Testing of the MTConnect–OPC UA Companion Specification

2019 ◽  
Author(s):  
Ryan Fisher ◽  
Guodong Shao
Keyword(s):  
Data Structures ◽  
Information Technologies ◽  
Manufacturing Industry ◽  
Smart Manufacturing ◽  
Standard Testing ◽  
Open Platform ◽  
The Future ◽  
Proprietary Format ◽  
Extensible Markup ◽  
Engineering Costs

Abstract Smart Manufacturing (SM) is the future of the manufacturing industry. Seamless, accurate, and fast connection and communications among devices are critical for SM. By leveraging information technologies, devices can dynamically communicate with each other to increase factory production, while decreasing engineering costs. MTConnect and Open Platform Communications - Unified Architecture (OPC-UA) standards facilitate such communication. MTConnect is a manufacturing interoperability standard that provides a semantic vocabulary for manufacturing equipment to provide structured contextualized data with no proprietary format. The OPC-UA is a platform-independent standard through which various systems and devices can communicate by sending messages between clients and servers over various networks. OPC-UA enables syntactic interoperability between clients and servers. The MTConnect - OPC-UA Companion Specification integrates the two standards to provide manufacturers more efficient and powerful interoperability capabilities. In this paper, we report the test of version 1.02 of this companion specification. This specification sets a standard means of communication between MTConnect devices and OPC-UA Clients/Servers based on Extensible Markup Language (XML) structures. To test the standard, the following components have been developed: an OPC-UA Server, an OPC-UA Client, a probe that translates data structures in MTConnect XML format to MTConnect OPC-UA Companion XML format that can be recognized by the server, a MTConnect XML data parser, and a MTConnect device simulator. The activities of the standard testing include passing varying data structures and objects through the server and confirming the information is received accurately by the client. The findings of the standard testing will be provided to the standard developing organizations for improving the future versions of the standard.

scholarly journals The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review

2019 ◽  
Vol 9 (18) ◽  
pp. 3865 ◽  
Author(s):  
Mehrshad Mehrpouya ◽  
Amir Dehghanghadikolaei ◽  
Behzad Fotovvati ◽  
Alireza Vosooghnia ◽  
Sattar S. Emamian ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
Information Technologies ◽  
Manufacturing Systems ◽  
High Efficiency ◽  
Industrial Applications ◽  
Future Trend ◽  
Smart Manufacturing ◽  
The Future ◽  
Smart Manufacturing Systems

Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations.

Introduction to Smart Manufacturing

2014 ◽  
pp. 1-19 ◽  
Author(s):  
ZongWei Luo
Keyword(s):  
Value Chain ◽  
Information Technologies ◽  
Manufacturing Industry ◽  
Life Cycles ◽  
Smart Manufacturing ◽  
Advanced Manufacturing ◽  
Value Chain Analysis ◽  
Chain Analysis ◽  
Manufacturing Intelligence

Fast advances in information technology (RFID, sensor, Internet of things, and the Cloud) have led to a smarter world vision with ubiquitous interconnection and intelligence. Smart manufacturing refers to advanced manufacturing with wise adoption of information technologies throughout end to end product and service life-cycles, capturing manufacturing intelligence for wise production and services. It represents a field with intense competition in this century of national competitiveness. In this chapter, an introduction to smart manufacturing innovation and transformation is presented. An example is used to illustrate what is happening in China's manufacturing industry, with insights about China's strategy of advanced manufacturing research and development. The chapter emphasizes the value chain analysis for setting smart manufacturing strategies. A case study is conducted in detail to showcase a value chain analysis of RFID enabled SIM-smart card manufacturing for China's mobile payment industry.

