Conferences related to Smart Manufacturing

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2021 IEEE Pulsed Power Conference (PPC)

The Pulsed Power Conference is held on a biannual basis and serves as the principal forum forthe exchange of information on pulsed power technology and engineering.


2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 IEEE International Conference on Robotics and Automation (ICRA)

The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2020 IEEE International Electron Devices Meeting (IEDM)

the IEEE/IEDM has been the world's main forum for reporting breakthroughs in technology, design, manufacturing, physics and the modeling of semiconductors and other electronic devices. Topics range from deep submicron CMOS transistors and memories to novel displays and imagers, from compound semiconductor materials to nanotechnology devices and architectures, from micromachined devices to smart -power technologies, etc.


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Periodicals related to Smart Manufacturing

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Advanced Packaging, IEEE Transactions on

The IEEE Transactions on Advanced Packaging has its focus on the modeling, design, and analysis of advanced electronic, photonic, sensors, and MEMS packaging.


Antennas and Propagation, IEEE Transactions on

Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Components and Packaging Technologies, IEEE Transactions on

Component parts, hybrid microelectronics, materials, packaging techniques, and manufacturing technology.


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Most published Xplore authors for Smart Manufacturing

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Xplore Articles related to Smart Manufacturing

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Parametric study and design of deep learning on leveling system for smart manufacturing

2018 IEEE International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE), 2018

Sheet metal is widely used in the industry for metal forming purposes, such as metal stamping and metal cutting. It is often winded and storage in a coil form for transportation purposes. However, before any manufacturing process such as, cutting, or stamping, leveling is required as the residual stress inside coil is present which can cause distortion to the metal ...


Equipment communication architecture for smart manufacturing

2018 IEEE International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE), 2018

With the rising trend of smart manufacturing. It is also moving toward the better direction of intelligent integration. Equipment communication creates high connectivity in their information exchange. The standard protocol could lower cost of building equipment and increase the efficiency of production line communication. This paper introduces the basic equipment communication architecture of smart manufacturing.


Smart Manufacturing Stakeholders and Their Requirements

2018 e-Manufacturing & Design Collaboration Symposium (eMDC), 2018

An important maxim of performance management is “You get what you measure.” This is largely true whether you are talking about employees, organizations, processes, time management, sports teams, or - to highlight a current global industry topic - Smart Manufacturing.The techniques for measuring the performance of a Smart Manufacturing facility are like those in regular use at most production factories: ...


The Development of Smart Manufacturing and Cases Study in Taiwan

2018 IEEE International Conference on Advanced Manufacturing (ICAM), 2018

This study was aimed at evaluating the smart manufacturing and cases study in Taiwan. The industry is transforming to focus on smart technologies, high customization, and integration of total solutions. In 2016, The President of Taiwan had announced the policy of “Smart machinery Innovative Industry” initiative, according to the statistics of the International Trade Centre database, the export value of ...


An assessment framework for smart manufacturing

2018 20th International Conference on Advanced Communication Technology (ICACT), 2018

This paper proposes an assessment framework for smart manufacturing in terms of the extent of Information & Communication Technologies (ICT) adoption to manufacturing process. For an assessment framework, this paper establishes assessment principles and identifies activities of manufacturing process to be assessed. In addition, maturity levels of smart manufacturing are defined in this paper. Each level has different characteristics and ...


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Educational Resources on Smart Manufacturing

