Design, implementation and evaluation of an expert system for operating regime detection in industrial gas turbine

Nayeri, Mohammad Reza; Araabi, Babak Nadjar; Yazdanpanah, Mohammad Javad; Moshiri, Behzad

doi:10.1016/j.eswa.2022.117332

Cited by 8 publications

(2 citation statements)

References 20 publications

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“…On the other hand, Nayeri et al (2022) point out that technologies in the application of information control are designed to provide information services to all employees of an organization related to decision-making in management. In this case, information is usually presented in the form of a general or special management report and contains information about the past, present, and future of the company.…”

Section: Review Articlementioning

confidence: 99%

Technologies applied to information control in organizations: A review

Panduro

2023

DecisionTech Rev

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In the contemporary global market, organizations face intense competition requiring the deployment of information technology (IT) for effective decision-making and to maintain market presence. This review article emphasizes the crucial role of information technologies in organizational decision-making processes. It outlines the evolution of data management tools, especially in the context of dynamic and contingent data management, and explores the adoption and implementation of technologies for information control within organizations. By analyzing various methodologies and results from existing research, the article illustrates the increasing reliance on IT to enhance organizational processes, decision-making, and overall competitiveness. Furthermore, it delves into the systematic review approach to understand the significance and application of information management technologies in organizational contexts, offering insights for entrepreneurs and academics. The review concludes with the assertion that proper information management through technology is vital for organizations to remain competitive in the ever-changing market landscape.

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Section: Review Articlementioning

confidence: 99%

Technologies applied to information control in organizations: A review

Panduro

2023

DecisionTech Rev

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“…Although literature for the assumed task is limited (especially when considering loaders), the task of operational regimes detection is not. Expert systems are being constantly created that work based on standard linear programming and logic rules, such as the one presented in [ 18 ]. Another trend involving usage of methods from artificial intelligence areas can be observed.…”

Section: Introductionmentioning

confidence: 99%

Haulage Cycles Identification for Wheeled Transport in Underground Mine Using Neural Networks

Skoczylas

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Stefaniak

et al. 2023

Sensors

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The task of ore transportation is performed in all mines, regardless of their type (open pit/underground) or mining process. A substantial number of enterprises utilize wheeled machines to perform ore haulage, especially haul trucks and loaders. These machines’ work consists of repeating cycles, and each cycle can be divided into 4 operations: loading, driving with full box/bucket, unloading and driving with empty box/bucket. Monitoring this process is essential to create analytical tools that support foremen and other management crew in achieving effective and optimal production and planning activities. Unfortunately, information gathered regarding the process is frequently based on operators’ oral testimony. This process not only allows for abuse but is also a repetitive and tedious task that must be performed by foremen. The time and attention of foremen is valuable as they are responsible for managing practically everything in their current mine section (machines, operators, works, repairs, emergencies, safety, etc.). Therefore, the automatization of the described process of information gathering should be performed. In this article, we present two neural network models (one for haul trucks and one for loaders) build for detecting work cycles of the ore haulage process. Both models were built utilizing a 2-stage approach. In the first stage, the models’ structures were optimized, while the second was focused on optimizing hyperparameters for the structure with best performance. Both of the proposed models were trained using data collected from on-board monitoring systems over hundreds of the machines’ work hours and utilized the same input features: vehicle speed, fuel consumption, selected gear and engine rotational speed. Models have been subjected to comprehensive testing during which the efficiency and stability of the model responsible for haul trucks was proven. Results for loaders were not as high quality for haul trucks; however, some interesting facts were discovered that indicate possible directions for future development.

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