industrial process control
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Author(s):  
Zermane Hanane ◽  
Mouss Hayet ◽  
Benaicha Sonia

The automation of manufacturing systems is a major obligation to the developments because of exponential industrial equipment, and programming tools, so that growth needs and customer requirements. This automation is achieved in our work through the application programming tools from Siemens, which are PCS 7 (Process Control System) for industrial process control and FuzzyControl++ for fuzzy control. An industrial application is designed, developed and implemented in the cement factory in Ain-Touta (S.CIM.AT) located in the province of Batna, East of Algeria. Especially in the cement mill which gives the final product that is the cement.


2021 ◽  
Vol 40 (2) ◽  
Author(s):  
F. W. Panella ◽  
A. Pirinu

AbstractSeveral studies demonstrate the effectiveness of pulsed thermography for detection and visualization of sub-superficial flaws in composites. Continuous improvement of thermal data manipulation makes active thermography an attractive and powerful inspection method for industrial process control and maintenance aims. Therefore, temperature image-processing is the major ongoing challenge in the thermographic research field. However, the particular interest for thermographic inspections is to be more addressed to its simple and relatively fast industrial application; an appropriate image processing tool should be implemented and verified on industrial components, containing manufacturing and in-service defects. In the proposed research, well-established and previously proposed methods were analysed and compared for different defect typology inside three CFRP components. The main goal is not solely focused on establishing the suitable data processing approach, providing detection limits of processed data in terms of damage type, size and distribution. The aim of proposed work is to present detailed examples of thermal imaging methods applied on similar critical defects, evaluating different results among methods in terms of defects mapping capabilities and Tanimoto evaluation criterion, coupled also with the signal-to-noise ratio as assessment of defect detectability.


2021 ◽  
Vol 2(50) ◽  
Author(s):  
Andrey Stopakevych ◽  
◽  
Aleksey Stopakevych ◽  

The aims of the research are increasing resiliency of industrial process control systems, the de-velopment of methods of creating resilient industrial process control systems and creating a resil-ient control system of the distillation column for the production of food alcohol. The set of ob-jectives were achieved without the use of hardware backup, but using the developed algorithms which were based on the use of the model of dynamics of technological plants in the software of the control system and modern theory of multivariable automatic control systems. The opti-mal linear-quadratic controller with disturbances model and a state observer was used as a full controller. The most important result was improvement of the survivability of industrial process control systems using the developed algorithm. Also, the resilient distillation column control sys-tem was developed. For the further researches significant results are formulas which allow de-fining new mode values of controls in a distillation column at failure event of corresponding control output channels and formulas of logic algebra for a choice of optimum configuration of control system of a distillation column of food spirit industry. The basis of the developed tech-nique was reconfiguration of the control system with inclusion, instead of the failed, additional devices, which were not being used in a current configuration, but were carried out the similar function taking into account dynamics coupling of a technological plant. The significance of these results is that they can be applied to the development of cyber-production systems that do not require permanent maintenance by personnel.


Author(s):  
Inés Tejado ◽  
Emiliano Pérez ◽  
José Emilio Traver ◽  
Cristina Nuevo-Gallardo ◽  
Paloma Rodríguez ◽  
...  

Author(s):  
Aishwaryadev Banerjee ◽  
Swagata Maity ◽  
Carlos H. Mastrangelo

Biosensors are essential tools which have been traditionally used to monitor environmental pollution, detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from the in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single-biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yanghua Gao ◽  
Weidong Lou ◽  
Hailiang Lu

This paper explores deep into the collaborative scheduling of common rail dual automatic guided vehicles (AGVs). Firstly, a dual AGV scheduling model was constructed to minimize the overall time of material distribution. Then, a novel scheduling algorithm was developed to dynamically plan the orders based on time windows. To effectively minimize the distribution time, heuristic algorithms were adopted to initialize the distribution order of materials. On this basis, the collaboration between the two AGVs was innovatively designed based on dynamic planning and time windows, making up for the defects of traditional methods in AGV cooperation. This greatly shortens the running time of the entire system in material distribution. The computing results fully demonstrate the efficiency and rationality of our algorithm. Finally, our algorithm was proved to be superior to the benchmark method through experiments on actual industrial instances.


2021 ◽  
Vol 54 (21) ◽  
pp. 121-126
Author(s):  
L.L. Rokebrand ◽  
J.J. Burchell ◽  
L.E. Olivier ◽  
I.K. Craig

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