Special Issue Description
In general, Industrial Artificial Intelligence (IAI) refers to the application of artificial intelligence to industrial automation. Different from general artificial intelligence, industrial AI narrows down the scope of AI research fields to building intelligent systems that resolve engineering problems with human-like intelligence. Industrial AI stresses more applications rather than AI concept or framework development and highlights the value of AI solution to specific process industry, including causality identification between input-output variables, state or product quality estimate, retrieval and reasoning of interesting cases, motif discovery from the closed-loop system for monitoring, fault diagnosis and detection, soft-sensing, parameter, structure and process optimization, planning and coordination, dynamical system modelling and control.
IAI has received sufficiently technical supports from sensing techniques, more powerful computing facilities and stronger communication infrastructure. However, one should be aware that these technologies mentioned above may create some business values only if the problems in industry can be well studied and formulated. Understanding the domain-based AI (DBAI) concept is important and meaningful to AI community, and one cannot expect much of AI technologies without knowing the application background in depth, the data nature, and dynamics and constraints of the variables. IAI, as a member of DBAI family, will play a key role in contributing to product and service innovation, process improvement, and insightful discovery, and will eventually become an unstoppable driver for the transformation of economy and business opportunities.
This special issue aims to highlight IAI concept, research scopes and recently technical advancements in industrial data analytics, and make the IAI concept more visible in AI community. Original contributions, including industrial data driven machine learning techniques, advanced fuzzy logic systems, online optimization algorithms, real-world case studies on industrial applications, and comprehensive surveys with directions, are cordially welcome. Through this special issue, some fundamental concepts and associated AI techniques for IAI will be further focused and promoted.
About the issue
The topics of this special issue include, but are not limited to:
Identification of input-output causality from noisy big industrial data
Computational intelligence and machine learning techniques for soft-sensors and predictive modelling
Time-series forecasting, and interval estimate for industrial data
Learning-based reasoning techniques for industrial applications
AI-driven operational optimization and decision-making
AI-based methods for process monitoring, abnormality detection and fault analysis
AI-based planning and scheduling for process industries
Case studies of AI technology for problem solving in process industries, chemical engineering, power systems, industrial robotics, maritime engineering, transportation engineering, civil engineering, and intelligent software engineering
Papers will be evaluated based on their originality, presentation, relevance and contribution to the development of industrial artificial intelligence, as well as their suitability and the quality in terms of both technical contribution and writing. The submitted papers must be written in excellent English and describe original research which has neither been published nor currently under review by other journals or conferences. Previously published conference papers should be clearly identified by the authors (at the submission stage) and an explanation should be provided how such papers have been extended to be considered for this special issue. Guest Editors will make an initial judgement of the suitability of submissions to this special issue. Submissions that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be proceeded for paper review and the authors will be promptly informed in such cases. Author guidelines for preparation of manuscript can be found at www.elsevier.com/locate/ins
All manuscripts and any supplementary material should be submitted through Elsevier Editorial System (EES). The authors must select as \”Special Issue: Advances in Industrial Artificial Intelligence (AIAI)\” when they identify the ”Article Type\” step in the submission process. The EES website is located at http://ees.elsevier.com/ins/
Guide for Authors
This site will guide you stepwise through the creation and uploading of your article. The guide for authors can be found on the journal homepage (www.elsevier.com/ins).
Deadline of initial submission: September 30, 2019
Revised version submission: December 30, 2019
Acceptance notification: June 30, 2020
Final manuscripts due: July 30, 2020
Anticipated publication: September 2020
Dianhui Wang, La Trobe University, Melbourne, VIC 3086, Australia
Tianyou Chai, Northeastern University, Shenyang 110819, China