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IEEE.tv Videos

Jim Davis on Deploying IoT in Manufacturing and Supply Chains - WF-IoT 2015
Smart Manufacturing: Embracing the Digital Revolution - Jane Barr at IEEE WIE Forum USA East 2017
Shaping Smarter Cities: The Technical Son Returns
Ultra Reliable Low Latency Communication for 5G New Radio - Rapeepat Ratasuk - 5G Technologies for Tactical and First Responder Networks 2018
IMS 2011 Microapps - Volume Manufacturing Trends for Automotive Radar Devices
Dr. Bernd Kosch on Industrie 4.0 and manufacturing - WF-IoT 2015
Network Slicing, Use Cases and Adoption Challenges - Ilaria Brunelli - 5G World Forum Santa Clara 2018
TechNews: Smart Cities Special Report
IEEE SMART GRID
IEEE Smart Grid World Forum - Klaus Kleinekorte
Smart Grid Vehicular Technology Vision: Possibility and Feasibility of Smart Community from Case Studies - Hiroaki Nishi
Global Distribution Systems for the Smart Grid: Gordon Day
Care Innovations: Toxics In Electronics (com legendas em portugues)
Cyber-Physical ICT for Smart Cities: Emerging Requirements in Control and Communications - Ryogo Kubo
U.S. Department of Energy Advanced Manufacturing Overview - Dev Shenoy: 2016 International Conference on Rebooting Computing
Stephen Mellor: Challenges of Deploying IoT in Manufacturing - WF-IoT 2015
Integrated Photonics Manufacturing Initiative - Michael Liehr Plenary from the 2016 IEEE Photonics Conference
Niobium Manufacturing for Superconductivity - ASC-2014 Plenary series - 5 of 13 - Tuesday 2014/8/12
IEEE Smart Grid: Vision, Mission, Community
Smart Grid Success Story - Wanda Reder - Ignite: Sections Congress 2017

IEEE-USA E-Books

  • Parametric study and design of deep learning on leveling system for smart manufacturing

    Sheet metal is widely used in the industry for metal forming purposes, such as metal stamping and metal cutting. It is often winded and storage in a coil form for transportation purposes. However, before any manufacturing process such as, cutting, or stamping, leveling is required as the residual stress inside coil is present which can cause distortion to the metal forming/cutting process. In conventional coil leveling machines, the machine parameters are often set by machine technicians with many years of experiences. In addition, the optimized machine parameter is achieved by trial and error method or based on experiences. However, the machine parameters are also not exactly trivial due to too many input factors which may cause changes to the outcome result. In the recent years, industry 4.0 and smart manufacturing has been a widely discussed topic in terms of industry manufacturing solutions in many different industrialized countries. In smart manufacturing, communication and interaction between machines have become an important role to improve manufacturing efficiency, flexibility and customization. As smart manufacturing focused on information process through real objects, it is required to digitize the experience through deep learning method. This paper is aimed to describe and study the deep learning application based on coil leveling system. Finally, through this study and experiment verification, analyzes on research directions and prospects of deep learning.

  • Equipment communication architecture for smart manufacturing

    With the rising trend of smart manufacturing. It is also moving toward the better direction of intelligent integration. Equipment communication creates high connectivity in their information exchange. The standard protocol could lower cost of building equipment and increase the efficiency of production line communication. This paper introduces the basic equipment communication architecture of smart manufacturing.

  • Smart Manufacturing Stakeholders and Their Requirements

    An important maxim of performance management is “You get what you measure.” This is largely true whether you are talking about employees, organizations, processes, time management, sports teams, or - to highlight a current global industry topic - Smart Manufacturing.The techniques for measuring the performance of a Smart Manufacturing facility are like those in regular use at most production factories: Key Performance Indicators (KPIs). The major differences are the number of stakeholder types responsible for achieving the KPI targets, and the breadth of available technologies they can apply in the process.Given the level of automation in today's leading semiconductor manufacturing plants, the most important tools these stakeholders have are the manufacturing applications that provide data analysis, decision support, production scheduling, process monitoring and control, yield management, and a host of other capabilities necessary for running a profitable enterprise in a hyper-competitive industry. In a Smart Manufacturing environment, these applications may interact not only with physical entities in the factory, but also components of its so-called “digital twin” to perform their functions.However, regardless of the overall system architecture or specific technologies used in these applications, they all depend on good data... and lots of it. And most of this data comes directly from the manufacturing equipment, which may number in the thousands for a high-volume factory. As a result, the importance of rich equipment models and robust integration standard for accessing that information cannot be overstated.This relationship between the KPIs, stakeholders, applications, and equipment is shown in Figure 1 below.

