Real-time Information Data Research Articles

Design Concept of Information Control Systems for Green Manufacturing Industries with IoT-Based Energy Efficiency and Productivity

In today's and future industrial competition, IoT and the Fourth Industrial Revolution are unavoidable. Indonesia must be prepared to compete globally in an increasingly efficient and integrated industry, including efficient energy use and renewable energy. This issue has received little strategic and scientific thought, particularly in Indonesia. This study purposes to create a conceptual model of an information control system in the industry, which will include operational performance. The method involves four steps. Firstly, the process flow within the industry is comprehensively analyzed, including the input, process, and output (IPO) aspects. Secondly, all information pertaining to each production process is integrated into the information system. Thirdly, a management control system (MCS) is proposed, incorporating key performance indicators (KPIs), allowing real-time monitoring by management. Lastly, real-time information data on resource sharing is submitted to the information sharing control system within similar industrial clusters. This enables related business parties to optimize their resource utilization based on the provided information. The results show that green manufacturing can be initiated by controlling energy-saving and productivity-related KPIs. The concept of IoT green manufacturing depends on active involvement from the government, industry and the public. A crucial aspect of this system is how the industry effectively manages production performance through shop floor control (SFC).

Self-Organizing Interval Type-2 Fuzzy Neural Network Compensation Control Based on Real-Time Data Information Entropy and Its Application in n-DOF Manipulator.

In order to solve the high-precision motion control problem of the n-degree-of-freedom (n-DOF) manipulator driven by large amount of real-time data, a motion control algorithm based on self-organizing interval type-2 fuzzy neural network error compensation (SOT2-FNNEC) is proposed. The proposed control framework can effectively suppress various types of interference such as base jitter, signal interference, time delay, etc., during the movement of the manipulator. The fuzzy neural network structure and self-organization method are used to realize the online self-organization of fuzzy rules based on control data. The stability of the closed-loop control systems are proved by Lyapunov stability theory. Simulations show that the algorithm is superior to a self-organizing fuzzy error compensation network and conventional sliding mode variable structure control methods in control performance.

Enhancing Industrial Agriculture Efficiency through Sensor Network Integration

Despite being pivotal in global food provision, industrial agriculture grapples with sustainability and efficiency challenges exacerbated by climate change and population growth. The paper focuses on the ability of sensor networks to mitigate these issues and how countering strategies are developed. A case study will be used to explain how sensor networks can be put into practice to monitor industrial agriculture and, thus, give farmers real-time data information for correct action-taking. An analysis was done on a small-scale farm specializing in growing staple crops. The study used diverse sensors, including moisture, temperature, and pest incidence rates. The implementation strategies we addressed excelled, supported by joint efforts that preserved its achievements. The data analysis revealed patterns and critical insights that are very useful to farming practices through which the crucial part of sensor networks about optimizing resources and sustainability is highlighted. The implication is that industrial agriculture’s major efficiency, eco-friendliness, and profit gains are very high. Still, the potential for applicability is a subject for thought at a small scale. Another possible development channel is to improve access to current advances in analytics and sensors to achieve higher agricultural productivity. During the last sentence, it is worth stressing that sensory networks have huge opportunities to drive advances in agriculture and lead it toward a friendly environment.

Adaptive Contextual Risk-Based Model to Tackle Confidentiality-Based Attacks in Fog-IoT Paradigm

The Internet of Things (IoT) allows billions of physical objects to be connected to gather and exchange information to offer numerous applications. It has unsupported features such as low latency, location awareness, and geographic distribution that are important for a few IoT applications. Fog computing is integrated into IoT to aid these features to increase computing, storage, and networking resources to the network edge. Unfortunately, it is faced with numerous security and privacy risks, raising severe concerns among users. Therefore, this research proposes a contextual risk-based access control model for Fog-IoT technology that considers real-time data information requests for IoT devices and gives dynamic feedback. The proposed model uses Fog-IoT environment features to estimate the security risk associated with each access request using device context, resource sensitivity, action severity, and risk history as inputs for the fuzzy risk model to compute the risk factor. Then, the proposed model uses a security agent in a fog node to provide adaptive features in which the device’s behaviour is monitored to detect any abnormal actions from authorised devices. The proposed model is then evaluated against the existing model to benchmark the results. The fuzzy-based risk assessment model with enhanced MQTT authentication protocol and adaptive security agent showed an accurate risk score for seven random scenarios tested compared to the simple risk score calculations.

