Design a personalised product service system utilising a multi-agent system

Chiu, Ming‐Chuan; Tsai, Chi-Hsuan

doi:10.1016/j.aei.2020.101036

Cited by 26 publications

(9 citation statements)

References 36 publications

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“…In the last years, customization has not been limited only to the development of unique products for the customers, but also to the personalization of the services offered to customer as a strategy to lock them into long-term relationships [15]. A few examples of this strategy are [16]: (i) sale of redesigned clothing (consumers purchase clothing that has been redesigned from old clothing items); (ii) clothing repair/alteration service (consumers are provided with repair services to maintain their clothes); (iii) clothing renting (consumers acquire a certain number of items to be used for a short time period); and (iv) style consultancy service (providing customers with a style consulting, in-store or online, on how to use their clothes or to create new looks).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Collaborative Product and Service Customization in Fashion Companies

Pessot

Macchion

Marchiori

et al. 2020

IFIP Advances in Information and Communication Technology

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This paper focuses on the identification of collaborative strategies and practices adopted by companies of the fashion industry in the management of customized offerings (both products and services) along their supply chain (SC). A multiple case study approach is applied and four companies (both medium and large) were interviewed. The cross-case analysis enabled mapping the cases following two dimensions: type of market asking for the customization (B2B vs. B2C) and scope of customization (products vs. services). The analysis highlights the practices and processes related to the customization, the enabling technologies adopted, and the actors involved by a focal company in the collaboration (both in upstream and downstream networks) to offer the product or service that meet customer needs.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Collaborative Product and Service Customization in Fashion Companies

Pessot

Macchion

Marchiori

et al. 2020

IFIP Advances in Information and Communication Technology

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show abstract

“…It is hard to launch a product by meeting the needs of every individual customer as their tastes are different for any industrial product. In that case, the dominant logic of products through the Smart Product Service System (PSS) is bringing an innovation by which the organisations can personalise the products as per customers' needs with various specifications (Chiu & Tsai, 2020). Organisations from any industrial belongings are now focusing on serving better performance rather than just a product with a large number of specifications so that making customers pleased has been found more effective than before time.…”

Section: Introductionmentioning

confidence: 99%

The Role of Servitization and Smart Product-Service Systems in the Industry

Al-Hodiany

Ateik

Aljounaidi

2022

MJSSH

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In the current decade of digitalisation, industries are focusing on product customers and its services to please customers with better performance and security and fulfilling their commitment to make the market smart as well as its customers. In that case, this study has aimed to investigate the servitization and smart product-service systems influence in the industries by using information and communication technologies (ICT), Cyber-Physical System (CPS), smart connected product (SCP) and Internet-of-Things (IoT). The study finds out that, servitization transforms the traditional business model into the digital or online business model and helps the customers to link with the technology. It also provides benefits and profits to the manufacturers of the industries, has been proved from the overall study that was the main curiosity point of the researcher behind choosing the topic. Hence, the discussion has added a value creation feature to the whole study while aiming and discussing the most relevant factors of servitization.

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“…This is mainly related to the so-called IoT (Internet of Things) and IIoT (Industrial IoT) applications (Huo et al, 2020;Bartodziej, 2017). In this scenario, producers have faced an additional challenge: the high degree of customization of embedded solutions required by consumers' demand (Chiu & Tsai, 2020). In a smart-phone-app-based purchase scenario, customization options are market differentials that producers cannot ignore nor renounce.…”

Section: Introductionmentioning

confidence: 99%

Improving Autoencoder-Based Anomaly Detection in Embedded Systems using Data Transformation

Oliveira

Bastos-Filho

Oliveira

2022

Preprint

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Quality control is a critical aspect of modern electronic circuit industry. In addition to being a prerequisite for proper functioning, circuit quality is closely related to safety, security, and economics. Deep learning models have been extensively used in embedded systems testing and anomaly detection. However, performance is heavily dependent on the data available for training. Often, the number of samples or even its quality is limited. This leads to poor training process and low performance. We present a solution to improve anomaly detection in embedded systems by transforming time signals acquired from the printed circuit board under test. The proposed approach is experimentally validated in two autoencoder-based anomaly detection systems. Hence, two types of signals are analyzed: electric current and thermographic signatures. In both cases, electrical or thermographic signals are pre-processed prior to being converted into spectrogram images, which are then used to train and test the autoencoder. The achieved anomaly detection accuracy improvement for the thermographic case is 71%, compared with the raw data. For the electric current case, we show how data transformations enable autoencoder training where, using raw data, training is not feasible. In this case, we find accuracy improvements of up to 98%. The results indicate that, even in a scenario where the available data are limited, it is possible to achieve an acceptable performance using the proposed technique.

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Design a personalised product service system utilising a multi-agent system

Cited by 26 publications

References 36 publications

Collaborative Product and Service Customization in Fashion Companies

Collaborative Product and Service Customization in Fashion Companies

The Role of Servitization and Smart Product-Service Systems in the Industry

Improving Autoencoder-Based Anomaly Detection in Embedded Systems using Data Transformation

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