Big Data enabled Intelligent Immune System for energy efficient manufacturing management

Wang, Sheng; Liang, Yuchen; Li, Weidong; Cai, Xiantao

doi:10.1016/j.jclepro.2018.05.203

Cited by 71 publications

(29 citation statements)

References 31 publications

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“…Japan has a consistent global technology research foundation and by looking at the fuzzy sets implementation in Japan, one can see they are far ahead of the competition on decision-making schemas [16,25]. Numerous international countries are participating in brain-inspired decision-making to improve life in their country [23,26].…”

Section: Brain-inspired Decision-making For Businessmentioning

confidence: 99%

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Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Alexander¹,

Wang²

2020

JBMS

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Brain science and brain-inspired artificial intelligence have the potential for strengthening business and management. Brain-inspired artificial intelligence (AI) uses principles of brain science to build algorithms and AI systems with human-like intelligence. Some concepts (e.g., cognition, inference, memory, and intelligence) and principles of brain science are introduced in this paper. The research progress in several topics are also presented that include brain-inspired artificial intelligence and brain-inspired computing, project management and brain-inspired management, the integration of brain science into leadership (especially crisis leadership), and brain-inspired decision-making for business. Future research and trends in some topics are introduced.

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Section: Brain-inspired Decision-making For Businessmentioning

confidence: 99%

“…Other researchers looked at specific parts of the brain such as the amygdala and psychology to develop a decision-making plan [16,21]. Future research is still necessary to present all the decision-making centers within the brain and all the factors which influence them [26].…”

Section: Brain-inspired Decision-making For Businessmentioning

confidence: 99%

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Alexander¹,

Wang²

2020

JBMS

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“…Later, Liang et al [104]adopted the Fruit Fly Optimisation and proposed the novel cyber physical system for machining optimisation during the manufacturing lifecycle. Another framework named the Intelligent Immune System is introduced in [105]. It was also designed for improving productivity and energy saving, employed artificial neural networks for identifying abnormal patterns and planted the re-scheduling algorithm for follow-up processing.…”

Section: Other Advanced Supportsmentioning

confidence: 99%

Big Data and Climate Change

Hassani

Huang

Silva

2019

BDCC

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Climate science as a data-intensive subject has overwhelmingly affected by the era of big data and relevant technological revolutions. The big successes of big data analytics in diverse areas over the past decade have also prompted the expectation of big data and its efficacy on the big problem—climate change. As an emerging topic, climate change has been at the forefront of the big climate data analytics implementations and exhaustive research have been carried out covering a variety of topics. This paper aims to present an outlook of big data in climate change studies over the recent years by investigating and summarising the current status of big data applications in climate change related studies. It is also expected to serve as a one-stop reference directory for researchers and stakeholders with an overview of this trending subject at a glance, which can be useful in guiding future research and improvements in the exploitation of big climate data.

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“…Other important applications developed due to the availability of real time data are the prediction of energy consumption, especially critical for building management [34][35][36][37][38][39][40][41] and electrical load management [42][43][44][45][46][47][48][49][50][51][52][53][54], and the forecast of energy production by renewable energy systems (mostly used for wind turbines and photovoltaic panels) [55][56][57][58][59].…”

Section: Introductionmentioning

confidence: 99%

Real Time Energy Performance Control for Industrial Compressed Air Systems: Methodology and Applications

et al. 2019

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Most manufacturing and process industries require compressed air to such an extent that in Europe, for instance, about 10% of the total electrical energy consumption of industries is due to compressed air systems (CAS). However, energy efficiency in compressed air production and handling is often ignored or underestimated, mainly because of the lack of awareness about its energy consumption, caused by the absence of proper measurements on CAS in most industrial plants. Therefore, any effective energy saving intervention on generation, distribution and transformation of compressed air requires proper energy information management. In this paper we demonstrate the importance of monitoring and controlling energy performance in compressed air generation and use, to enable energy saving practices, to enhance the outcomes of energy management projects, and to obtain additional benefits for non-energy-related activities, such as operations, maintenance management and energy accounting. In particular, we propose a novel methodology based on measured data, and baseline definition through statistical modelling and control charts. The proposed methodology is tested on a real compressed air system of a pharmaceutical manufacturing plant in order to verify its effectiveness and applicability.

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Big Data enabled Intelligent Immune System for energy efficient manufacturing management

Cited by 71 publications

References 31 publications

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Big Data and Climate Change

Real Time Energy Performance Control for Industrial Compressed Air Systems: Methodology and Applications

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