OMSM 2018 - Special Session on Optimization and Management in Smart Manufacturing
Date2018-06-10 - 2018-06-15
Deadline2018-01-15
VenueKalamata, Greece
Keywords
Websitehttps://www.caopt.com/LION12
Topics/Call fo Papers
Organizers:
Dr. Panos M. Pardalos, , University of Florida, USA
Dr. Xinbao Liu, , School of Management, Hefei University of Technolog, China
Dr. Jun Pei, , School of Management, Hefei University of Technolog, China
Description:
Current global science and technology innovation shows some new development trends and characteristics. Emerging information technology such as internet and big data technology are widely permeated which drives the group technology revolution characterized by green, intelligent, and ubiquitous in almost all the areas. Intelligentization, greenization, servitization, and interconnection are becoming important for the development and revolution of manufacturing industry. Interdisciplinary and networked innovative platform is reforming the innovation system of traditional manufacturing industry. A new green manufacturing system based on the value network is forming. This session aims to apply data-driven resource management and optimization technique to offer theory support for the management revolution, business pattern revolution, decision theories and methods innovation, and intelligent decision system construction.
Topics of interest include but are not limited to:
Network Manufacturing
Sustainability Manufacturing Strategy Management
Sustainability Supply Chain Operations Management
R&D project management of high-end equipment
Environmental and Sustainability Assessment
Operations Management of Smart Factory
Behavioral Operations Management
Production engineering management of high-end equipment
Inventory Planning and Control of Green Products
Green Logistics Operation and Management
Service engineering management of high-end equipment
Remanufacturing engineering management of high-end equipment
Quality Management Based on Industrial Big Data
Development Management of Renewable Energy Technologies
Big Data Applications in Smart Manufacturing
Dr. Panos M. Pardalos, , University of Florida, USA
Dr. Xinbao Liu, , School of Management, Hefei University of Technolog, China
Dr. Jun Pei, , School of Management, Hefei University of Technolog, China
Description:
Current global science and technology innovation shows some new development trends and characteristics. Emerging information technology such as internet and big data technology are widely permeated which drives the group technology revolution characterized by green, intelligent, and ubiquitous in almost all the areas. Intelligentization, greenization, servitization, and interconnection are becoming important for the development and revolution of manufacturing industry. Interdisciplinary and networked innovative platform is reforming the innovation system of traditional manufacturing industry. A new green manufacturing system based on the value network is forming. This session aims to apply data-driven resource management and optimization technique to offer theory support for the management revolution, business pattern revolution, decision theories and methods innovation, and intelligent decision system construction.
Topics of interest include but are not limited to:
Network Manufacturing
Sustainability Manufacturing Strategy Management
Sustainability Supply Chain Operations Management
R&D project management of high-end equipment
Environmental and Sustainability Assessment
Operations Management of Smart Factory
Behavioral Operations Management
Production engineering management of high-end equipment
Inventory Planning and Control of Green Products
Green Logistics Operation and Management
Service engineering management of high-end equipment
Remanufacturing engineering management of high-end equipment
Quality Management Based on Industrial Big Data
Development Management of Renewable Energy Technologies
Big Data Applications in Smart Manufacturing
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- 2018 International Conference on Data Science and Information Technology(DSIT 2018)
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Last modified: 2017-12-29 15:35:08