Advanced Manufacturing Partnership Research Articles

A Study on the Application of Deep Learning Models for Real-time Defect Detection in the Manufacturing Process : Cases of Defect detection in the Label Printing Process

The global smart manufacturing market is growing rapidly as developed countries (Germany, USA, Japan) as well as late comers such as China are now recognizing the importance of “smart manufacturing” and promoting active policies to foster related ecosystems. Policies to revitalize manufacturing through the convergence of cutting-edge ICT and manufacturing technology are already in progress. Some such policies include Industry 4.0, the Advanced Manufacturing Partnership of the United States, Japan’s Industrial Revitalization Plan, and China’s Made in China 2025. As a result of the gradual shift from product standardization to product customization, the importance of machine vision in manufacturing has also been increasing. However, it is difficult to develop a standard machine vision method because there are different specifications for meeting the individual demands of different manufacturing industries. Moreover, it is difficult to apply such a standard machine vision method to artificial intelligence because defective data for learning in the manufacturing industry are not frequently generated and stored. Therefore, it is conducted manually or visually inspected by workers. This study applies the primary feature of matching models for a label printing process to efficiently detect defects with high performance and applies a deep learning model to maximize performance. Our proposed method achieved an accuracy of 97% with a feature matching model and 99.8% accuracy with the deep learning model.

Research status of the rare and precious metals’ Materials Genome Initiative

The core philosophy of Materials Genome Initiative (MGI) is the transition of the way of new materials design from the traditional “trial-and-error” approach to the in-silico materials design approach which employs intensive computing and material informatics. In June 2011, President Barack Obama launched MGI alongside the Advanced Manufacturing Partnership to help businesses discover, develop and deploy new materials twice as fast. In this paper, the concept of rare and precious genome is presented first, followed by the progress of MGI. After that, we focus on the research status of the rare and precious metals’ MGI including the computational tools, the high-throughput experimental methodologies and the rare and precious metals database. We also introduce the application of MGI in the development of rare and precious metal materials, outline the remaining fundamental challenges and present an outlook on the future of the rare and precious metals’ MGI.

Construction of high-throughput computation platform for random alloys (HCPRA) and its applications

Materials play not only an important role in academic research but also a rather important role in daily life. The discovery of a new material can make a significant contribution to both scientific research and society development. For example, the discovery of graphene in 2004 has attracted enormous attention in academic circle and graphene has shown promising applications in electronic and optical devices. However, the period of discovering a new material is too long to satisfy the demand of society. To speed up the process, Advanced Manufacturing Partnership was proposed in 2011 by US President Obama. This plan has a key part: Materials Genome Initiative (MGI). MGI is made up with three part, (1) construction of high-throughput computation platforms, (2) construction of high-throughput experimental platforms and (3) construction of databases. The high-throughput computation and experimental platforms have promising applications in investigating known materials as well as discovering new materials with high efficiency since they can produce a large amount of data in a short term. Databases can provide convenience for data analysis and machine learning that is a prevailing way to design new materials. In this paper, we present our new designed High-throughput Computational Platform for Random Alloys. The platform is built by using Fortran and Shell languages and its main function is to calculate mechanical and thermodynamic properties of random alloys in large quantities automatically by employing the Vienna ab - initio Simulation Package (VASP). There are two main problems that are needed to be solved in the construction of High-throughput Computational Platform for Random Alloys. The first one is the creation of structures for random binary alloys. Another is to set the comparable computational parameters for all calculations automatically. To create structures for binary random alloys, we employ Alloy Theoretic Automated Toolkit to obtain a set of special quasi- random structure templates. Then, we collect all structure information for elementary substance from literature or by performing the first principles calculations. Finally, we design the platform to create special quasi-random structures (POSCAR) for all kinds of binary random alloys by using the templates and structure information of elementary substance combine with the Neumann-Kopp rule. In order to set comparable computational parameters for the VASP calculations, we write a code to read the structure information from POSCAR and use the information to set a comparable k-mesh for all calculations. The INCAR file is created by using the information from POSCAR and POTCAR. After all input files are generated, the platform employs VASP to perform the first-principles calculations. The platform is also designed to extract and analyze calculation results as well as print a calculation report and save all the calculation data into a database. The platform also has some useful functions such as error information-outputting system and error-skipping system. The function is rather important since convergence problem is inevitable in the first-principle calculations especially in high throughput calculations. To test the efficiency of the platform, elastic constants of 47 pure metals are investigated which indicates a computer with eight cores can finish all calculations in one day. And all calculated results match those in the literature well. By using the platform, the mechanical properties of zirconium based binary alloys are investigated and we find the elastic constants and elastic modulus can be well described by a parabolic function.

