Hyperledger fabric-based consortium blockchain for construction quality information management

2020 ◽  
Vol 7 (4) ◽  
pp. 512-527 ◽  
Author(s):  
Botao Zhong ◽  
Haitao Wu ◽  
Lieyun Ding ◽  
Hanbin Luo ◽  
Ying Luo ◽  
...  
Keyword(s):  
Information Management ◽  
Quality Information ◽  
Construction Quality

Construction quality information management with blockchains

2020 ◽  
Vol 120 ◽  
pp. 103373
Author(s):  
Da Sheng ◽  
Lieyun Ding ◽  
Botao Zhong ◽  
Peter E.D. Love ◽  
Hanbin Luo ◽  
...  
Keyword(s):  
Information Management ◽  
Quality Information ◽  
Construction Quality

ISO 9001:2000 based Quality Information Management Responsibility System

2007 ◽  
Vol 2 (2) ◽  
pp. 217 ◽  
Author(s):  
M. Sakthivel ◽  
S.R. Devadasan ◽  
S. Vinodh ◽  
A. Ramesh ◽  
S. Shyamsundar
Keyword(s):  
Information Management ◽  
Iso 9001 ◽  
Quality Information ◽  
Management Responsibility ◽  
Responsibility System

scholarly journals Data Cleaning in Knowledge Discovery Database-Data Mining (KDD-DM)

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2196-2199
Keyword(s):  
Data Mining ◽  
Information Systems ◽  
Data Quality ◽  
Knowledge Discovery ◽  
Information Management ◽  
Data Cleaning ◽  
Main Issue ◽  
Quality Information ◽  
Data Preparation ◽  
Paper Review

Data quality is a main issue in quality information management. Data quality problems occur anywhere in information systems. These problems are solved by Data Cleaning (DC). DC is a process used to determine inaccurate, incomplete or unreasonable data and then improve the quality through correcting of detected errors and omissions. Various process of DC have been discussed in the previous studies, but there is no standard or formalized the DC process. The Domain Driven Data Mining (DDDM) is one of the KDD methodology often used for this purpose. This paper review and emphasize the important of DC in data preparation. The future works was also being highlight.

Information management in lean office deployment contexts

2020 ◽  
Vol 11 (6) ◽  
pp. 1175-1206 ◽  
Author(s):  
Rodrigo de Castro Freitas ◽  
Maria do Carmo Duarte Freitas
Keyword(s):  
Information Processing ◽  
Information Management ◽  
Information Seeking ◽  
Theoretical Research ◽  
Future Research ◽  
Quality Information ◽  
Information Flows ◽  
Access To Information ◽  
Key Factors ◽  
Content Type

Purpose Lean office covers the improvement of administrative processes and information flows. In offices, one of the essential challenges is to coordinate the development of information management capabilities. Thus, this paper aims to identify the key factors of information management in lean office deployment contexts. Design/methodology/approach By adopting a qualitative approach, it consists of theoretical research that applies grounded theory's coding technique and exploits 27 scientific studies on lean office published in the past 20 years. Findings It identifies five key factors for managing information into an organizational structure that optimizes information flow, such as “information-seeking,” “access to information,” “information quality,” “information processing” and “use of information and communication technology”. Research limitations/implications Data analysis was restricted in scientific research regarding lean office deployment. Therefore, the accuracy of the concepts and categories of information management proposed in this paper can be adjusted and validated in future research, thus deepening the discussion of its findings. Practical implications It highlights issues for managing information in contemporary organizations such as failures in information retrieval, restrictions on access to information, lack of quality information, inadequate information processing criteria and inefficiency of information systems infrastructure. Originality/value It analyzes the lean office deployment from the theoretical framework of information management. Thus, it differs from other studies in this field because it is not limited to the operational aspects of lean management. Nevertheless, it shows that lean office reconfigures information flows and continually improves organizations’ strategic management.

Computerized quality information management system at Daido Steel, Chita Plant.

DENKI-SEIKO ◽  
1985 ◽  
Vol 56 (4) ◽  
pp. 234-241
Author(s):  
Shoji Sakatoku ◽  
Shinkichi Fujita ◽  
Masao Tanaka ◽  
Katsuhiko Arakawa ◽  
Hideki Izawa
Keyword(s):  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Quality Information ◽  
Quality Information Management System

scholarly journals Green Lean Total Quality Information Management in Malaysian Automotive Companies

2012 ◽  
Vol 41 ◽  
pp. 1708-1713 ◽  
Author(s):  
Noor Azlina Mohd. Salleh ◽  
Salmiah Kasolang ◽  
Ahmed Jaffar
Keyword(s):  
Information Management ◽  
Quality Information ◽  
Total Quality

Research on Quality Information Management Based on Quality BOM in Multi-Specification & Small-Batch Production

2013 ◽  
Vol 456 ◽  
pp. 90-95
Author(s):  
Dang Zhou ◽  
Ming He ◽  
Zhi Bing Yang
Keyword(s):  
Information Management ◽  
Information Structure ◽  
Information Management System ◽  
Production Quality ◽  
Black Box ◽  
Information Modeling ◽  
Quality Information ◽  
Capacity Evaluation ◽  
Functional Models ◽  
Structure Tree

The characteristic of quality information management in multi-specification & small-batch was discussed, compared with mass production. Quality BOM was defined and its specific contents were described. On this basis, quality information modeling method based on quality BOM was introduced. The information model of quality structure tree was established and information structure of quality node was described in detail. Three different methods of quality defects relevance, including weak relevance method, strong relevance method and black box relevance method, were introduced, which satisfied different requirements of quality capacity evaluation. Functional models of Nimak Quality Information Management System were introduced as an application example. It was proved by this application example that the research provided a new solution to the problems of quality information management.

scholarly journals Infollution (Information Pollution) Management, Filtering Strategy, Scalable Workforce, and Organizational Learning: A Conceptual Study

2019 ◽  
Vol 10 (4) ◽  
pp. 1-7 ◽  
Author(s):  
Qaisar Iqbal ◽  
Shaohua Yang ◽  
Rashid Nawaz ◽  
Yifeng Lin
Keyword(s):  
Information Management ◽  
Global Scale ◽  
Organisational Learning ◽  
Dynamic Capability ◽  
Quality Information ◽  
Processing Theory ◽  
Pollution Management ◽  
Information Generation ◽  
Technology And Communication ◽  
Conceptual Study

Information generation is increasing rapidly on a global scale. The exponential advancement in information technology and communication has accentuated the problem of effective information management. Yet, employees’ cognitive ability to process information has not increased in parallel with information generation. With the exponential rise of information, information pollution (infollution) emerges as a problem on an exponential basis. Infollution is among the greatest challenges of the 21st century. Nevertheless, based on information processing theory and dynamic capability, researchers have conceptualised that agile organisations can cope with information pollution by promoting scalable workforce and organisational learning. By employing coping strategies, filtering has been hypothesised as moderating the association of scalable workplace and organisational learning with infollution management. This research will extend the literature in the domain of information management and agile organisations. It will be particularly useful for information processors to identify quality information for improved decision-making. 

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