scholarly journals Remote monitoring of operational parameters for the cane honey production process

Lámpsakos ◽  
2021 ◽  
pp. 3991
Author(s):  
Víctor Rodrigo Cerda Mejía ◽  
Octavio Edelberto Guijarro Rubio ◽  
Isnel Benítez Cortés ◽  
Galo Leonardo Cerda Mejía ◽  
Estela Guardado Yordi ◽  
...  
Keyword(s):  
Wireless Communication ◽  
Production Process ◽  
Real Time ◽  
Storage System ◽  
Ph Sensor ◽  
Industrial Process ◽  
Future Research ◽  
Operational Parameters ◽  
Local Data ◽  
Honey Production

A local data acquisition, processing and storage system were implemented by means of an open source micro-controlled development card. To continuously measure the variables of the cane honey production process, it was performed using five temperature sensors, pH sensor and a level sensor. Each sensor was associated with a component set with its respective upper and lower reference values, during the processing of a batch of product. The main objective was to determine the effectiveness of using sensors and wireless communication technology to monitor operational parameters, in real time. In general, the recorded temperature, pH and level data obtained from sensors corresponded closely to the changes that occurred in the process, and the wireless communication nodes developed successfully measured and monitored the temperature, pH and level readings in real time. The study also found that the temperature, pH and level readings obtained by the sensors began to standardize more closely within the upper and lower limits. Furthermore, operational parameters could be reasonably predicted by applying a statistical model to measure temperature, pH and level. The present study also found that the operational parameters analyzed showed variability with its consequent effect on the quality of the final product. The findings of this study should serve as the first step towards any future research and development that may take place in the field of agro-industrial process design

Intelligent Safety Control System for Operation of Group Tower Cranes

2013 ◽  
Vol 330 ◽  
pp. 592-597
Author(s):  
Zhen Zhen Zhang ◽  
Hong Liu Xu ◽  
Xiao Guan ◽  
Bin Wang
Keyword(s):  
Control System ◽  
Wireless Communication ◽  
Real Time ◽  
Early Warning ◽  
Intelligent Design ◽  
Failure Diagnosis ◽  
Operational Parameters ◽  
Control Module ◽  
Safety Control ◽  
Data Acquisition Module

An intelligent safety control system for operation of group tower cranes was developed in the context of rising security problems during operation of group tower cranes. The anti-anti-collision principle includes self-anti-collision and multi-tower cranes anti-collision. The system consists of PLC module, Touch screen, signal receiving module, data acquisition module, control module and signal transmitting module. Several techniques such as digital coding, early warning, failure diagnosis, wireless communication, intelligent design and humanization design are applied in the system. Operational parameters of tower canes are detected in real time insure the safety for cross operation of several tower cranes.

scholarly journals Review of Soft Sensors in Anaerobic Digestion Process

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1434
Author(s):  
Pengfei Yan ◽  
Minghui Gai ◽  
Yuhong Wang ◽  
Xiaoyong Gao
Keyword(s):  
Anaerobic Digestion ◽  
Production Process ◽  
Real Time ◽  
Industrial Production ◽  
Soft Sensor ◽  
Future Research ◽  
Real Time Monitoring ◽  
Soft Sensors ◽  
Digestion Process ◽  
Volatile Fatty Acid Concentration

Anaerobic digestion is associated with various crucial variables, such as biogas yield, chemical oxygen demand, and volatile fatty acid concentration. Real-time monitoring of these variables can not only reflect the process of anaerobic digestion directly but also accelerate the efficiency of resource conversion and improve the stability of the reaction process. However, the current real-time monitoring equipment on the market cannot be widely used in the industrial production process due to its defects such as expensive equipment, low accuracy, and lagging analysis. Therefore, it is essential to conduct soft sensor modeling for unmeasurable variables and use auxiliary variables to realize real-time monitoring, optimization, and control of the an-aerobic digestion process. In this paper, the basic principle and process flow of anaerobic digestion are first briefly introduced. Subsequently, the development history of the traditional soft sensor is systematically reviewed, the latest development of soft sensors was detailed, and the obstacles of the soft sensor in the industrial production process are discussed. Finally, the future development trend of deep learning in soft sensors is deeply discussed, and future research directions are provided.