An empirical study for smart production for TFT-LCD to empower Industry 3.5

With increasing technological advancements, manufacturing intelligence has become a crucial issue for maintaining competitive advantages. Industry 4.0, proposed by Germany, is one of the large-scale projects to achieve manufacturing intelligence and smart production. Others include the Advanced Manufacturing Partnership 2.0 (AMP2.0) from the United States, Industry 4.1J of Japan and Made in China 2025. On the other hand, most of the emerging countries may not be ready for the migration of Industry 4.0 directly since their industrial infrastructures are different with the leading countries. This study aims to propose Industry 3.5 as a hybrid strategy between existing Industry 3.0 and to-be Industry 4.0, in which digital decision-making, big data analytics, and manufacturing intelligence are integrated to empower smart production with disruptive innovations that can be realized in existing industrial infrastructure. To estimate the validity of the proposed Industry 3.5, an empirical study was conducted in a thin film transistor liquid crystal display (TFT-LCD) manufacturing factory in Taiwan. A smart daily planning and scheduling (DPS) system is developed to enhance manufacturing intelligence for smart production without a fully automation facility as the Cyber-Physical System proposed in Industry 4.0. This study concludes with discussions of development directions for industrial revolution.

Integrated and Intelligent Manufacturing: Perspectives and Enablers

Abstract With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry 4.0 strategy in 2013. The US government launched the Advanced Manufacturing Partnership (AMP) in 2011 and the National Network for Manufacturing Innovation (NNMI) in 2014. Most recently, the Manufacturing USA initiative was officially rolled out to further “leverage existing resources... to nurture manufacturing innovation and accelerate commercialization” by fostering close collaboration between industry, academia, and government partners. In 2015, the Chinese government officially published a 10-year plan and roadmap toward manufacturing: Made in China 2025. In all these national initiatives, the core technology development and implementation is in the area of advanced manufacturing systems. A new manufacturing paradigm is emerging, which can be characterized by two unique features: integrated manufacturing and intelligent manufacturing. This trend is in line with the progress of industrial revolutions, in which higher efficiency in production systems is being continuously pursued. To this end, 10 major technologies can be identified for the new manufacturing paradigm. This paper describes the rationales and needs for integrated and intelligent manufacturing (i2M) systems. Related technologies from different fields are also described. In particular, key technological enablers, such as the Internet of Things and Services (IoTS), cyber-physical systems (CPSs), and cloud computing are discussed. Challenges are addressed with applications that are based on commercially available platforms such as General Electric (GE)’s Predix and PTC’s ThingWorx.

Patent-based Disputes in the US Import Trade with China: With Special References to the Parallel Development of MIC 2025 & AMP 2.0 and ITA2

The current scale of the import trade of the US with China is significant and has the potential to be more in near future. However, patent-based disputes, especially in terms of Section 337 investigation, have also been increased in recent years. In the context of parallel development of national innovation strategies of China’s “Made in China 2025 Plan” and the American “Advanced Manufacturing Partnership,” along with the latest expanded “Information Technology Agreement” in the WTO trading system, the implications for optimally resolving patent-based disputes in the US import trade with China is highly significant for two countries. These disputes may even impact the world trade, since bilateral trade between China and the US accounts for a considerable proportion. Thus, both China and the US should take precautions and appropriate measures to guard against such potential frictions in order to attain mutually beneficial outcomes in resolving such disputes.

