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Books > Professional & Technical > Industrial chemistry & manufacturing technologies > General
Industrial internet of things (IIoT) is changing the face of
industry by completely redefining the way stakeholders,
enterprises, and machines connect and interact with each other in
the industrial digital ecosystem. Smart and connected factories, in
which all the machinery transmits real-time data, enable industrial
data analytics for improving operational efficiency, productivity,
and industrial processes, thus creating new business opportunities,
asset utilization, and connected services. IIoT leads factories to
step out of legacy environments and arcane processes towards open
digital industrial ecosystems. Innovations in the Industrial
Internet of Things (IIoT) and Smart Factory is a pivotal reference
source that discusses the development of models and algorithms for
predictive control of industrial operations and focuses on
optimization of industrial operational efficiency, rationalization,
automation, and maintenance. While highlighting topics such as
artificial intelligence, cyber security, and data collection, this
book is ideally designed for engineers, manufacturers,
industrialists, managers, IT consultants, practitioners, students,
researchers, and industrial industry professionals.
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Journal; Index 83-104
(Hardcover)
London Iron and Steel Institute, London Tra Iron and Steel Institute, London Car Iron and Steel Institute
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R1,113
Discovery Miles 11 130
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Ships in 12 - 19 working days
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Process systems engineering (PSE) is a discipline that delivers
tools for guided decision-making in the development of new
processes and products. Proven successful in the pharmaceutical-,
food- and water sectors, it has also breached the field of energy
systems. The future energy systems aim to be more efficient,
cost-effective, environmentally benign, and interconnected. The
design and operation is extremely challenging for decision-makers,
engineers, and scientists and here lies a crucial role for the
process systems engineer.
Ozonation and Biodegradation in Environmental Engineering: Dynamic
Neural Network Approach gives a unified point-of-view on the
application of DNN to estimate and control the application of
ozonation and biodegradation in chemical and environmental
engineering. This book deals with modelling and control design of
chemical processes oriented to environmental and chemical
engineering problems. Elimination in liquid, solid and gaseous
phases are all covered, along with processes of laboratory scale
that are evaluated with software sensors and controllers based on
DNN technique, including the removal of contaminants in residual
water, remediation of contaminated soil, purification of
contaminated air, and more. The book also explores combined
treatments using both ozonation and biodegradation to test the
sensor and controller.
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