Implementing the reliability of data information in multi-criteria decision making process based on fuzzy TOPSIS and fuzzy entropy

A multi-criteria decision-making process utilizes real-time data information, which is inherently uncertain and imprecise. To be relevant in the decision-making process, real-time data information must be reliable. Because fuzziness alone is insufficient to solve decision-making problems, measuring the information’s reliability is critical. Z-number, which incorporates both restrictions and reliability in its definition is considered as a powerful tool to depict the imperfect information. In this paper, a new methodology is developed based on fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and fuzzy entropy for solving the multi-criteria decision-making problems where the weight information for decision makers and criteria is incomplete. The evaluation of the information is represented in the form of linguistic terms and the following calculation is performed using Z-numbers. Fuzzy entropy is applied to determine the weights of the criteria and fuzzy TOPSIS is used to rank the alternatives. An empirical study of subjective well-being of working women is used to demonstrate the proposed methodology.

German Smart Meter Development and inspiration

The widespread use of smart meters provides electric power suppliers and power users with a number of innovative business models that add value. The new changes brought by smart meters include two-way communication capabilities, remote monitoring of the status quo of electricity use, transmission of real-time data information, and an increase in the frequency of meter reading, so that both the electricity supplier and the consumer can receive real-time data. These functions represent the corner of the smart meter’s potential, in fact smart meter technology can obviously become the basis of a series of innovative business models.

Study on Control Design of Boiler Burning Main Station in Power Plant

Boiler combustion control system adopts decentralized control of distributed control structure, the system structure is divided into three parts: the operator station, responsible for monitoring and configuration system; process control station (master station), to achieve automatic control function; data collection station (From the station), collecting front-end module real-time data information. In the operator station and the main station communication in the upper network using industrial Ethernet to complete the data transceiver function, the same in the underlying communication using Profibus network protocol to complete the data collection.

RFID impacts on barriers affecting lean manufacturing

Purpose Lean manufacturing is one of the leading paradigms for fast and proficient manufacturing but its proper implementation is a foremost task due to certain barriers affecting lean and can be handled when utilized with RFID technology. With this aspect in view, the purpose of this paper is to enlighten and present a thorough literature study that can show how RFID-based lean manufacturing is helpful for handling barriers affecting lean manufacturing in light of previous literature available. Design/methodology/approach In order to achieve this purpose a systematic literature review is conducted to justify the impacts of RFID technology for handling barriers. The aim of this systematic literature review is to initially find the barriers affecting lean implementation and then to explain the properties of RFID-based lean manufacturing which are highly feasible to handle detected barriers. Findings An interrelation is generated in this study which provides a clear indication that the properties of RFID carry significant effects to handle detected barriers in the operational, managerial and financial regime of manufacturing companies. The detected barriers that affect lean implementation are company’s cultures, top management commitment, poor employee administration, lack of finances, unbalanced inventory control, unstable customer handling and longer lead times. The properties of RFID-based lean manufacturing like operational visibility, inventory control, production control, minimized lead times and the real-time data information (to facilitate top management and employees on shop floor) are extremely helpful to control these barriers. Originality/value The originality of this study is the provision of clarity provided to both academicians and practitioners by citing and utilizing previous research studies which undoubtedly indicates positive impacts of RFID on lean implementation.

Design of Equipment Power Remote Control System Based on Ethernet

A network power control system was designed in the paper based on MCU STM32 in order to realize network control to the industrial site power equipment. Software and hardware design scheme of the system were given. STM32F103 chip was used as the main controller in the system and ENC28J60 chip as the Ethernet controller to connect network, the μIP protocol stack was used for network data communication. Network power control test experiment was carried out, the result showed that it can control the equipment power remotely, and can receive real-time information data of the industrial field through Ethernet.Compared with the traditional power control system, this system has the characteristics of intelligence, integration and remote.

A Coal Mine Security Production Dispatching System with Web Configuration Technology

Coal mine security production dispatching system with web configuration technology is an advanced information system that integrates Internet, Database, XML and Web configuration technology. The system combines organically information of real-time data of coal mine safety monitoring and production scheduling, and digitizes it and finally discloses solution Visual Graph via ActiveX-based components of Web configuration to achieve standardization, normalization, and high efficiency of coal mine safety production scheduling. This system has been successfully utilized in coal mine for two years and achieved expected success of providing fresh, quantitative, and truthful production scheduling information for safety production scheduling and management department.