Trends and Recent Advances of Industrial Big Data Analytics and Cyber Physical Systems for PHM Applications

In today’s competitive business environment, companies are facing challenges in dealing with big data issues for rapid decision making for improved productivity and business innovation. Many product and manufacturing systems are not ready to manage big data due to the lack of smart analytics tools. U.S. has been driving the Cyber Physical Systems (CPS), Industrial Internet, and Advanced Manufacturing Partnership (AMP) Program to advance future manufacturing. Germany is leading a transformation toward 4th Generation Industrial Revolution (Industry 4.0) based on Cyber-Physical Production System (CPPS). It is clear that as more predictive analytics software and embedded IoT are integrated in industrial products, predictive technologies can further intertwine smart IoT to predict product performance autonomously and further optimize the smart service systems. The presentation will address the trends of predictive big data analytics and CPS for future industrial PHM application. First, predictive analytics and Cyber-Physical System (CPS) enabled industrial systems will be introduced. Second, advanced predictive analytics technologies for self-aware industrial systems with case studies will be presented. Finally, business innovation based on industrial big data will be introduced using case studies.

Policy Debate

In its June 2011 report to President Barak Obama, the President’s Council of Advisors on Science and Technology (PCAST) noted that: ‘While the United States may not be able to compete in the long run to make goods for which low wage unskilled labor is the key input, this need not be true for sophisticated manufacturing linked to products and processes derived from scientific discovery and technological innovation’. Rather than focusing policy efforts on low technology manufacturing, PCAST argues that ‘advanced manufacturing provides the path forward to revitalizing US leadership in manufacturing and will best support economic productivity and ongoing knowledge production and innovation in the Nation’. In June 2011, President Obama announced the launching of the Advanced Manufacturing Partnership, an effort bringing together industry, universities, and the federal government to invest in such emerging technologies as nano-scale carbon materials, next-generation optoelectronics, flexible electronics, and nanotechnology enabled medical diagnostic devices and therapeutics. PCAST argues for a coherent innovation policy that manifests itself in a recommended ‘Advanced Manufacturing Initiative for America’s Future’ (‘AMI’) – a concerted government effort led by the US Departments of Commerce, Defense, and Energy, and coordinated by the Executive Office of the President. How does an AMI based on an ‘innovation policy’ harmonize with an Administration that has been consistently following an ‘industrial policy’ that financially – as well as through its regulatory policies – supports and influences specific manufacturing companies and industries that it deems as ‘winners’? The short answer is not well. Both ‘tilting the field’ and ‘playing the role of principal actor’ is how the Obama administration has actively supported ‘green’ technology companies, and this industrial policy could be expanded in a second term to other government designated ‘winners’ at the competitive expense of other industry sub-sectors of advanced manufacturing.

Declining Manufacturing Employment as a Global Social Change: Implications for Azerbaijan

Existing literature provides striking empirical results about the declining manufacturing employment all over the world. This bare finding brought about clear definition of deindustrialization: systematic disinvestment in a nation's core manufacturing industries. In some studies we observe globalization as a main source of this concern. Only in Japanese economy between 2001 and 2004, 800 thousand jobs were lost in manufacturing SMEs. For the same period, job loss in all US manufacturing industry reached to 2, 1 million. Of the 10 countries tracked by the US Bureau of Labor Statistics, between 1997 and 2009, United States lost highest number of jobs in manufacturing. By mid-2012, Advanced Manufacturing Partnership Steering Committee submitted its report to Mr. Obama with the title of Capturing Domestic Competitive Advantage in Advanced Manufacturing. This report also includes concerns about declining share of manufacturing in the US Economy. From the social change standpoint, US is much concerned than others, because middle-class of America is built up by manufacturing. Also, US experience shows that, manufacturing jobs are more likely to be full-time and to offer 12 percent higher wages than other jobs. Other study suggests that between 1970s and 2000s external factors caused manufacturing sector employment decline across 18 OECD countries. About the developing countries, a comprehensive study including analysis of 64 countries comes up with interesting result: From 1980 to 2003 manufacturing employment increased in most countries. Declining relative importance of manufacturing in terms of employment and output made some countries to take pre-emptive steps. Developing countries such as Cameroon and Nigeria perceives manufacturing sector development plans as poverty reduction policy for the economy. Fostering non-oil industry, that is manufacturing, holds a national vital priority and provides potential employment opportunities for Azerbaijan economy too. During the rising concerns era of manufacturing employment, numerous policy implications are also supposed to be concluded for the Azerbaijan economy. This study will attempt to come up with some practical and plausible suggestions for the Azerbaijan, regarding manufacturing employment and its social impacts.

