Data-driven customer requirements discernment in the product lifecycle management via intuitionistic fuzzy sets and electroencephalogram

Lou, Shanhe; Feng, Yixiong; Zheng, Hao; Gao, Yicong; Tan, Jianrong

doi:10.1007/s10845-018-1395-x

Cited by 20 publications

(6 citation statements)

References 46 publications

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“…(dysfunctional question)”. For each question, the participants can choose an answer from “I like it that way,” “It must be that way,” “I am neutral,” “I can live with it that way,” and “I dislike it that way.” There are 5∗5 possible results, and each of which corresponds to a Kano attribute [ 20 ].…”

Section: Methodsmentioning

confidence: 99%

Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Mao

Xie

Zhao

et al. 2022

International Journal of Nursing Sciences

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Objectives Gerontechnology has great potential in promoting older adults’ well-being. With the accelerated aging process, gerontechnology has a promising market prospect. However, most technological developers and healthcare professionals attached importance to products’ effectiveness, and ignored older adults’ demands and user experience, which reduced older adults' adoption intention of gerontechnology use. The inclusion of older adults in the design process of technologies is essential to maximize the effect. This study explored older adults’ demands for a self-developed intelligent medication administration system and proposed optimization schemes, thus providing reference to developing geriatric-friendly technologies and products. Methods A cross-sectional survey was conducted to explore older adults’ technological demands for the self-developed intelligent medication administration system, and data were analyzed based on the Kano model. A self-made questionnaire was administered from July 2020 to October 2020 after participants used this system for two weeks. The study was registered with the Chinese Clinical Trial Registry (ChiCTR2000040644). Results A total of 354 older adults participated in the survey. Four items, namely larger font size, simpler operation process, scheduled medication reminders and reliable hardware, were classified as must-be attributes; three items, namely searching drug instructions through WeChat, more sensitive system and longer battery life, as attractive attributes; one item, viewing disease-related information through WeChat, as the one-dimensional attribute; and the rest were indifferent attributes, including simple and beautiful displays, blocking advertisements automatically, providing user privacy protection protocol, viewing personal medical information only by logged-in users, recording all the medications, ordering medications through WeChat. The satisfaction values were between 0.24 and 0.69, and dissatisfaction values were between 0.06 and 0.94. Conclusion This study suggested that older adults had personalized technology demands. Including their technological demands and desire may assist in decreasing the digital divide and promoting the satisfaction of e-health and/or m-health. Based on older adults’ demands, our study proposed optimization schemes of the intelligent medication administration system, which may help developers design geriatric-friendly intelligent products and nurses to perform older adults-centered and efficient medication management.

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Section: Methodsmentioning

confidence: 99%

Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Mao

Xie

Zhao

et al. 2022

International Journal of Nursing Sciences

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“…Operators can use the real-time data that digital twins give for planning, production, and sourcing in a variety of ways. In terms of smart approach savvy operations, smart controls, and smart management, they promote effective production strategies [1,14,17,22].…”

Section: Concept Of Digital Twinmentioning

confidence: 99%

“…Facilities managers may improve critical operational areas like remote machine setup, preventive and emergency repairs, material supply, pricing for goods, information reporting, and more with the aid of these strategies. These improvements, which include more precise maintenance predictions, enhanced service agendas, and more precise and objective decisions, aid in optimizing product performance in comparison to services [1]. A number of enabling technologies, including life cycle management (PLM), enterprise-level resource planning (ERP), the internet of Things (IoT), and electronic physical systems (CPSs), which can interact with one another in real time, are necessary for the majority of SMEs to address industry problems pursuant to the 4th Industrial Revolution [2].…”

Section: Introductionmentioning

confidence: 99%

Digital Twin of Product Life Cycle

2024

مجلة الدلتا الدولية للعلوم التجارية ونظم المعلومات

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The goal of this study is to investigate the theoretical underpinnings of smart manufacturing's use of digital twins, product life cycles, and cyber-physical systems. By integrating the flow of information as well as data throughout all phases of corporate operations, digitization is the foundation that enables swift reaction to constantly changing business environments. One of the 4th Fourth Revolution's technologies, known as a "digital twin," has emerged in reaction to the advancement of manufacturing techniques, goods, and services. Production goods and systems are no longer sophisticated systems that carry out their tasks and meet quality standards; they now also interact with other parts, goods, and services through the Internet of Things via cyber networks. According to this article, the concept of a digital twin hinges on controlling the full product life cycle through the integration of the physical and virtual worlds via cyber-physical systems through cyberspace. Additionally, it demonstrates how digital twin processes and analyzes data using machines learning, AI, IoT sensors, computing in the cloud, and virtual modeling to support development and decisionmaking. In order to boost industrial productivity, cut costs, forecast failures and unexpected stops, and perform predictive maintenance, it was required to create a convergence within the material universe and cyber domains.

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“…As pointed by Kusiak [23], big data is a long way from transforming manufacturing, because most of the manufacturers and customers do not know what to do with the big data they have. Hence, how to apply the advanced analytics techniques to carry out efficient BDA is a vital task for manufacturers to transform their manufacturing mode and determine their competitiveness [33,34]. For example, in order to optimise the design scheme of new products, the agentbased system (ABS) and artificial neural networks (ANN) were investigated [35,36].…”

Section: Related Work and Knowledge Gapmentioning

confidence: 99%

An Advanced Operation Mode with Product-Service System Using Lifecycle Big Data and Deep Learning

Ren

Zhang

Sakao

et al. 2021

Int. J. of Precis. Eng. and Manuf.-Green Tech.

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As a successful business strategy for enhancing environmental sustainability and decreasing the natural resource consumption of societies, the product-service system (PSS) has raised significant interests in the academic and industrial community. However, with the digitisation of the industry and the advancement of multisensory technologies, the PSS providers face many challenges. One major challenge is how the PSS providers can fully capture and efficiently analyse the operation and maintenance big data of different products and different customers in different conditions to obtain insights to improve their production processes, products and services. To address this challenge, a new operation mode and procedural approach are proposed for operation and maintenance of bigger cluster products, when these products are provided as a part of PSS and under exclusive control by the providers. The proposed mode and approach are driven by lifecycle big data of large cluster products and employs deep learning to train the neural networks to identify the fault features, thereby monitoring the products’ health status. This new mode is applied to a real case of a leading CNC machine provider to illustrate its feasibility. Higher accuracy and shortened time for fault prediction are realised, resulting in the provider’s saving of the maintenance and operation cost.

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Data-driven customer requirements discernment in the product lifecycle management via intuitionistic fuzzy sets and electroencephalogram

Cited by 20 publications

References 46 publications

Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Digital Twin of Product Life Cycle

An Advanced Operation Mode with Product-Service System Using Lifecycle Big Data and Deep Learning

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