Application Research on Real-Time Database System Model Based on Distributed System of Cloud Manufacturing

This paper analyzed on real-time database system, and applied the cloud manufacturing technology and distributed system technology to the database system model. Through the analysis on the real time database, we can got the distributed real-time data system types and data storage model, establish two kinds of memory T-mode and S-mode, database storage model and make the production of block. Finally establish the work flow of distributed real-time database system, get relevant application program. A large number of real-time data collection and administration can be realized, which can improve the real-time information data processing efficiency and system model performance. Through the establishment of model and analysis of its working process in the real-time distributed system real time database application path, it can provide guidance for the establishment of distributed real-time database system model.

Data Processing and Algorithm Analysis of Vehicle Path Planning Based on Wireless Sensor Network

Optimizing the path planning to reduce the time and cost is an essential consideration in modern society, and existing research has mostly concentrated on static path planning and real-time data information in vehicle navigational applications. Using dynamic path planning to adjust and update the path information in time is a challenging approach to reduce road congestion and traffic accidents. In this paper, we present a data analysis algorithm that determines an efficient dynamic path for vehicle repair-scrap sites and navigates more flexibly to avoid obstacles, where the key idea is to design the sensor wireless network that helps to obtain data from different devices. Firstly, the data processing scheme for real-time data with regional cluster and node division can be obtained from different sensor devices through the wireless senor network. Secondly, the search space and the relevant road information are restricted to a strongly connected graph. The most important strategy for an optimal solution to find the shortest path is the search method. Finally, to validate the performance of our design and algorithm, we have conducted a simulation based on necessary traffic variables. The performance simulation results show that real-time dynamic path planning can be significantly optimized using our data processing scheme.

Adaptive Fault Monitoring in All-Optical Networks Utilizing Real-Time Data Traffic

We propose a novel fault detection and localization scheme for all-optical networks with the information of real-time data traffic. Our adaptive fault localization framework is based on combining passive and proactive monitoring solutions, together with adaptive management in two phases. Numerical results indicate that our proposed scheme has good scalability, in terms of the number of fault monitors required. Also, we show that our framework allows more flexible network design, and requires much less monitoring bandwidth when compared with the passive monitoring solutions.

The Study on RFID Middleware for Real-Time Monitoring in Manufacturing

Real-time monitoring is an important function for manufacturing execution systems (MES). In order to acquire the real-time data information, RFID technology is used to collect the data in shop-floor. This paper studies RFID middleware for the real-time monitoring in discrete manufacturing. Firstly, a process flow model is proposed. And the model of the process flow is converting into a manufacturing node flow. Secondly, RFID devices are configured for the manufacturing node. And a formalized description for RFID middleware mode is suggested. For the sake of resolving the model of RFID middleware, the data process policy is studied, and the real-time status of the monitored part is acquired. At last, a prototypical software system is developed to demonstrate above ideas.

Production Process Management for the Composite Component Manufacturing Workshop

This paper presents a Manufacturing Execution System (MES) for the composite component manufacturing workshop of an aerospace enterprise. The production process management is the core module of the MES. The system shows the production process management has important effect on the workshop production. The function modules of the production process management are introduced in detail. An improved working flow of the production process for optimizing the traditional production process is emphatically described. Barcode technology is applied to collect the production data and quality inspection data. By scanning the barcode, the real time data information can be collected and data statistic analysis can be done rapidly. The integration relationship between the production process management system and other systems is also introduced. Three-layer structure is adopted to design and develop the system. The developed system has been applied in the composite component manufacturing workshop. The results show that working efficiency of production process management has been improved.

Adaptive Fuzzy Short-term Load Forecasting System

Forecasting of day load curve is a critical problem faced by power utilities. In this paper, a fuzzy forecasting system is designed and implemented. Its original forecasting model can be obtained by data learning and model parameters can then be adaptively optimized through gradient information of real-time data. Thus, the system is of extinguished adaptive feature and self-learning capability. Experimental results demonstrate the satisfactory performances of the intelligent forecasting system.