Author
John J. H. Sun
Bio: John J. H. Sun is an academic researcher from National Tsing Hua University. The author has contributed to research in topics: Standardization & Industry 4.0. The author has an hindex of 4, co-authored 4 publications receiving 325 citations.
Papers
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TL;DR: A systematic approach to review IoT technology standards and patents is depicted and the essential standard landscape and the patent landscape based on the governing standards organizations for America, Europe and China where most global manufacturing bases are located are reviewed.
268 citations
TL;DR: The emerging I 4.0 standards from the International Organization for Standardization, the International Electrotechnical Commission, and China's Guobiao standards are covered followed by a patent analysis covering global patents issued in the U.S., Europe, China, and the World Intellectual Property Organization.
Abstract: Cyber-physical systems (CPS) are a collection of transformative technologies for managing interconnected physical and computational capabilities. Recent developments in technology are increasing the availability and affordability of sensors, data acquisition systems, and computer networks. The competitive nature of industry requires manufacturers to implement new methodologies. CPS is a broad area of engineering which supports applications across industries, such as manufacturing, healthcare, electric power grids, agriculture, and transportation. In particular, CPS is the core technology enabling the transition from Industry 3.0 to Industry 4.0 (I 4.0) and is transforming global advanced manufacturing. This paper provides a consolidated review of the latest CPS literature, a complete review of international standards, and a complete analysis of patent portfolios related to the 5C’s CPS architecture model by Lee et al. The critical evaluation of international standards and the intellectual property contained in CPS patents is unaddressed by the previous research and will benefit both academic scholars and industry practitioners. The analysis provides a basis for predicting research and development future trends and helps policy makers manage technology changes that will result from CPS in I 4.0. This paper covers the emerging I 4.0 standards from the International Organization for Standardization, the International Electrotechnical Commission, and China’s Guobiao standards followed by a patent analysis covering global patents issued in the U.S., Europe, China, and the World Intellectual Property Organization.
142 citations
TL;DR: A deep learning analytical method is applied for automatic and intelligent patent value estimation and demonstrates the improved results of building PCA-preprocessed DNN models to perform patent valuations of manufacturing Internet of Things patents.
Abstract: The R&D output and global commercialization of intellectual properties (IPs), especially patents filed in many countries, have increased dramatically over the past decade. The overwhelming growth in research and IP activities has led to a major challenge to understand and forecast technology development insights and trends. Evidence-based data analytics is essential for technology mining. The assessment of patent values is a critical aspect of technology mining, which remains a highly subjective task performed by domain experts. As businesses become globalized, subjectivity in underlying assessments of large volumes of patent documents leads to overpriced or undervalued IP sales or licensing that exposes stakeholders to legal and financial risks. Thus, the development of intelligent methods for patent valuation requires new research emphasis. This article applies a deep learning analytical method for automatic and intelligent patent value estimation. Principal component analysis (PCA) is used to identify significant patent value indicators from the given patent dataset. Then, deep neural networks (DNN) for value prediction are modeled and trained using the training set. A detailed case study of 6466 manufacturing Internet of Things (IoT) patents is analyzed to demonstrate the improved results of building PCA-preprocessed DNN models to perform patent valuations. Finally, selected higher value IoT patents owned by leading Taiwan assignees are identified and analyzed to verify the technological competitive intelligence.
28 citations
12 Oct 2017
TL;DR: The aim of this article is to provide the methodology and analysis methods for IoT patent TFM and introduce computer supported IP and patent knowledge e-discovery.
Abstract: Patent analysis helps companies understand their intellectual property (IP) portfolio and develop competitive marketing and management strategies. A Technology Function Matrix (TFM) is a critical approach for patent data analytics. This paper develops a generic computer supported TFM construction methodology that can be used for creating patent technical maps for any given domain. The approach is adopted for the case of the Internet of Things (IoT) patent technology analysis in the context of Industry 4.0 [1]. The aim of this article is to provide the methodology and analysis methods for IoT patent TFM and introduce computer supported IP and patent knowledge e-discovery.
6 citations
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TL;DR: The state of the art in the area of Industry 4.0 as it relates to industries is surveyed, with a focus on China's Made-in-China 2025 and formal methods and systems methods crucial for realising Industry 5.0.
Abstract: Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines ...
1,780 citations
TL;DR: The impact of IoT and CPSs on industrial automation from an industry 4.0 perspective is reviewed, a survey of the current state of work on Ethernet time-sensitive networking (TSN) is given, and the need for harmonization beyond networking is pointed out.
Abstract: With the introduction of the Internet of Things (IoT) and cyberphysical system (CPS) concepts in industrial application scenarios, industrial automation is undergoing a tremendous change. This is made possible in part by recent advances in technology that allow interconnection on a wider and more fine-grained scale. The purpose of this article is to review technological trends and the impact they may have on industrial communication. We will review the impact of IoT and CPSs on industrial automation from an industry 4.0 perspective, give a survey of the current state of work on Ethernet time-sensitive networking (TSN), and shed light on the role of fifth-generation (5G) telecom networks in automation. Moreover, we will point out the need for harmonization beyond networking.
1,242 citations
TL;DR: A novel concept of digital twin shop-floor (DTS) based on digital twin is explored and its four key components are discussed, including physicalShop-floor, virtual shop- Floor, shop- floor service system, and shop-ground digital twin data.
Abstract: With the developments and applications of the new information technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, a smart manufacturing era is coming. At the same time, various national manufacturing development strategies have been put forward, such as Industry 4.0 , Industrial Internet , manufacturing based on Cyber-Physical System , and Made in China 2025 . However, one of specific challenges to achieve smart manufacturing with these strategies is how to converge the manufacturing physical world and the virtual world, so as to realize a series of smart operations in the manufacturing process, including smart interconnection, smart interaction, smart control and management, etc. In this context, as a basic unit of manufacturing, shop-floor is required to reach the interaction and convergence between physical and virtual spaces, which is not only the imperative demand of smart manufacturing, but also the evolving trend of itself. Accordingly, a novel concept of digital twin shop-floor (DTS) based on digital twin is explored and its four key components are discussed, including physical shop-floor, virtual shop-floor, shop-floor service system, and shop-floor digital twin data. What is more, the operation mechanisms and implementing methods for DTS are studied and key technologies as well as challenges ahead are investigated, respectively.
741 citations
TL;DR: The results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things and there is still absence of real applications in the field of production planning.
Abstract: Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional ...
673 citations
TL;DR: The Industry 4.0 environment is scanned on this paper, describing the so-called enabling technologies and systems over the manufacturing environment.
586 citations