During the Product Design Process

The Utilization of Critical Thinking During the Product Design Process

Eco backstage and its sustainability in terms of design, material or technology

On the website of the European Parliament, it is stated that “the global economy uses the equivalent of one and a half of the planet’s resources in order to produce global results and to absorb waste, and estimates show that these numbers will rise to the level of the resources of two planets by 2030.” Although ecological, sustainability and resilience policies have been adopted through legislation over 60 years ago, humanity finds itself at a point in time when the linear economy and demographic growth are still the main causes for the imminent depletion of natural resources, thus endangering the environment, the planet and the human species itself. In parallel with the implementation of these laws and policies, humanity is also aiming to conquer new territories or to exploit other planets. Although this is a more modern and glamorized mind-set, one that encompasses the whole solar system, it is, in essence, still a primitive “colonizer” thinking pattern. Under these circumstances, sustainable design has become not just a necessity, but rather a sine qua non for survival. Changing the traditional model of the economy to a circular one means multiplying the life cycles of a product. Thus, this paper aims to examine the “greening” of theatre set production by implementing circular design as the primary method to reshape material resources, technology, and product design processes, serving as the sole approach to prevent waste production.

Intelligent Algorithm-Driven Product Design Process Optimization: Intelligent Transformation of Product Design Processes

Abstract In this study, the Petri net model is initially employed to establish a framework for the product design process, subsequently enhanced by the integration of an ant colony algorithm to augment the intelligent capabilities of product design. Further refinement is achieved through the incorporation of a genetic algorithm, which optimizes the model by aligning the product design challenges more closely with real-world scenarios. This paper introduces a bespoke ant colony optimization algorithm tailored for discrete variable-oriented product design, focusing on optimizing the size and structural topology of products. A test enterprise is selected to demonstrate the efficacy of this approach. The analysis is conducted using a real case analysis method, assessing impacts on product manufacturing costs and input-output efficiency. Results from the implementation show a substantial reduction in the overall cost of intelligent product design by 15.819%. Following the adoption of smart product design strategies in 2017, there was a notable reduction in capital investment, amounting to 267,345,000 yuan, while maintaining the initial annual production volume. Over the period from 2016 to 2020, the employment of design engineers decreased by an average of 3,815 daily without compromising performance levels. The application of intelligent product process design not only achieved optimal input-output efficiency but also underscored the success of intelligent transformation in the product design process.

The future of green skills for the manufacturing sector

The European Green Deal and the European Innovation Council (EIC) aim to drive sustainability in manufacturing. Industry 5.0 emphasises the integration of automation with green skills, highlighting their importance for sustainability. However, which manufacturing areas need green skills and which green skills are crucial in manufacturing remains unclear. This paper aims to fill these gaps, by performing a literature review and an analysis of the European Skills, Competences, Qualifications, and Occupations (ESCO) database. Results identify five critical areas: Product-Process Design, Big Data Analytics and Artificial Intelligence, Supply Chain Management, Circular Economy, and Energy Management. These areas necessitate skills such as environmental impact assessment, waste management, data analysis, eco-design, and knowledge of renewable energy technologies. ESCO analysis indicates that 46.28% of 3008 occupations involve green skills, which are crucial for sustainable development. Targeted training programs are needed based on identified areas and skills. Interconnections among clusters and the importance of data analysis are highlighted. Additionally, in the near future manufacturing companies should attempt to develop broad, transversal skills integrated with digitalisation to meet an increasing demand for sustainability. Overall, the study provides insights into green skills development and their critical role in shaping the future of sustainable manufacturing.

Exploration of Intelligent Transformation Path of Traditional Cultural and Creative Products Based on Internet of Things Technology

Abstract More and more modern technology is applied to traditional cultural and creative industries, which enhances the technicality and novelty of traditional cultural products, and the fusion of culture and modern technology profoundly changes people’s way of life and learning. This paper explores the Internet of Things (IoT) technology and the intelligent transformation process of cultural and creative products and constructs cultural and creative products that integrate intelligent voice series. Specifically, a speech recognition model is integrated into the design process of cultural and creative products, and the designed model is applied to the design of intelligent cultural and creative products by analyzing the Hidden Markov Model (HMM), proposing a solution to the shortcomings of the HMM model, and choosing to perform noise reduction of speech signals through the fixed beam algorithm. Based on the speech recognition model designed in this paper, an intelligent cultural and creative product with a speech recognition function is designed, taking the ‘owl wine container’ from the Shanxi Museum as an example. The regression equation of the audience’s satisfaction with the product is Y (satisfaction) = -0.000263 + 0.208X1 (practicality) + 0.265X2 (innovation) + 0.253X3 (culture) + 0.271X4 (interactivity) - 0.296X5 (fun). This paper’s intelligent cultural and creative products have a greater impact on satisfaction due to their innovativeness and interactive function.

Visual Design of Medical Animation Production Processes: A Medical Animation Movie in Türkiye

Visual Design of Medical Animation Production Processes: A Medical Animation Movie in Türkiye

Inclusive manufacturing through the application of lean tools to sustainability issues

Lean Thinking is a management philosophy that focuses on reducing waste and enhancing customer value. This study applies the concept of Lean Thinking to confront sustainability challenges in manufacturing companies, particularly with regards to achieving the Sustainable Development Goals (SDG) of the Agenda 2030 that aim to integrate people with disabilities. Some commonly used and less frequently used tools, including the Ishikawa Diagram, Value Stream Mapping, and Cognitive Maps, were revised to mitigate the risks posed to the inclusion, full utilization, and well-being of workers. The findings indicate that adopting a lean thinking approach can facilitate the inclusive design of new production processes and enhance the efficiency of current operations, promoting social sustainability. The study identified certain challenges and drawbacks associated with applying Lean Thinking to sustainability concerns, including the necessity for stakeholder involvement, organizational cultural transformations, and steadfast devotion. Additionally, the study contributes to the extensive literature on lean and sustainability by offering practical use cases and informative perspectives on utilizing lean thinking as a means of promoting sustainable process enhancement and development.

A Process for Creating and Designing Automated CAD Models Through the SolidWorks API

This study proposes a novel method for speeding up CAD modelling procedures by combining parametric modelling strategies, Knowledge-Based Systems (KBS), and Visual Basic for Applications (VBA) inside the SolidWorks environment. The suggested system accepts client design requirements through a user-friendly graphical user interface (GUI), utilising the power of knowledge representation and automation to speed up the design process. This technique greatly decreases the amount of time needed to model CAD, improves design correctness, and equips engineers to quickly convert client demands into real components by utilising KBS and parametric modelling. This research shows the viability and efficacy of this unique technique, highlighting its potential to transform the processes of product design and development.