Intelligent Integrated Maintenance Of Manufacturing Systems
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Intelligent Integrated Maintenance Of Manufacturing Systems
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Author : Roubi A. Zaied
language : en
Publisher:
Release Date : 2010
Intelligent Integrated Maintenance Of Manufacturing Systems written by Roubi A. Zaied and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Intelligent Systems In Production Engineering And Maintenance
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Author : Anna Burduk
language : en
Publisher: Springer
Release Date : 2018-07-31
Intelligent Systems In Production Engineering And Maintenance written by Anna Burduk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Technology & Engineering categories.
The book presents a collection of 103 peer-reviewed articles from the Second International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM 2018). The conference was organized by the Faculty of Mechanical Engineering and CAMT (Centre for Advanced Manufacturing Technologies), Wrocław University of Science and Technology and was held in Wrocław (Poland) on 17–18 September 2018. The conferences topics included the possibility of using a wide range of intelligent methods in production engineering, presenting and discussing new solutions for innovative plants, research findings and case studies demonstrating advances in production and maintenance from the point of view of Industry 4.0 – particularly applications of intelligent systems, methods and tools in production engineering, maintenance, logistics, quality management, information systems and product development. The book is divided into two parts: the first includes papers related to intelligent systems in production engineering, while the second is dedicated to special sessions focusing on: 1. Computer Aided methods in Production Engineering 2. Mining 4.0 and Intelligent Mining Transportation 3. Modelling and Simulation of Production Processes 4. Multi-Faceted Modelling of Networks and Processes 5. Product Design and Product Manufacturing in Industry 4.0 This book is an excellent source of information for scientists in the field of manufacturing engineering and for top managers in production enterprises.
Integrated Maintenance Planning In Manufacturing Systems
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Author : Umar M. Al-Turki
language : en
Publisher: Springer Science & Business
Release Date : 2014-04-25
Integrated Maintenance Planning In Manufacturing Systems written by Umar M. Al-Turki and has been published by Springer Science & Business this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-25 with Technology & Engineering categories.
This book introduces the concept of integrated planning for maintenance and production taken into account quality and safety for high global socio-economic impact. It provides insight into the planning process at a global level starting from the business level and ending with the operational level where the plan is implemented and controlled.
Intelligent Maintenance And Monitoring Strategy For Smart Manufacturing Systems
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Author : Honghan Ye
language : en
Publisher:
Release Date : 2021
Intelligent Maintenance And Monitoring Strategy For Smart Manufacturing Systems written by Honghan Ye and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
In smart manufacturing systems, production scheduling, maintenance decision-making, and process monitoring are three key, closely interconnected components, which play significant roles in the system performance, quality control, and overall cost. Due to the rapid advancement of in-process measurements and sensor technology, massive data frequently appear in modern industries. While such a data-rich environment has the potential to better reveal real-time details of the underlying system and make better decisions for the system improvement, it also presents significant challenges in the following perspectives: (i) how to effectively leverage the acquired knowledge to balance trade-offs between conflicting objectives, (ii) how to optimally design the monitoring system given the practical resources constraint, and (iii) how to efficiently handle the high-dimensional heterogeneous information with different acquisition rates, distributions, and characteristics. This thesis concentrates on production and maintenance scheduling, and process monitoring to develop systematic analytics methodologies for quality control, cost reduction, and performance improvement in smart manufacturing systems. By incorporating engineering domain knowledge with advanced statistical techniques, the proposed methodologies facilitate (i) the real-time decisions that improve the system production and maintenance scheduling, (ii) the effective monitoring of system status, (iii) the informative and intelligent decisions on balancing between exploration and exploitation given the limited monitoring resources, and (iv) the asynchronous process monitoring with different data acquisition rates. The first chapter introduces the background and challenges in production and maintenance scheduling, and monitoring in smart manufacturing systems, and establishes the major research objective of the thesis. Chapter 2 addresses a joint scheduling problem that considers corrective maintenance (CM) due to unexpected breakdowns and scheduled preventive maintenance (PM) in a generic M-machine flow shop. The objective is to find the optimal job sequence and PM schedule such that the total of tardiness cost, PM cost, and CM cost is minimized. To address this critical research issue, our novel idea is to dynamically update the PM interval based on real-time machine age, such that maintenance activity coordinates with job scheduling to the maximum extent, which results in an overall cost saving. With the rapid development of sensor technology, real-time observations from the sensors can be used to describe the machine status more accurately and achieve early anomaly detection. In Chapter 3, we propose a nonparametric monitoring and sampling algorithm integrated with Thompson sampling to quickly detect abnormalities occurring in heterogeneous data streams. In particular, a Bayesian approach is incorporated with an antirank-based cumulative sum (CUSUM) procedure to collectively estimate the underlying status of all data streams based on the partially observed data. Furthermore, an intelligent sampling strategy based on Thompson sampling (TS) algorithm is proposed to dynamically observe the informative data streams and balance between exploration and exploitation to facilitate quick anomaly detection. While the proposed method in Chapter 3 shows good performance in monitoring heterogeneous data streams, it heavily relies on the assumption that full historical in-control observations of all data streams are available offline, which does not always hold in practice. To address this issue, Chapter 4 further proposes a generic online nonparametric monitoring and sampling scheme occurring in high-dimensional heterogeneous processes when only partial observations are available. Specifically, we integrate the TS algorithm with a quantile-based nonparametric CUSUM procedure to construct local statistics of all data streams based on the partially observed data. Further, we develop a global monitoring scheme by using the sum of top-r local statistics to screen out the most suspicious data streams. Chapter 5 proposes a generic top - r based asynchronous monitoring (TRAM) framework to online monitor high-dimensional heterogeneous and asynchronous processes, where measurements of each data stream follow arbitrary distributions and are collected at different sampling intervals. In particular, we first adopt a quantile-based nonparametric CUSUM scheme to monitor each data stream locally. Then, an effective compensation strategy is proposed for unsampled data streams at the local statistics level to alleviate severe detection delay when mean shifts occur to long-sampling-interval data streams. Furthermore, we develop a global monitoring scheme using the sum of top - r local statistics, which is able to quickly detect a wide range of possible mean shifts in all directions. Chapter 6 then summarizes the contribution of the thesis. In summary, this thesis contributes to developing systematic analytics methodologies for quality control, cost reduction, and performance improvement in smart manufacturing systems. The developed methods are generic and can also be applied to other applications such as healthcare, energy and climate research, which will lead to improved maintenance scheduling, efficient resource allocation, and significant overall cost savings.
