scholarly journals Smart Manufacturing Technologies for Printed Electronics

Author(s):  
Saleem Khan ◽  
Shawkat Ali ◽  
Amine Bermak
2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.


Author(s):  
Marzieh Khakifirooz ◽  
Mahdi Fathi ◽  
Panos M. Pardalos ◽  
Daniel J. Power

This work introduces a formation and variety of decision-making models based on operations research modeling and optimization techniques in smart manufacturing environments. Unlike traditional manufacturing, the goal of Smart manufacturing is to optimizing concept generation, production, and product transaction and enable flexibility in physical processes to address a dynamic, competitive and global supply chains by using intelligent computerized control, advanced information technology, smart manufacturing technologies and high levels of adaptability. While research in the broad area of smart manufacturing and its challenges in decision making encompasses a wide range of topics and methodologies, we believe this chapter provides a good snapshot of current quantitative modeling approaches, issues, and trends within the field. The chapter aims to provide insights into the system engineering design, emphasizing system requirements analysis and specification, the use of alternative analytical methods and how systems can be evaluated.


2019 ◽  
Vol 11 (5) ◽  
pp. 837-862 ◽  
Author(s):  
Diamantino Torres ◽  
Carina Pimentel ◽  
Susana Duarte

Purpose The purpose of this study intends to make a characterization of a shop floor management (SFM) system in the context of smart manufacturing, through smart technologies and digital shop floor (DSF) features. Design/methodology/approach To attain the paper objective, a mixed method methodology was used. In the first stage, a theoretical background was carried out, to provide a comprehensive understanding on SFM system in a smart manufacturing perspective. Next, a case study within a survey was developed. The case study was introduced to characterize a SFM system, while the survey was made to understand the level of influence of smart manufacturing technologies and of DSF features on SFM. In total, 17 experts responded to the survey. Findings Data analytics is the smart manufacturing technology that influences more the SFM system and its components and the cyber security technology does not influence it at all. The problem solving (PS) is the SFM component more influenced by the smart manufacturing technologies. Also, the use of real-time digital visualization tools is considered the most influential DSF feature for the SFM components and the data security protocols is the least influential one. The four SFM components more influenced by the DSF features are key performance indicator tracking, PS, work standardization and continuous improvement. Research limitations/implications The study was applied in one multinational company from the automotive sector. Originality/value To the best of the authors’ knowledge, this work is one of the first to try to characterize the SFM system on smart manufacturing considering smart technologies and DSF features.


Author(s):  
Bhaskar Botcha ◽  
Zimo Wang ◽  
Sudarshan Rajan ◽  
Natarajan Gautam ◽  
Satish T. S. Bukkapatnam ◽  
...  

Prior R&D efforts point to substantial performance enhancements and energy savings from adopting the Smart Manufacturing (SM) paradigm for process optimization and real-time quality assurance. Significant barriers and risks disincentivize the industry from investing in the adoption and training of SM component suites for discrete manufacturing applications. A diverse discrete part manufacturing enterprises, SM tools and platform vendors are yearning for a testbed reconfigurable to achieve three objectives of performance benchmarking, demonstration, and workforce training for a spectrum of their industrial scenarios and workflows. This paper presents the key ingredients towards the successful transformation of present machine tool and manufacturing environments into SM platform-integrated environments. The present implementation focuses on demonstration of the use of the Smart Manufacturing (SM) platform towards qualification of advanced materials and manufacturing technologies to meet an industry-specified functionality. This initial implementation uses Kepler workflow system residing as part of an Amazon Web Services environment to allow flexible workflows on multiple machines, each of which is integrated with an innovative sensor wrapper that integrates Commercial Off The Shelf (COTS) components from National Instruments (NI) to connect a legacy equipment to the SM platform. Here, an advanced analytics engine with modules customizable for both high-performance computing and shop floor environments was integrated into the commercial web service (from Amazon) to provide real-time monitoring and anomaly detection capability. This implementation indicates the potential of SM platform to achieve drastic reductions in the time and effort taken towards qualification of advanced materials and manufacturing technologies.


Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6456 ◽  
Author(s):  
Erkan Yalcinkaya ◽  
Antonio Maffei ◽  
Mauro Onori

The next-generation technologies enabled by the industry 4.0 revolution put immense pressure on traditional ISA95 compliant manufacturing systems to evolve into smart manufacturing systems. Unfortunately, the transformation of old to new manufacturing technologies is a slow process. Therefore, the manufacturing industry is currently in a situation that the legacy and modern manufacturing systems share the same factory environment. This heterogeneous ecosystem leads to challenges in systems scalability, interoperability, information security, and data quality domains. Our former research effort concluded that blockchain technology has promising features to address these challenges. Moreover, our systematic assessment revealed that most of the ISA95 enterprise functions are suitable for applying blockchain technology. However, no blockchain reference architecture explicitly focuses on the ISA95 compliant traditional and smart manufacturing systems available in the literature. This research aims to fill the gap by first methodically specifying the design requirements and then meticulously elaborating on how the reference architecture components fulfill the design requirements.