scholarly journals Real-time vision-based multiple object tracking of a production process: Industrial digital twin case study

2021 ◽  
pp. 095440542110024
Author(s):  
Robert Ward ◽  
Payam Soulatiantork ◽  
Shaun Finneran ◽  
Ruby Hughes ◽  
Ashutosh Tiwari
Keyword(s):  
Production Process ◽  
Real Time ◽  
Industry 4.0 ◽  
Low Cost ◽  
Digital Simulation ◽  
Smart Manufacturing ◽  
Design Solution ◽  
Future Research ◽  
Production Cycle ◽  
Process Industries

The adoption of Industry 4.0 technologies within the manufacturing and process industries is widely accepted to have benefits for production cycles, increase system flexibility and give production managers more options on the production line through reconfigurable systems. A key enabler in Industry 4.0 technology is the rise in Cyber-Physical Systems (CPS) and Digital Twins (DTs). Both technologies connect the physical to the cyber world in order to generate smart manufacturing capabilities. State of the art research accurately describes the frameworks, challenges and advantages surrounding these technologies but fails to deliver on testbeds and case studies that can be used for development and validation. This research demonstrates a novel proof of concept Industry 4.0 production system which lays the foundations for future research in DT technologies, process optimisation and manufacturing data analytics. Using a connected system of commercial off-the-shelf cameras to retrofit a standard programmable logic controlled production process, a digital simulation is updated in real time to create the DT. The system can identify and accurately track the product through the production cycle whilst updating the DT in real-time. The implemented system is a lightweight, low cost, customable and scalable design solution which provides a testbed for practical Industry 4.0 research both for academic and industrial research purposes.

A benchmarking study of Indian seaports

2019 ◽  
Vol 13 (1) ◽  
pp. 88-102
Author(s):  
Sajeev Abraham George ◽  
Anurag C. Tumma
Keyword(s):  
Financial Performance ◽  
Future Research ◽  
Data Envelopment ◽  
Operational Parameters ◽  
Two Stage ◽  
Content Type ◽  
The Public ◽  
Port Authorities ◽  
Financial Performance Measures ◽  
The Government

Purpose The purpose of this paper is to benchmark the operational and financial performances of the major Indian seaports to help derive useful insights to improve their performance. Design/methodology/approach A two-stage data envelopment analysis (DEA) methodology has been used with the help of data collected on the 13 major seaports of India. The first stage of the DEA captured the operational efficiencies, while the second stage the financial performance. Findings A window analysis over a period of three years revealed that no port was able to score an overall average efficiency of 100 per cent. The study identified the better performing units among their peers in both the stages. The contrasting results of the study with the traditional operational and financial performance measures used by the ports helped to derive useful insights. Research limitations/implications The data used in the study were majorly limited to the available sources in the public domain. Also, the study was limited to the major seaports which are under the Government of India and no comparisons were carried out with other local or international ports. Practical implications There is a need to prioritize investments and improvement efforts where they are most needed, instead of following a generalized approach. Once the benchmark ports are identified, the port authorities and other relevant stakeholders should work in detail on the factors causing inefficiencies, for possible improvements in performance. Originality/value This paper carried out a two-stage DEA that helped to derive useful insights on operational efficiency and financial performance of the India seaports. A combination of the financial and operational parameters, along with a comparison of the DEA results with the traditional measures, provided a different perspective on the Indian seaport performance. Considering the scarcity of research papers reported in the literature on DEA-based benchmarking studies of seaports in the Indian context, it has the potential to attract future research in this field.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

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