Service Oriented Holonic And Multi Agent Manufacturing Systems For Industry Of The Future
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Author : Theodor Borangiu
language : en
Publisher: Springer Nature
Release Date : 2021-03-02
Service Oriented Holonic And Multi Agent Manufacturing Systems For Industry Of The Future written by Theodor Borangiu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-02 with Technology & Engineering categories.
The scientific theme of the book concerns “Manufacturing as a Service (MaaS)” which is developed in a layered cloud networked manufacturing perspective, from the shop floor resource sharing model to the virtual enterprise collaborative model, by distributing the cost of the manufacturing infrastructure - equipment, software, maintenance, networking - across all customers. MaaS is approached in terms of new models of service-oriented, knowledge-based manufacturing systems optimized and reality-aware, that deliver value to customer and manufacturer via Big data analytics, Internet of Things communications, Machine learning and Digital twins embedded in Cyber-Physical System frameworks. From product design to after-sales services, MaaS relies on the servitization of manufacturing operations such as: Design as a Service, Predict as a Service or Maintain as a service. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book’s readership is comprised by researchers and engineers working in the manufacturing value chain area who develop and use digital control solutions in the ‘Industry of the Future’ vision. The book also addresses to master and Ph.D. students enrolled in Engineering Sciences programs.
Predictive Maintenance In Smart Factories
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Author : Tania Cerquitelli
language : en
Publisher: Springer Nature
Release Date : 2021-08-26
Predictive Maintenance In Smart Factories written by Tania Cerquitelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-26 with Science categories.
This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.
Smart Sustainable Manufacturing Systems
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Author : Dimitris Kiritsis (Kyritsis)
language : en
Publisher: MDPI
Release Date : 2019-08-14
Smart Sustainable Manufacturing Systems written by Dimitris Kiritsis (Kyritsis) and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-14 with Technology & Engineering categories.
With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities. Advanced manufacturing systems are of paramount importance in making key enabling technologies and new products more competitive, affordable, and accessible, as well as for fostering their economic and social impact. The manufacturing industry also serves as an innovator for sustainability since automation coupled with advanced manufacturing technologies have helped manufacturing practices transition into the circular economy. To that end, this Special Issue of the journal Applied Sciences, devoted to the broad field of Smart Sustainable Manufacturing Systems, explores recent research into the concepts, methods, tools, and applications for smart sustainable manufacturing, in order to advance and promote the development of modern and intelligent manufacturing systems. In light of the above, this Special Issue is a collection of the latest research on relevant topics and addresses the current challenging issues associated with the introduction of smart sustainable manufacturing systems. Various topics have been addressed in this Special Issue, which focuses on the design of sustainable production systems and factories; industrial big data analytics and cyberphysical systems; intelligent maintenance approaches and technologies for increased operating life of production systems; zero-defect manufacturing strategies, tools and methods towards online production management; and connected smart factories.
Intelligent Systems In Production Engineering And Maintenance Iii
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Author : Anna Burduk
language : en
Publisher: Springer Nature
Release Date : 2023-10-28
Intelligent Systems In Production Engineering And Maintenance Iii written by Anna Burduk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-28 with Technology & Engineering categories.
This book reports on intelligent methods and solutions in engineering production and maintenance. It describes advanced tools for optimizing production processes, increasing their automation, safety and sustainability. Contributions cover different stages of the production process, such as product design, supply chain, and equipment maintenance and safety. This is one of the two volumes based on the 4th International Conference on Intelligent Systems in Production Engineering and Maintenance, ISPEM 2023, held on September 13-15, 2023, in Wroclaw, Poland.
Service Oriented Holonic And Multi Agent Manufacturing Systems For Industry Of The Future
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Author : Damien Trentesaux
language : en
Publisher: Springer Nature
Release Date : 2021-07-28
Service Oriented Holonic And Multi Agent Manufacturing Systems For Industry Of The Future written by Damien Trentesaux and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Technology & Engineering categories.
This book approaches its subject matter by promoting concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The scientific theme of the book concerns “Manufacturing as a Service”, developed by virtualizing and encapsulating manufacturing resources, activities and controls into cloud networked services in an open perspective that spans models from shop floor resource allocation to enterprise infrastructure sharing. The papers included in the application space have a profound human dedication and aim at solving societal needs serving the partnership of the future—people and industry in the era of Society 5.0. The book’s readership includes researchers and engineers working in manufacturing, supply chains and logistics areas who innovate, develop and use digital control solutions and students enrolled in Engineering and Service Science programs.
Big Data Analytics In Smart Manufacturing
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Author : P Suresh
language : en
Publisher: CRC Press
Release Date : 2022-12-14
Big Data Analytics In Smart Manufacturing written by P Suresh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-14 with Computers categories.
The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit. The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems. The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way. Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing. Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners.