An Integrated Approach for Design Improvement Based on Analysis of Time-Dependent Product Usage Data

Ma, Hongzhan; Chu, Xuening; Lyu, Guolin; Xue, Deyi

doi:10.1115/1.4037246

Cited by 24 publications

(11 citation statements)

References 27 publications

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“…17 As a research basis, data-driven design method has an important impact on product creativity and design efficiency. The research content of data-driven design focuses on knowledge and data mining technology, 18 product usage data analysis approach, 19 and customer preference prediction. 20 The relationship between data-driven design and PLM is complex, and key scientific issues such as design methodology and knowledge classification system still need to be studied intensively.…”

Section: Introductionmentioning

confidence: 99%

Data-driven product design toward intelligent manufacturing: A review

Feng

Zhao

Zheng

et al. 2020

International Journal of Advanced Robotic Systems

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With the arrival of the big data era, a lot of valuable data have been generated in the entire product life cycle. The gathered product data contain a lot of design knowledge, which brings new opportunities to enhance the production efficiency and product competitiveness. Data-driven product design is an effective and popular design method, which can provide sufficient support for designers to make smart decisions. This article focuses on a comprehensive review of the existing research in data-driven product design. Based on the product design process, this article summarizes the data-driven design methods into the following aspects: customer requirement analysis, conceptual design, detailed design, and design knowledge support tools. In the customer requirement analysis stage, through data mining and transformation methods, customer requirements are predicted and then mapped to obtain accurate requirement expressions for aiding designers to explore the design space. In the conceptual design stage, the intelligent algorithms and data warehouse technologies are discussed in detail for function reasoning and scheme decision-making to achieve the iterative mapping from customer space to solution space. In the detailed design stage, data modeling languages and methods are introduced to support the simulation verification of the design process. For the design knowledge support tools, the methods of extracting knowledge from product data are discussed in detail, and the realization of computer-aided conceptual design is assisted through the development of knowledge-oriented design tools. Finally, this article summarizes the key points of data-driven product design research and provides an outlook for future research directions.

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Section: Introductionmentioning

confidence: 99%

Data-driven product design toward intelligent manufacturing: A review

Feng

Zhao

Zheng

et al. 2020

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

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“…Real-life data gathered by sensors are supporting virtual simulations of usages and in the end the redesign of the next products' generation. Shin et al (2015) and Ma et al (2017) proposed similar works based on field data. With the help of sensors and data analytics, the defective design parameters related to abnormal field data are identified.…”

Section: Embodiment Designmentioning

confidence: 99%

Data-Driven Design Challenges in the Early Stages of the Product Development Process

et al. 2021

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With the rapid development of digital technologies, products connectivity is increasing as well as the data produced and collected. Forecasts on product development predict that this trend will keep on growing. In this context, new design solutions based on data are emerging. Those data-driven design approaches are common for identifying the customers' need when developing a new product. However, few studies cover data-driven design in the other early stages of product design. Thus, the research question addressed in this paper is: what are the challenges of data-driven design research in the early phases of the product development process? Through a literature review and a workshop proposed at the conference DESIGN 2020, this paper offers a first glimpse of future research leads. A list of 5 challenges for data-driven design in the early stages of product design is proposed and ranked from short term to long term.

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“…In addition to demand-side data, companies collect reams of useful data from their production systems and operating environments. Data can be generated from a multitude of sources, such as production machinery, supply chain management systems and monitoring systems (Noor 2013;Ma et al 2017;Ghobakhloo 2020), also using systemic approaches (Alfieri et al 2012). The massive data generation and their systematic collection have been even more stressed with the revolution in production systems brought by Industry 4.0 actions.…”

Section: Supply-side Datamentioning

confidence: 99%

Data-driven design: the new challenges of digitalization on product design and development

et al. 2020

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Digitalization and the momentous role being assumed by data are commonly viewed as pervasive phenomena whose impact is felt in all aspects of society and the economy. Design activity is by no means immune from this trend, and the relationship between digitalization and design is decades old. However, what is the current impact of this ‘data revolution’ on design? How will the design activity change? What are the resulting research questions of interest to academics? What are the main challenges for firms and for educational institutions having to cope with this change? The paper provides a comprehensive conceptual framework, based on recent literature and anecdotal evidence from the industry. It identifies three main streams: namely the consequences on designers, the consequences on design processes and the role of methods for data analytics. In turn, these three streams lead to implications at individual, organizational and managerial level, and several questions arise worthy of defining future research agendas. Moreover, the paper introduces relational diagrams depicting the interactions between the objects and the actors involved in the design process and suggests that what is occurring is by no means a simple evolution but a paradigmatic shift in the way artefacts are designed.

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An Integrated Approach for Design Improvement Based on Analysis of Time-Dependent Product Usage Data

Cited by 24 publications

References 27 publications

Data-driven product design toward intelligent manufacturing: A review

Data-driven product design toward intelligent manufacturing: A review

Data-Driven Design Challenges in the Early Stages of the Product Development Process

Data-driven design: the new challenges of digitalization on product design and development

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