A Study on the Impact of Family-friendly Certification on Financial Performance of SMEs: Focusing on the Manufacturing Industry

2019 ◽  
Vol 118 (2) ◽  
pp. 7-12
Author(s):  
Ok-Hee Park ◽  
Kwan-sik Na ◽  
Seok-Kee Lee
Keyword(s):  
Financial Performance ◽  
Family Life ◽  
Manufacturing Industry ◽  
Work And Family ◽  
Family Friendly ◽  
The Future ◽  
The Impact

Background/Objectives: The purpose of the paper is to examine how family-friendly certificates introduced to pursue the compatibility of work and family life affect the financial performance of small and medium-sized manufacturers, and to provide useful information to companies considering the introduction of this system in the future.

scholarly journals Multi-Scale Convolutional Gated Recurrent Unit Networks for Tool Wear Prediction in Smart Manufacturing

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Weixin Xu ◽  
Huihui Miao ◽  
Zhibin Zhao ◽  
Jinxin Liu ◽  
Chuang Sun ◽  
...  
Keyword(s):  
Tool Wear ◽  
Information Technologies ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Wear Prediction ◽  
Multi Scale ◽  
Tool Wear Prediction ◽  
Machine Health Monitoring ◽  
Gated Recurrent Unit ◽  
Unit Network

AbstractAs an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry. In this paper, a multi-scale Convolutional Gated Recurrent Unit network (MCGRU) is proposed to address raw sensory data for tool wear prediction. At the bottom of MCGRU, six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network, which augments the adaptability to features of different time scales. These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations. At the top of the MCGRU, a fully connected layer and a regression layer are built for cutting tool wear prediction. Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.

Industrial internet of things for smart manufacturing applications using hierarchical trustful resource assignment

Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Duan Pingli ◽  
Bala Anand Muthu ◽  
Seifedine Nimer Kadry
Keyword(s):  
Internet Of Things ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
The Internet ◽  
Resource Assignment ◽  
Industrial Internet Of Things ◽  
Assignment Method ◽  
Industrial Internet

BACKGROUND: The manufacturing industry undergoes a new age, with significant changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices, which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. OBJECTIVES: The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. RESULTS: Finally, experimental findings demonstrate that when the IIoT equipment and gateways are valid, the utilities of each participant are improved. CONCLUSION: This is an easy and powerful method to guarantee that intelligent manufacturing components genuinely work for their purposes, which want to integrate each element into a system without interactions with each other.

scholarly journals Automation technology as a key component of the Industry 4.0 production development path

2021 ◽  
Author(s):  
Christian Brecher ◽  
Aleksandra Müller ◽  
Yannick Dassen ◽  
Simon Storms
Keyword(s):  
Industry 4.0 ◽  
Information Technologies ◽  
Production Systems ◽  
Product Variety ◽  
Transformation Process ◽  
Smart Manufacturing ◽  
Production Development ◽  
Flexible Production Systems ◽  
Current Production ◽  
Automation Technology

AbstractSince 2011, the Industry 4.0 initiative is a key research and development direction towards flexible production systems in Germany. The objective of the initiative is to deal with the challenge of an increased production complexity caused by various factors such as increasing global competition between companies, product variety, and individualization to meet customer needs. For this, Industry 4.0 envisions an overarching connection of information technologies with the production process, enabling smart manufacturing. Bringing current production systems to this objective will be a long transformation process, which requires a coherent migration path. The aim of this paper is to represent an exemplary production development way towards Industry 4.0 using eminent formalization approaches and standardized automation technologies.

2021 Offshore petroleum exploration acreage release

2021 ◽  
Vol 61 (2) ◽  
pp. 291
Author(s):  
Paul Trotman
Keyword(s):  
Manufacturing Industry ◽  
Oil And Gas ◽  
Domestic Demand ◽  
Liquefied Natural Gas ◽  
Petroleum Exploration ◽  
Demand Growth ◽  
Regulatory Frameworks ◽  
The Future ◽  
Policy Work ◽  
Offshore Petroleum

In 2020, the liquefied natural gas (LNG) trade saw a modest increase of 1%, which is in contrast to the strong growth of previous years. Recently, the global LNG trade has picked up following the easing of impacts from the pandemic and demand growth in Asia. An increase of 6% in the global LNG trade is expected in 2021 and 2022. Domestic demand for gas remains high, with gas being used both for residential supply and also as an essential feedstock for the manufacturing industry. With a projected domestic gas shortfall, the future exploration and development of oil and gas will play a key role in ensuring access to secure, reliable and affordable energy in the future as well as assisting economic recovery from the pandemic. The importance of remaining an attractive investment destination is essential. Our challenge is to not only strike the balance of being agile and adaptive to market disruptions but also provide robust policy and regulatory frameworks to underpin future investment in the sector. Against this backdrop, this paper provides details of the 2021 offshore petroleum exploration acreage release and information about the ongoing policy work of the department.

