Data Quality Test Method for Factory Energy Management System

Q2 Social Sciences
Seung-hwan Ju, H. Seo
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引用次数: 0

Abstract

Because data is an important factor in the software industry, how to reliably test data is important. This is even more essential for building Industry 4.0 and smart industrial complexes. This study prepares ISO/IEC 25024-based test methods and guidelines and uses them for energy management at the industrial complex level. In order to provide services by collecting energy data from industrial complexes, it is necessary to verify data quality based on data reliability and compatibility of each plant. Data quality technology needs to conform to ISO TC184/SC4/WG13 (industrial data quality standard) based technology. The study defines the data quality evaluation matrix for the energy management system of industrial parks and factories. It defines five categories and maps detailed indicators to each. The category has three detailed items, which are evaluation items for core requirements, interoperability, and conformity to standards. Each data requirement category covers functionality and reliability, usability and efficiency, and portability as data requirements in the system. Core requirements for system operation such as data consistency are basic evaluation items, and interoperability, which is the semantic compatibility of data for integrated operation of multiple sites, is verified. In addition, data quality is evaluated by verifying standard conformance. Through this evaluation system, the requirements for linking the factory energy management system data with the industrial complex energy management system can be evaluated. This can be used to monitor data quality and develop improvement technologies by developing a master data quality management technology standard suitable for industrial sites.
工厂能源管理系统数据质量测试方法
因为数据是软件行业的一个重要因素,所以如何可靠地测试数据很重要。这对于建设工业4.0和智能工业综合体更为重要。本研究准备了基于ISO/IEC 25024的测试方法和指南,并将其用于工业综合体级别的能源管理。为了通过从工业综合体收集能源数据来提供服务,有必要根据每个工厂的数据可靠性和兼容性来验证数据质量。数据质量技术需要符合基于ISO TC184/SC4/WG13(工业数据质量标准)的技术。该研究定义了工业园区和工厂能源管理系统的数据质量评估矩阵。它定义了五个类别,并将详细的指标映射到每个类别。该类别有三个详细项目,分别是核心需求、互操作性和标准符合性的评估项目。每个数据需求类别都涵盖了作为系统中数据需求的功能性和可靠性、可用性和效率以及可移植性。数据一致性等系统运行的核心要求是基本评估项目,互操作性是多个站点综合运行数据的语义兼容性。此外,通过验证标准符合性来评估数据质量。通过该评估系统,可以评估工厂能源管理系统数据与工业复杂能源管理系统的连接要求。这可用于监测数据质量,并通过制定适用于工业现场的主数据质量管理技术标准来开发改进技术。
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来源期刊
Webology
Webology Social Sciences-Library and Information Sciences
自引率
0.00%
发文量
374
审稿时长
10 weeks
期刊介绍: Webology is an international peer-reviewed journal in English devoted to the field of the World Wide Web and serves as a forum for discussion and experimentation. It serves as a forum for new research in information dissemination and communication processes in general, and in the context of the World Wide Web in particular. Concerns include the production, gathering, recording, processing, storing, representing, sharing, transmitting, retrieving, distribution, and dissemination of information, as well as its social and cultural impacts. There is a strong emphasis on the Web and new information technologies. Special topic issues are also often seen.
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