Intelligent decision-making support system for manufacturing solution recommendation in a cloud framework
- PDF / 1,512,930 Bytes
- 16 Pages / 595.276 x 790.866 pts Page_size
- 65 Downloads / 223 Views
ORIGINAL ARTICLE
Intelligent decision-making support system for manufacturing solution recommendation in a cloud framework Alessandro Simeone 1 & Yunfeng Zeng 1 & Alessandra Caggiano 2,3 Received: 27 July 2020 / Accepted: 9 November 2020 # The Author(s) 2020
Abstract Cloud manufacturing represents a valuable tool to enable wide sharing of manufacturing services and solutions by connecting suppliers and customers in large-scale manufacturing networks through a cloud platform. In this context, with increasing manufacturing network size at global scale, the elevated number of manufacturing solutions offered via cloud platform to connected customers can increase the complexity of decision-making, resulting in poor user experience from a customer perspective. To tackle this issue, in this paper, an intelligent decision-making support tool based on a manufacturing service recommendation system (RS) is designed and developed to provide for tailored manufacturing solution recommendation to customers in a cloud manufacturing system. A machine learning procedure based on neural networks for data regression is employed to process historical data on user manufacturing solution preferences and to carry out the automatic extraction of key features from incoming user instances and compatible manufacturing solutions generated by the cloud platform. In this way, the machine learning procedure is able to perform a customer segmentation and build a recommendation list characterized by a ranking of manufacturing solutions which is tailored to the specific customer profile. With the aim to validate the proposed intelligent decision-making support system, a case study is simulated within the framework of a cloud manufacturing platform delivering dynamic sharing of sheet metal cutting manufacturing solutions. The system capability is discussed in terms of machine learning performance as well as industrial applicability and user selection likelihood. Keywords Cloud manufacturing . Industry 4.0 . Decision-making support . Recommendation system . Machine learning . Neural network
1 Introduction In modern industrial framework, the broad sharing of manufacturing services and solutions within large-scale manufacturing networks is strongly supported by cloud manufacturing (CMfg). The latter allows to connect suppliers and customers via a cloud platform by integrating Industry 4.0 key enabling technologies such as cloud computing and Internet of things (IoT) [1–3].
* Alessandra Caggiano [email protected] 1
Intelligent Manufacturing Key Laboratory of Ministry of Education, Shantou University, Shantou, China
2
Department of Industrial Engineering, University of Naples Federico II, Naples, Italy
3
Fraunhofer Joint Laboratory of Excellence on Advanced Production Technology (Fh-J_LEAPT UniNaples), Naples, Italy
Most CMfg platforms are designed to dynamically manage and combine the manufacturing service offers and demands in the network with the aim to deliver on-demand manufacturing solutions according to a service-oriented model
Data Loading...
