Integrated design of agricultural and industrial processes: A case study of combined sugar and ethanol production
Sign Up to like & getrecommendations! Published in 2017 at "Aiche Journal"
DOI: 10.1002/aic.15374
Abstract: Bioethanol production from molasses has advantages in greenhouse gas emissions because of its energy acquisition from bagasse. However, the improvement of bioethanol productivity is challenging; while each elemental technology option can be greatly improved, the… read more here.
Keywords: production; agricultural industrial; case; industrial processes ... See more keywords
Mining lipolytic enzymes in community DNA from high Andean soils using a targeted approach
Sign Up to like & getrecommendations! Published in 2017 at "Antonie van Leeuwenhoek"
DOI: 10.1007/s10482-017-0877-8
Abstract: Microbial enrichments cultures are a useful strategy to speed up the search for enzymes that can be employed in industrial processes. Lipases have gained special attention because they show unique properties such as: broad substrate… read more here.
Keywords: high andean; andean soils; industrial processes; enzymes community ... See more keywords
Production capacity identification and analysis using novel multivariate nonlinear regression: Application to resource optimization of industrial processes
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Cleaner Production"
DOI: 10.1016/j.jclepro.2020.124469
Abstract: Abstract Production capacity identification and analysis in industrial processes plays a more and more important role at home and abroad, which not only can improve the energy efficiency, but also reduce the carbon emission. However,… read more here.
Keywords: industrial processes; capacity identification; production; production capacity ... See more keywords
Optimizing resource flow of industrial processes, with a case study of zero liquid discharge at a copper smelting plant
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Cleaner Production"
DOI: 10.1016/j.jclepro.2020.125452
Abstract: Abstract The transition towards circular flows within industrial processes often involves assessment of only one type of flow. For example, zero liquid discharge sometimes focuses on water flows, without taking into consideration solid residues. It… read more here.
Keywords: zero liquid; methodology; study; industrial processes ... See more keywords
Psychrophiles: A source of cold-adapted enzymes for energy efficient biotechnological industrial processes
Sign Up to like & getrecommendations! Published in 2020 at "Journal of environmental chemical engineering"
DOI: 10.1016/j.jece.2020.104607
Abstract: Abstract Biocatalysts are the backbone of bioprocessing industries that are going through a phase of transition with reference to the requirement of extraordinary enzymes for various biochemical processes. This transition is well reported and documented… read more here.
Keywords: energy; source cold; industrial processes; psychrophiles source ... See more keywords
Data-driven modeling and analysis based on complex network for multimode recognition of industrial processes
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Manufacturing Systems"
DOI: 10.1016/j.jmsy.2021.04.001
Abstract: Abstract An industrial process usually has multiple operating conditions or periods due to various factors such as the fluctuation of raw material quality, differences of worker levels, and changes of product specifications. Industrial data from… read more here.
Keywords: industrial processes; multimode recognition; complex network; recognition industrial ... See more keywords
Ensemble deep relevant learning framework for semi-supervised soft sensor modeling of industrial processes
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.07.086
Abstract: Abstract Deep learning has been growing in popularity for soft sensor modeling of nonlinear industrial processes, infeuality-related variables. However, applications may be highly nonlinear, and the quantity of labeled samples is considerably limited. The extraction… read more here.
Keywords: industrial processes; sensor modeling; ensemble deep; soft sensor ... See more keywords
Simulation, through discrete events, of industrial processes in productive environments
Sign Up to like & getrecommendations! Published in 2017 at "Procedia Manufacturing"
DOI: 10.1016/j.promfg.2017.09.137
Abstract: Abstract This paper explains the simulation of a production cell using discrete event simulation. The production cell is included in a car factory, specifically in the body shop and belongs to the facility of the… read more here.
Keywords: discrete events; simulation discrete; system; industrial processes ... See more keywords
Multi-objective optimization of costs and energy efficiency associated with autonomous industrial processes for sustainable growth
Sign Up to like & getrecommendations! Published in 2021 at "Technological Forecasting and Social Change"
DOI: 10.1016/j.techfore.2021.121115
Abstract: Abstract Digital technologies are transforming the industrial landscape and disrupting traditional business models. New business opportunities related to Industry 4.0 are emerging, so companies must adapt to the new environment. This work puts forward a… read more here.
Keywords: methodology; energy; autonomous industrial; industrial processes ... See more keywords
Incipient Fault Detection for Complex Industrial Processes with Stationary and Nonstationary Hybrid Characteristics
Sign Up to like & getrecommendations! Published in 2018 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.8b00233
Abstract: For a nonstationary process which has a time-varying mean, a time-varying variance, or both, it can be difficult to detect incipient disturbances which may be hidden by the time-varying process variations. Besides, stationary and nonstationary… read more here.
Keywords: nonstationary hybrid; complex industrial; industrial processes; process ... See more keywords
Nonlinear Dynamic Soft Sensor Development with a Supervised Hybrid CNN-LSTM Network for Industrial Processes
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c01108
Abstract: A soft sensor is a key component when a real-time measurement is unavailable for industrial processes. Recently, soft sensor models based on deep-learning techniques have been successfully applied to complex industrial processes with nonlinear and… read more here.
Keywords: network; lstm; cnn; soft sensor ... See more keywords