Research and Design of MES Based on Real-Time Database in Iron & Steel Enterprise

2011 ◽  
Vol 421 ◽  
pp. 586-589
Author(s):  
Lun Wei Chen ◽  
Rong Luo ◽  
Ping Luo ◽  
Qiang Jiao Li
Keyword(s):  
Real Time ◽  
Production Efficiency ◽  
Production Data ◽  
Automation System ◽  
Core Competitiveness ◽  
Planning And Scheduling ◽  
Iron And Steel ◽  
Upper Management ◽  
Database Technology ◽  
Real Time Database

Aiming at the status of the bottom automation system and upper management information system was not effectively integrated in iron and steel enterprise which leads to the delay of production data and the difficult of tracking production process, MES based on real-time database, in which production data is collected, analyzed and processed in real-time using real-time database technology, is researched and designed in this paper, it can optimize production planning and scheduling management level and greatly enhance the production efficiency and promote the core competitiveness of enterprise.

Study on SBO in the Real-Time Data Acquisition of Iron and Steel Enterprise

2011 ◽  
Vol 121-126 ◽  
pp. 438-442
Author(s):  
Shao Pu Yu ◽  
Kai Bi Zhang ◽  
Rong Luo
Keyword(s):  
Real Time ◽  
Production Costs ◽  
Time Data ◽  
Enterprise Information System ◽  
Enterprise Information ◽  
Iron And Steel ◽  
The Real ◽  
General Production ◽  
Database Technology ◽  
Real Time Database

On the basis of research on the steel enterprise information system in the current domestic small and medium-scale iron and discovery of the adequate for the existing system, a idea of the combination the real-time database technology with advanced management services is put forward. By SBO platform we construct the general production framework based real-time database and design its main functional modules; at the same time, we summarize the overview of the interface method with real-time database, finally we realize the program .The program helps raise the level of corporate information production and productivity, reduce production costs significantly and improve their market competitiveness.

Transaction Issues in Mobile Distributed Real-Time Database Systems

2019 ◽  
Vol 13 ◽  
Author(s):  
Prakash Kumar Singh ◽  
Udai Shanker
Keyword(s):  
Real Time ◽  
New Technology ◽  
Database Systems ◽  
Industrial Applications ◽  
Distributed Applications ◽  
Mobile Environment ◽  
Research Issues ◽  
Database Technology ◽  
Real Time Database ◽  
Performance Issues

In recent years, a large number of populations are dependent on mobile database technology and it is difficult for us to imagine our lifestyle in absence of database. Today’s portable handy mobile devices take part in emerging new technology for sharing distributed applications or/ and information between many users even on the move (from one network to another). To manage this resulting large Volume of data in a wireless environment with time constraints such as deadline making it the fertile land of research for researchers. Fast transaction processing in many industrial applications is needed efficient algorithm and protocols in the field of mobile distributed real-time database (MDRTDBS). Transaction execution in a mobile environment has various interesting research issues like low bandwidth, storage capacity, power backup, priority scheduling policy, and concurrency and commits protocols, security, check-pointing etc. At first in our paper, we address performance issues that are important to MDRTDBS and then survey the various researches that have been done so far. In fact, this paper provides ground knowledge for addressing the performance issues important for mobile distributed real-time database and somehow helping to find out the future area of research in the field of MDRTDBS.

scholarly journals Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4836
Author(s):  
Liping Zhang ◽  
Yifan Hu ◽  
Qiuhua Tang ◽  
Jie Li ◽  
Zhixiong Li
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Real Time ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Data Driven ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Production Data ◽  
Online Decision Making

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

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