Since the late of previous decade, hypertext technique has been applied in many areas. A hypertext data model with version control which is applied to a digital delivery for engineering documents named Optical Disk ba...Since the late of previous decade, hypertext technique has been applied in many areas. A hypertext data model with version control which is applied to a digital delivery for engineering documents named Optical Disk based Electronic Archives Management System(ODEAMS) is presented first and it has successfully solved some problems in engineering data management. Then, this paper describes some details to implement the hypertext network in ODEAMS after introducing the requirements and characters of engineering data management.展开更多
This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling ...This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.展开更多
Engineering Change (EC) management for a Product Lifecycle Management (PLM) system, including EC data model, EC evaluation and EC implementation is presented. A method of dynamic and parallel EC evaluation is proposed...Engineering Change (EC) management for a Product Lifecycle Management (PLM) system, including EC data model, EC evaluation and EC implementation is presented. A method of dynamic and parallel EC evaluation is proposed, which breaks an EC evaluation task into several subtasks. Such subtasks can be dynamically and simultaneously proceeded, disassembled and communicated by different specialists, and at the same time a set of EC objects is created. This approach provides flexible and effective evaluation of the EC. The EC implementation followed will further ensure the completeness and consistency of EC data.展开更多
Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and e...Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.展开更多
Engine data management is of great significance for ensuring data security and sharing,as well as facilitating multi-party collaborative learning.Traditional data management approaches often involve decentralized data...Engine data management is of great significance for ensuring data security and sharing,as well as facilitating multi-party collaborative learning.Traditional data management approaches often involve decentralized data storage that is vulnerable to tampering,making it challenging to conduct multi-party collaborative learning under privacy protection conditions and fully leverage the value of data.Moreover,data with compromised integrity can lead to incorrect results if used for model training.Therefore,this paper aims to break down data sharing barriers and fully utilize decentralized data for multi-party collaborative learning under privacy protection conditions.We propose a trustworthy engine data management method based on blockchain technology to ensure data immutability and non-repudiation.To address the issue of limited data samples for some users resulting in poor model performance,we introduce swarm learning techniques based on centralized machine learning and design a trustworthy data management method for swarm learning,achieving trustworthy regulation of the entire process.We conduct research on engine models under swarm learning based on the NASA open dataset,effectively organizing decentralized data samples for collaborative training while ensuring data privacy and fully leveraging the value of data.展开更多
A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern...A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern scientific discovery and technologic advancement. The importance of good information was long recognized by prominent leaders such as Sun Tzu and Napoleon. Factual data enables managers to measure, to understand their businesses, and to directly translate that knowledge into improved decision making and performance. This position paper argues that data analytics is ready to change engineering management in the following areas: 1) by making relevant historical data available to the manager at the time when it's needed; 2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful data from multiple sources to support quantitative decision-making. Considering the unique need for engineering management, the paper proposes researchable topics in the two broad areas of data acquisition and data analytics. The purpose of the paper is to provoke discussion from peers and to encourage research activity.展开更多
This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge...This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge and the history of big data. Second, the paper reviews the academic activities about big data in China. Then, it elaborates a number of challenging big data problems, including transforming semi-structured and non-structured data into"structured format" and explores the relationship of data heterogeneity, knowledge heterogeneity and decision heterogeneity. Furthermore, the paper reports various real-life applications of big data, such as financial and petroleum engineering and internet business.展开更多
文摘Since the late of previous decade, hypertext technique has been applied in many areas. A hypertext data model with version control which is applied to a digital delivery for engineering documents named Optical Disk based Electronic Archives Management System(ODEAMS) is presented first and it has successfully solved some problems in engineering data management. Then, this paper describes some details to implement the hypertext network in ODEAMS after introducing the requirements and characters of engineering data management.
文摘This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.
基金Supported by Fujian Province Natural Science Foundation (A04400066)Xiamen Science and Technology Program(3502Z20055028)
文摘Engineering Change (EC) management for a Product Lifecycle Management (PLM) system, including EC data model, EC evaluation and EC implementation is presented. A method of dynamic and parallel EC evaluation is proposed, which breaks an EC evaluation task into several subtasks. Such subtasks can be dynamically and simultaneously proceeded, disassembled and communicated by different specialists, and at the same time a set of EC objects is created. This approach provides flexible and effective evaluation of the EC. The EC implementation followed will further ensure the completeness and consistency of EC data.
文摘Engineering data are separately organized and their schemas are increasingly complex and variable. Engineering data management systems are needed to be able to manage the unified data and to be both customizable and extensible. The design of the systems is heavily dependent on the flexibility and self-description of the data model. The characteristics of engineering data and their management facts are analyzed. Then engineering data warehouse (EDW) architecture and multi-layer metamodels are presented. Also an approach to manage anduse engineering data by a meta object is proposed. Finally, an application flight test EDW system (FTEDWS) is described and meta-objects to manage engineering data in the data warehouse are used. It shows that adopting a meta-modeling approach provides a support for interchangeability and a sufficiently flexible environment in which the system evolution and the reusability can be handled.
文摘Engine data management is of great significance for ensuring data security and sharing,as well as facilitating multi-party collaborative learning.Traditional data management approaches often involve decentralized data storage that is vulnerable to tampering,making it challenging to conduct multi-party collaborative learning under privacy protection conditions and fully leverage the value of data.Moreover,data with compromised integrity can lead to incorrect results if used for model training.Therefore,this paper aims to break down data sharing barriers and fully utilize decentralized data for multi-party collaborative learning under privacy protection conditions.We propose a trustworthy engine data management method based on blockchain technology to ensure data immutability and non-repudiation.To address the issue of limited data samples for some users resulting in poor model performance,we introduce swarm learning techniques based on centralized machine learning and design a trustworthy data management method for swarm learning,achieving trustworthy regulation of the entire process.We conduct research on engine models under swarm learning based on the NASA open dataset,effectively organizing decentralized data samples for collaborative training while ensuring data privacy and fully leveraging the value of data.
文摘A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern scientific discovery and technologic advancement. The importance of good information was long recognized by prominent leaders such as Sun Tzu and Napoleon. Factual data enables managers to measure, to understand their businesses, and to directly translate that knowledge into improved decision making and performance. This position paper argues that data analytics is ready to change engineering management in the following areas: 1) by making relevant historical data available to the manager at the time when it's needed; 2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful data from multiple sources to support quantitative decision-making. Considering the unique need for engineering management, the paper proposes researchable topics in the two broad areas of data acquisition and data analytics. The purpose of the paper is to provoke discussion from peers and to encourage research activity.
基金supported by the key research grant"Innovative Research on Management Decision Making under Big Data Environment"(Grant No.71331005)"Non-structured Data Analysis Methods and Key Technologies for Management Decision Making"(Grant No.71501175)the key international collaboration grant"Business Intelligence Methods Based on Optimization Data Mining with Applications of Financial and Banking Management"(Grant No.71110107026)from the National Natural Science Foundation of China
文摘This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge and the history of big data. Second, the paper reviews the academic activities about big data in China. Then, it elaborates a number of challenging big data problems, including transforming semi-structured and non-structured data into"structured format" and explores the relationship of data heterogeneity, knowledge heterogeneity and decision heterogeneity. Furthermore, the paper reports various real-life applications of big data, such as financial and petroleum engineering and internet business.