2021 ◽  
Vol 11 (17) ◽  
pp. 8202
Author(s):  
Michele Calì

This Special Issue of Applied Sciences provides a collection of original papers on smart manufacturing technology with the aim of: examining emerging aspects of digitalization in the industrial and biomedical fields, as well as in business management and sustainability; proposing and developing a new approach useful for companies, factories, and organizations to achieve greater innovation and productivity—as well as sustainability—by applying smart manufacturing technologies; and exploring new ideas and encouraging research directions so as to obtain autonomous and semiautonomous processes, high-quality products, and services with a greater integration and interconnection of resources while reducing costs. The advantages of new methods and experimental results obtained in the collected contributions are discussed promoting further design, implementation, and application in the various fields.


Machines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 244
Author(s):  
Kai-Leung Yung ◽  
Yuk-Ming Tang ◽  
Wai-Hung Ip ◽  
Wei-Ting Kuo

The design and development of space instruments are considered to be distinct from that of other products. It is because the key considerations are vastly different from those that govern the use of products on planet earth. The service life of a space instrument, its use in extreme space environments, size, weight, cost, and the complexity of maintenance must all be considered. As a result, more innovative ideas and resource support are required to assist mankind in space exploration. This article reviews the impact of product design and innovation on the development of space instruments. Using a systematic literature search review and classification, we have identified over 129 papers and finally selected 48 major articles dealing with space instrument product innovation design. According to the studies, it is revealed that product design and functional performance is the main research focuses on the studied articles. The studies also highlighted various factors that affect space instrument manufacturing or fabrication, and that innovativeness is also the key in the design of space instruments. Lastly, the product design is important to affect the reliability of the space instrument. This review study provides important information and key considerations for the development of smart manufacturing technologies for space instruments in the future.


2018 ◽  
Vol 10 (12) ◽  
pp. 4779 ◽  
Author(s):  
Yuquan Meng ◽  
Yuhang Yang ◽  
Haseung Chung ◽  
Pil-Ho Lee ◽  
Chenhui Shao

With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of the two has not been fully exploited. Conventionally, studies in sustainable manufacturing and smart manufacturing have different objectives and employ different tools. Nevertheless, in the design and implementation of smart factories, sustainability, and energy efficiency are supposed to be important goals. Moreover, big data based decision-making techniques that are developed and applied for smart manufacturing have great potential in promoting the sustainability of manufacturing. In this paper, the state-of-the-art of sustainable and smart manufacturing is first reviewed based on the PRISMA framework, with a focus on how they interact and benefit each other. Key problems in both fields are then identified and discussed. Specially, different technologies emerging in the 4th industrial revolution and their dedications on sustainability are discussed. In addition, the impacts of smart manufacturing technologies on sustainable energy industry are analyzed. Finally, opportunities and challenges in the intersection of the two are identified for future investigation. The scope examined in this paper will be interesting to researchers, engineers, business owners, and policymakers in the manufacturing community, and could serve as a fundamental guideline for future studies in these areas.


2021 ◽  
Vol 11 (8) ◽  
pp. 3568
Author(s):  
Amr T. Sufian ◽  
Badr M. Abdullah ◽  
Muhammad Ateeq ◽  
Roderick Wah ◽  
David Clements

The fourth industrial revolution is the transformation of industrial manufacturing into smart manufacturing. The advancement of digital technologies that make the trend Industry 4.0 are considered as the transforming force that will enable this transformation. However, Industry 4.0 digital technologies need to be connected, integrated and used effectively to create value and to provide insightful information for data driven manufacturing. Smart manufacturing is a journey and requires a roadmap to guide manufacturing organizations for its adoption. The objective of this paper is to review different methodologies and strategies for smart manufacturing implementation to propose a simple and a holistic roadmap that will support the transition into smart factories and achieve resilience, flexibility and sustainability. A comprehensive review of academic and industrial literature was preformed based on multiple stage approach and chosen criteria to establish existing knowledge in the field and to evaluate latest trends and ideas of Industry 4.0 and smart manufacturing technologies, techniques and applications in the manufacturing industry. These criteria are sub-grouped to fit within various stages of the proposed roadmap and attempts to bridge the gap between academia and industry and contributes to a new knowledge in the literature. This paper presents a conceptual approach based on six stages. In each stage, key enabling technologies and strategies are introduced, the common challenges, implementation tips and case studies of industrial applications are discussed to potentially assist in a successful adoption. The significance of the proposed roadmap serve as a strategic practical tool for rapid adoption of Industry 4.0 technologies for smart manufacturing and to bridge the gap between the advanced technologies and their application in manufacturing industry, especially for SMEs.


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