Wind Power Systems
Applications of Computational Intelligence
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Article
Hyper-automation in manufacturing industry
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Article
Manufacturing metaverse
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Chapter
Smart Manufacturing
Main concepts of smart manufacturing such as digitization, service orientation, sustainability, resilience, openness, and integration are discussed. Manufacturing enterprises will deploy these concepts to a di...
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Article
Active label-denoising algorithm based on broad learning for annotation of machine health status
Deep learning has led to tremendous success in machine maintenance and fault diagnosis. However, this success is predicated on the correctly annotated datasets. Labels in large industrial datasets can be noisy...
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Article
Universal manufacturing: data, resiliency, and sustainability linkages
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Article
Extreme science and engineering
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Article
Resilient manufacturing
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Article
Service manufacturing = Process-as-a-Service + Manufacturing Operations-as-a-Service
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Article
Editorial: Intelligent manufacturing: bridging two centuries
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Article
Data-driven modeling of truck engine exhaust valve failures: A case study
Exhaust valve is an essential part of truck engine. Dynamic and unpredictable thermal and mechanical stress cause valves to wear prematurely, leading to increased maintenance costs. In this paper, a data-drive...
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Article
Smart manufacturing must embrace big data
Study and model industrial processes to save money, energy and materials, urges Andrew Kusiak.
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Article
Optimizing wastewater pum** system with data-driven models and a greedy electromagnetism-like algorithm
Optimizing a pum** system in the wastewater treatment process by improving its operational schedules is presented. The energy consumption and outflow rate of the pum** system are modeled by a data-driven ...
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Article
Put innovation science at the heart of discovery
The success rate of discoveries would be improved if we could find out how to innovate, argues Andrew Kusiak.
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Article
Renewables: Share data on wind energy
Giving researchers access to information on turbine performance would allow wind farms to be optimized through data mining, says Andrew Kusiak.
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Article
Short-term prediction of influent flow in wastewater treatment plant
Predicting influent flow is important in the management of a wastewater treatment plant (WWTP). Because influent flow includes municipal sewage and rainfall runoff, it exhibits nonlinear spatial and temporal b...
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Article
Prediction of methane production in wastewater treatment facility: a data-mining approach
A prediction model for methane production in a wastewater processing facility is presented. The model is built by data-mining algorithms based on industrial data collected on a daily basis. Because of many par...
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Article
A data-mining approach to predict influent quality
In wastewater treatment plants, predicting influent water quality is important for energy management. The influent water quality is measured by metrics such as carbonaceous biochemical oxygen demand (CBOD), po...
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Book
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Chapter
Improving Combustion Performance by Online Learning
In this chapter, combustion process is improved by computing control settings with clustering algorithms. The framework involves learning from a high-dimensional data stream generated by the combustion process...
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Chapter and Conference Paper
EI2N 2008 PC Co-chairs’ Message
It is a fact that enterprises need to collaborate in order to prosper in the current extremely dynamic and heterogeneous business environment. Enterprise integration, interoperability and networking are the ma...