  • The Development of Smart Manufacturing and Cases Study in Taiwan

    This study was aimed at evaluating the smart manufacturing and cases study in Taiwan. The industry is transforming to focus on smart technologies, high customization, and integration of total solutions. In 2016, The President of Taiwan had announced the policy of “Smart machinery Innovative Industry” initiative, according to the statistics of the International Trade Centre database, the export value of Taiwan's machinery industry was ranked 17th in the world in 2016 years, and the progress reached the 15th in the world in 2017 years. The global ranking increased by 2. According to Gardner's statistics report in 2016, the global export ranking of Taiwan's machine tools was upgraded from the 5th to the 4th. From the above important data, the Taiwan government's smart machinery program has shown initial results.Finally, this paper introduce 4 cases of smart manufacturing system solutions in Taiwan are as follow: Printed circuit board industry, Machine tool, Vehicle industry, Textile industry. Through smart manufacturing, turning over the previous company image as a foundry, improving the working environment, and enhancing the productivity and competitiveness of related industries.

  • An assessment framework for smart manufacturing

    This paper proposes an assessment framework for smart manufacturing in terms of the extent of Information & Communication Technologies (ICT) adoption to manufacturing process. For an assessment framework, this paper establishes assessment principles and identifies activities of manufacturing process to be assessed. In addition, maturity levels of smart manufacturing are defined in this paper. Each level has different characteristics and different extent of ICT adoption in manufacturing process. Based on an assessment reference model, this paper gives a way of creating assessment indicators for each activities per each maturity levels. With answers to questionnaires/indicators, smart manufacturing can be assessed and expressed as a maturity level.

  • Status of Smart Manufacturing in the United States

    Smart Manufacturing (SM) has been widely recognized as a groundbreaking advanced manufacturing trend that will revolutionize the manufacturing industries and profoundly influence human society. Although the Industry 4.0-based Smart Manufacturing has been a conversation topic for many manufacturing media, strategists, and leaders, many in the field are uncertain what SM entails, its importance, or how it is even relevant to their organizations. Programs in deploying SM technologies have been under development in Germany, European Union, and Korea since 2011. This paper investigates the current status of Smart Manufacturing in the United States, and the trends in its technologies such as Industrial Internet of Things and artificial intelligence in standardized industrial robotics.

  • Towards a Cloud-Based Controller for Data-Driven Service Orchestration in Smart Manufacturing

    The orchestration of smart manufacturing service operations and processes arises as a challenging step in the realization of the Industry 4.0 vision. This paper presents the work in progress towards the specifications of a controlling environment for data-driven orchestration of software services in future smart manufacturing scenarios. The paper discusses the role and significance of multi-aspect data in the management of manufacturing operations and proposes a reference architecture for controlling the orchestration of the respective data services, following the work that has been conducted in the context of the EU-funded project DISRUPT.

  • Poster Abstract: IoT Platform for Engineering Education and Research (IoT PEER)--Applications in Secure and Smart Manufacturing

    A small-scale IoT testbed called IoT PEER (IoT Platform for Engineering Education and Research) was built at Tennessee Tech for both research and education. Currently, this testbed is being used in studying security and smart manufacturing related topics. In this poster we report two Industrial IoT (IIoT) case studies: 1) Machinery Health Monitoring (MHM), and 2) Intrusion Detection in Industrial/Manufacturing Environment. System design and architecture along with preliminary results are provided.

  • Research on Application of Virtual-Real Fusion Technology in Smart Manufacturing

    With the development of information technology, intelligence has attracted more and more attention. This paper takes workshop of the gear ring of car as the research object, and optimizes the facility layout and logistics system of the workshop based on the virtual real fusion and smart manufacturing technology. By using eM-Plant logistics simulation software to simulate the logistics of the workshop, which can analyze the logistics bottlenecks in the workshop, optimize the efficiency and reduce the energy consumption. According to the optimization results to complete the mapping of the virtual workshop to the physical workshop.

  • WiP: An Architecture for Disruption Management in Smart Manufacturing

    This paper reports the work in progress towards the specification of a conceptual architecture of a smart system for supporting the management of disruptions in the manufacturing domain. In particular, it proposes an approach to the description of the system architecture based on a number of interrelated viewpoints following the pertinent ISO 42010 standard. The approach is being developed in the context of the EU-funded H2020 DISRUPT project aiming to deliver a comprehensive data-driven solution for automated vertical and horizontal integration facilitating the transition into smart manufacturing.



Standards related to Smart Manufacturing

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No standards are currently tagged "Smart Manufacturing"


Jobs related to Smart Manufacturing

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