Digitalization and intelligentization of manufacturing industry

China has entered a new historical period in her development. In order to achieve scientific development and to accelerate transformation of economic development pattern, the most fundamental issue is to rely on the power of science and technology, and the most crucial element is to improve the capability of independent innovation. The key for promoting China’s economic and social development is to embark on the innovation-driven track as soon as possible. Since the 2008 global financial crisis, the landscape of the global competition has undergone profound changes. On the one hand, the strategic significance of the industrial economy has once again become prominent, as major developed countries are refocusing on the industrial economy and implementing a strategy of re-industrialization. In 2009, the U.S. enacted the Framework for Revitalization of U.S. Manufacturing Industry and Congress passed the Manufacturing Promotion Act. In late 2011, the U.S. initiated the ‘‘Advanced Manufacturing Partnership Plan’’ and released a five-year plan to revitalize and double the exports of the manufacturing sector. In February this year, the U.S. again promulgated an Advanced Manufacturing National Strategic Plan, under which she proposed to once again recognize the status of the advanced manufacturing sector in the national economy and maintain international leadership and dominance in the field of advanced manufacturing. Germany, Britain, Japan and other developed countries have launched a series of major initiatives to revitalize their manufacturing sector. On the other hand, a new round of industrial revolution is deepening, and developed countries in the West are proposing new ways of revitalizing their manufacturing sector, by relying on scientific and technological innovation, seizing the commanding heights in international industrial competition, and enhancing their core competencies in economic development in order to seize the initiative in future development. For example, through product model innovation, integration and incorporation of the latest technologies, Apple has successfully pioneered the development direction for IT products. Another example is the breakthrough of shale gas development in U.S. which brought about a ‘‘shale gas revolution’’. It had a profound impact not only on the world’s energy situation but also on the political and economic development. Recently, scholars in the U.S. have published a number of articles. Firstly, they emphasized the impending round of industrial revolution with ‘‘digitalization in manufacturing’’ as its core technology. Secondly, their viewpoint was that the U.S. had substantial advantage in information technology which should be vigorously developed and widely applied using digitalization and intelligentization as the core technology in advanced manufacturing, in order to achieve revolutionary changes in the manufacturing sector. Thirdly, they pointedly noted that with the emerging technologies, in 20 years’ time China’s manufacturing industry will very likely experience the budding difficulties faced by the U.S. during the past 20 years. Very soon it will be China’s turn to be worried. After 60-plus years endeavors made after the founding of New China—in particular the struggles during economic reform and opening up over the past 30 years—China’s manufacturing industry has achieved historical leaps and J. Zhou (&) Chinese Academy of Engineering, Beijing, China

Bridging the Gap: Linking Simulation and Testing

The Materials Genome Initiative (MGI) which is a key enabler for the Advanced Manufacturing Partnership, announced in 2011 by U.S. President Barack Obama, was established to accelerate the development and deployment of advanced materials. The MGI is driven by the need to "bridge the gap" between (I) experimental results and computational analysis to enable the rapid development and validation of new mateirals, and (II) the processes required to convert these materials into useable goods.

Modest but uneven R&D increases proposed for FY 2013

Uncertainty created by the Budget Control Act of 2011 clouds the outlook for federal science and technologyfunding. Some Department of Energyphysics programs face significant cuts.