Smart Manufacturing Through a Framework for a Knowledge-Based Diagnosis System

2017 ◽  
Author(s):  
Michael P. Brundage ◽  
Boonserm Kulvatunyou ◽  
Toyosi Ademujimi ◽  
Badarinath Rakshith
Keyword(s):  
Manufacturing Industry ◽  
Ad Hoc ◽  
Root Cause Analysis ◽  
Medical Community ◽  
Smart Manufacturing ◽  
Cause Analysis ◽  
Diagnosis System ◽  
Standard Representation ◽  
Root Cause ◽  
Knowledge Based

Various techniques are used to diagnose problems throughout all levels of the organization within the manufacturing industry. Often times, this root cause analysis is ad-hoc with no standard representation for artifacts or terminology (i.e., no standard representation for terms used in techniques such as fishbone diagrams, 5 why’s, etc.). Once a problem is diagnosed and alleviated, the results are discarded or stored locally as paper/digital text documents. When the same or similar problem reoccurs with different employees or in a different factory, the whole process has to be repeated without taking advantage of knowledge gained from previous problem(s) and corresponding solution(s). When discussing the diagnosis, personnel may miscommunicate over terms used in the root cause analysis leading to wasted time and errors. This paper presents a framework for a knowledge-based manufacturing diagnosis system that aims to alleviate these miscommunications. By learning from diagnosis methods used in manufacturing and in the medical community, this paper proposes a framework which integrates and formalizes root cause analysis by categorizing faults and failures that span multiple organizational levels. The proposed framework aims to enable manufacturing operations by leveraging machine learning and semantic technologies for the manufacturing system diagnosis. A use case for the manufacture of a bottle opener demonstrates the framework.

scholarly journals All Out Lean

2016 ◽  
Vol 138 (01) ◽  
pp. 30-35 ◽  
Author(s):  
Gary Cowger
Keyword(s):  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Continuous Monitoring ◽  
Manufacturing Industry ◽  
Lean Implementation ◽  
The Future ◽  
The U.S

This article highlights advantages of Lean Manufacturing in the manufacturing industry. The U.S. Bureau of Census survey shows that leaner the company, the faster it grows and the more profitable, productive, and innovative it becomes. It is a constellation of interrelated processes that improve productivity and reduce waste through continuous monitoring, evaluation, and improvement. The successful results of lean implementation have shown that workers are going to have to take more responsibility for outcomes, and managers are going to have to treat workers like partners. However, lean brings out the skepticism in many engineers and owners of small- and medium-sized businesses. It takes a lot to convince them to invest the time and money needed to transform even a modest factory into a lean operation. Lean has proven to be a philosophy of continuous improvement, as learning how to expose and fix problems creates sustainable advantages that are expected to continue in the future.

scholarly journals Industry 4.0 and Developing Countries: Innovation Perspective of Ethiopia, India and Bangladesh

2020 ◽  
Vol 6 (6) ◽  
pp. 62-70
Author(s):  
Amrut Rao ◽  
Ravindra Pathak ◽  
Ashraf Mahmud Rayed
Keyword(s):  
Developing Countries ◽  
Industry 4.0 ◽  
Global Economy ◽  
Information Technologies ◽  
Technological Development ◽  
Value Added ◽  
Developed Countries ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
Efficient Production

Ethiopia, India and Bangladesh are raising economic power, but have not yet integrated very much with the global economy and still have not achieved their potential in context of technology, globalization, and international competitiveness like developed countries. These countries have much strength, but at the same time , are facing many challenges in the increasingly competitive and fast changing global economy. The main key strengths of these courtiers are their large domestic market, young and growing population, a strong private sector with experience in market institutions, and a well developed legal and financial system. In today’s environment of global competition, technological development and innovation; companies, especially manufacturing, are forced to reconfigure their manufacturing and management processes. Industry 4.0 and intelligent manufacturing are part of a transformation, in which manufacturing and information technologies have been integrated to create innovative systems of manufacturing, management and ways of doing business. This system allows optimizing manufacturing, to achieve greater flexibility, efficient production processes and generate a value added proposal for their customers, as well as to provide a timely response to their market needs. The objective of this work is to explore the Industry 4.0, smart manufacturing, environment requirement and relation of innovation in perspective of developing countries.

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