Data-Driven Welding Expert System Structure Based on Internet of Things

Author(s):  
Chao Chen ◽  
Na Lv ◽  
Shanben Chen
2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.


Author(s):  
Haiting Huang

In order to explore the application of IoT technology in robots and the promotion of IoT robot technology to the economy, by comparing traditional technology and IoT intelligent robot technology, this article combines it with economic development to analyze the promotion of IoT robot to economic development. Based on the ultra-wideband ranging method, this paper designs an ultra-wideband radio frequency positioning system and applies it to the robot’s positioning process. Moreover, this article combines the application of robots in the current social and economic development to construct the system structure, and conducts functional analysis with manufacturing robots and monitoring robots as the main body. After constructing an intelligent robot based on the Internet of Things technology, by comparing the traditional technology and the intelligent robot technology of the Internet of Things, this article combines it with economic development to analyze the promotion of IoT robot to economic development. From the analysis results of this article, it can be seen that the advancement of IoT robot technology can effectively promote economic development.


2011 ◽  
Vol 128-129 ◽  
pp. 224-228
Author(s):  
Jian Xin Huang ◽  
Ya Qin Bian

Considering the weapon materiel maintenance condition, intelligence theory and method such as expert system and neural network is introduced in BIT technology. BIT intelligence maintenance decision in materiel maintenance field is discussed. The realization of materiel intelligence BIT reflects the concurrent design concept of system exploitation. Level integrated intelligence BIT system organization framework is adopted. BIT comprehensive decision-making and maintenance expert system structure is designed, and its implementation plan based on BIT is offered, which can enhance the fault diagnosis capability of modern complicated weapon materiel.


Author(s):  
Yunpeng Li ◽  
Utpal Roy ◽  
Y. Tina Lee ◽  
Sudarsan Rachuri

Rule-based expert systems such as CLIPS (C Language Integrated Production System) are 1) based on inductive (if-then) rules to elicit domain knowledge and 2) designed to reason new knowledge based on existing knowledge and given inputs. Recently, data mining techniques have been advocated for discovering knowledge from massive historical or real-time sensor data. Combining top-down expert-driven rule models with bottom-up data-driven prediction models facilitates enrichment and improvement of the predefined knowledge in an expert system with data-driven insights. However, combining is possible only if there is a common and formal representation of these models so that they are capable of being exchanged, reused, and orchestrated among different authoring tools. This paper investigates the open standard PMML (Predictive Model Mockup Language) in integrating rule-based expert systems with data analytics tools, so that a decision maker would have access to powerful tools in dealing with both reasoning-intensive tasks and data-intensive tasks. We present a process planning use case in the manufacturing domain, which is originally implemented as a CLIPS-based expert system. Different paradigms in interpreting expert system facts and rules as PMML models (and vice versa), as well as challenges in representing and composing these models, have been explored. They will be discussed in detail.


Author(s):  
Nipun R. Navadia ◽  
Gurleen Kaur ◽  
Harshit Bhardwaj ◽  
Taranjeet Singh ◽  
Aditi Sakalle ◽  
...  

Cloud storage is a great way for companies to fulfill more of their data-driven needs and excellent technology that allows the company to evolve and grow at a faster pace, accelerating growth and providing a flexible forum for developers to build useful apps for better devices to be developed over the internet. The integration of cloud computing and the internet of things creates a scalable, maintainable, end-to-end internet of things solution on the cloud network. By applying the infrastructure to the real universe, it generates sources of insight. Cloud computing and IoT are separate technology but are closely associated and are termed as ‘cloud-based IoT' as IoT has the ability to create intelligent goods and services, gather data that can affect business decisions and probably change the business model to boost success and expansion, and cloud infrastructure can be at the heart of all IoT has to deliver.


Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 480 ◽  
Author(s):  
Andrea Ballo ◽  
Alfio Dario Grasso ◽  
Gaetano Palumbo

With the aim of providing designer guidelines for choosing the most suitable solution, according to the given design specifications, in this paper a review of charge pump (CP) topologies for the power management of Internet of Things (IoT) nodes is presented. Power management of IoT nodes represents a challenging task, especially when the output of the energy harvester is in the order of few hundreds of millivolts. In these applications, the power management section can be profitably implemented, exploiting CPs. Indeed, presently, many different CP topologies have been presented in literature. Finally, a data-driven comparison is also provided, allowing for quantitative insight into the state-of-the-art of integrated CPs.


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