Dongbo Li

A Web-based Product Service System for aerospace maintenance, repair and overhaul services

Manufacturing enterprises around the world have made significant efforts to provide high value added services in addition to their traditional product development and manufacturing business. A product service system (PSS) is presented in this paper which aims to better integrate product development with maintenance and service operations. This project focuses on the maintenance, repair and overhaul (MRO) services in the aerospace industry. A MRO service model is proposed for the development of the proposed PSS. An ontology-based knowledge representation model is developed for the reuse of knowledge unambiguously in MRO services. An initial attempt has been made to demonstrate the role of PSS in the aerospace industry as a decision support tool for MRO services. Product lifecycle management (PLM) environment and Web-based technologies have been developed to enable the methodology to provide services and support in the aerospace manufacturing and flight operations business.

Product lifecycle oriented digitization agile process preparation system

After analyzing the features of process preparation, a product lifecycle oriented digitization agile process preparation system (DAPP) is presented. This paper develops a general approach and a system tool for digitization agile process preparation (DAPP). First, according to modern manufacturing concept and the bottleneck problems of computer integrated manufacturing system (CIMS), a concept of DAPP is proposed. Secondly, after analysis of the characteristics of the process preparation system (DAPPS), the needs for DAPPS are explored in depth. Thirdly a framework is proposed to support DAPPS by providing computer-aided and database environments for DAPPS, advisory tools for product structure manufacturability evaluation, rapid process planning, tooling design, process consumption determination as well as field process preparation, and knowledge bases incorporated in the advisory tools. Fourthly, according to the framework, a design support strategy for DAPPS is investigated to guide the coordination of preparation activities. Finally, based on the proposed approach and strategy, the system prototype has been developed employing the knowledge-based approach. The results of this research will facilitate the rationalization of process preparation and thus shorten the preparation time.

The Requirement Analysis and Knowledge Management Methodologies in a Product Service System

Manufacturing enterprises are making more efforts in providing high value added services in addition to their traditional product business. A service-centric product service system (PSS) is present in this paper which is used as a decision support tool and offers a means of supporting decision-making for maintenance, repair and overhaul (MRO) solution finding. Requirement analysis technologies are used to identify the final important rating and the technical targets of engineering characteristics (ECs), and reduce the redundant ECs. An ontology-based knowledge representation is developed to represent, accumulate and collect knowledge and experience emerged during the MRO services, which realizes the knowledge originated from the service process and served operations. An initial attemp has been made to demonstrate the role of PSS as a decision support tool for MRO in the aerospace manufacturing business.

Double-layered big data analytics architecture for solar cells series welding machine

Abstract The rapid and extensive pervasion of big data has enhanced the revolution of the society. A great interest has arisen in the past five years for mining and sharing the massive data. However, implementation of the big data analysis is facing many challenges, such as the storage, transmission, and computing. How to make the decision more intelligent in latency time becomes a crucial requirement for many researches. In this paper, a double-layered architecture ATWDP of online and offline analytics for solar cells series welding machine industry is proposed and the distributed and parallel computing system can handle the above challenges. The ATWDP offers an approach to analyze the data gathered from various sensing devices stably and efficiently. Some key implementation technologies in the system are discussed, especially the Hadoop Apache framework. The evaluation of service quality based on Support Vector Machine-Dempster Shafer Theory (SVMs-DS) and Spark is an application scenario to illustrate the mechanism of the ATWDP. And a data set is used to verify the rationality of the ATWDP in the storage and processing. Test results show that the ATWDP platform has a good performance and is a suitable solution for dealing with the big data of solar cells series welding machine.

Process service quality evaluation based on Dempster-Shafer theory and support vector machine

Human involvement influences traditional service quality evaluations, which triggers an evaluation’s low accuracy, poor reliability and less impressive predictability. This paper proposes a method by employing a support vector machine (SVM) and Dempster-Shafer evidence theory to evaluate the service quality of a production process by handling a high number of input features with a low sampling data set, which is called SVMs-DS. Features that can affect production quality are extracted by a large number of sensors. Preprocessing steps such as feature simplification and normalization are reduced. Based on three individual SVM models, the basic probability assignments (BPAs) are constructed, which can help the evaluation in a qualitative and quantitative way. The process service quality evaluation results are validated by the Dempster rules; the decision threshold to resolve conflicting results is generated from three SVM models. A case study is presented to demonstrate the effectiveness of the SVMs-DS method.