Chapter

Smart Factory - A Step towards the Next Generation of Manufacturing

January 2008

In book: Manufacturing Systems and Technologies for the New Frontier (pp.115-118)

Authors:

Fraunhofer Institute for Industrial Engineering IAO

The Stuttgart Model of adaptive, transformable and virtual factories, already implemented in German basic research performed at the Universität Stuttgart has been extended with a new perspective, the so-called “Smart Factory”. The Smart Factory approach is a new dimension of multi-scale manufacturing by using the state-of-the-art ubiquitous/pervasive computing technologies and tools. The Smart Factory represents a context-sensitive manufacturing environment that can handle turbulences in real-time production using decentralized information and communication structures for an optimum management of production processes. This paper presents our research steps and future work in giving reality to the envisioned Smart Factory at the Universität Stuttgart.

Fabrica inteligentă în domeniul auto în Industria 4.0 Smart Factory in the automotive field in Industry 4.0

Article

Full-text available

Jan 2023

Rezumat Producția industrială se confruntă cu provocări majore în ceea ce privește flexibilitatea și productivitatea în timpul procesului de fabricație. Această lucrare va prezenta principiile unei fabrici inteligente într-un mediu dinamic al Industriei 4.0 în domeniul auto din România. O fabrică inteligentă trebuie să urmeze câteva principii precum: Integrare, Inteligență și Interactivitate. Integrarea se realizează printr-o fabrică conectată, iar acest principiu se realizează prin legătura dintre automatizarea mașinilor și fabrica IT. Inteligența este realizată de o fabrică digitală, iar acest principiu este realizat prin furnizarea și utilizarea datelor provenite de la dispozitive, procesele de producție și controlul calității produselor. Interactivitatea este realizată de o fabrică care colaborează, iar acest principiu este realizat prin îmbunătățirea interacțiunii om-mașină. Fabricația inteligentă îmbrățișează o mulțime din cele mai noi tehnologii de informare și comunicare, plus facilități inteligente, și ajută la crearea și răspândirea unui impact pozitiv în cadrul întregii structuri organizaționale. Datele colectate prin intermediul senzorilor diferă în ceea ce privește sursa, semantica și chiar formatul, de exemplu, datele pot fi colectate prin sisteme de fabricație, proces, gama de produs sau oameni. Lucrarea de față prezintă ideile principale ale unei fabrici inteligente cât și câteva principii de proiectare ale unei fabrici inteligente. Cuvinte cheie Fabrica inteligentă, Industria 4.0, domeniul auto, fabricația modernă Abstract Industrial production is facing major challenges regarding the flexibility and productivity during the manufacturing process. This paper will present the principles of Smart Factory in a dynamic Industry 4.0 environment in automotive field in Romania. A Smart Factory need to follow some principles as: Integration, Intelligence, and Interactivity. Integration is achieved by a connected factory and this principle is made by the link between machine automation and IT factory. Intelligence is achieved by a digitally factory and this principle is made by providing and using data from devices, production processes and product quality control. Interactivity is achieved by a factory that collaborates and this principle is made by improving human-machine interaction. Smart manufacturing embraces a lot of the latest information and communication technologies, plus smart facilities, and helps create and spread a positive impact throughout the entire organizational structure. Data collected via sensors differs in source, semantics and even format, for example, data can be collected via manufacturing systems, process, product range or people. This paper presents the main ideas of a smart factory as well as some design principles of a smart factory.

A Primer on the Factories of the Future

Article

Full-text available

Aug 2022
SENSORS-BASEL

In a dynamic and rapidly changing world, customers’ often conflicting demands have continued to evolve, outstripping the ability of the traditional factory to address modern-day production challenges. To fix these challenges, several manufacturing paradigms have been proposed. Some of these have monikers such as the smart factory, intelligent factory, digital factory, and cloud-based factory. Due to a lack of consensus on general nomenclature, the term Factory of the Future (or Future Factory) has been used in this paper as a collective euphemism for these paradigms. The Factory of the Future constitutes a creative convergence of multiple technologies, techniques, and capabilities that represent a significant change in current production capabilities, models, and practices. Using the semi-narrative research methodology in concert with the snowballing approach, the authors reviewed the open literature to understand the organizing principles behind the most common smart manufacturing paradigms with a view to developing a creative reference that articulates their shared characteristics and features under a collective lingua franca, viz., Factory of the Future. Serving as a review article and a reference monograph, the paper details the meanings, characteristics, technological framework, and applications of the modern factory and its various connotations. Amongst other objectives, it characterizes the next-generation factory and provides an overview of reference architectures/models that guide their structured development and deployment. Three advanced communication technologies capable of advancing the goals of the Factory of the Future and rapidly scaling advancements in the field are discussed. It was established that next-generation factories would be data rich environments. The realization of their ultimate value would depend on the ability of stakeholders to develop the appropriate infrastructure to extract, store, and process data to support decision making and process optimization.

A Primer on the Factories of the Future

Preprint

Full-text available

Jun 2022

In a dynamic and rapidly changing world, customers’ often conflicting demands plus fluid economic requirements, often driven by geo-politics, have continued to evolve, out-striping the capability of existing production systems. With its inherent shortcomings, the traditional factory has proven to be incapable of addressing these modern-day manufacturing challenges. Recent advancements in Industry 4.0 have catalyzed the development of new manufacturing paradigms (or smart factory visions) under different monikers (e.g., Smart factory, Intelligent factory, Digital factory, Cloud-based factory etc.) would help fix these challenges. Due to a lack of consensus on a general nomenclature for these manufacturing paradigms, the term Future Factory (or Factory of the Future) is here used as a collective euphemism, without prejudice. The Future Factory constitutes a creative convergence of multiple technologies, techniques and capabilities that represent a significant change in current production capabilities, models, and practices. It is a data-driven manufacturing approach and system that harnesses intelligence from multiple information streams i.e., assets (including people), processes, and subsystems to help create new forms of production efficiency and flexibility. Serving both as a review monograph and reference companion, this paper details the meanings, characteristics, and technological underpinnings of the Future Factory. It also elucidates on the architectural models that guide the structured deployment of these modern factories with particular emphasis on three advanced communication technologies capable of speeding up advancements in the field. It not only highlights the relevance of communication between assets but also lays out mechanisms to achieve these interactions using the Administration shell. Finally, the paper also discusses the key enabling technologies that are typically embedded into bare bone factories to help improve their visibility, resilience, intelligence, and capacity, in addition to how these technologies are being deployed and to what effect. At the onset of the study, we were interested in developing a monograph which would serve as a comprehensive but concise review of general principles, fundamental concepts, major characteristics, key building blocks and implementation guidelines for the Future Factory within the overall context of the manufacturing ecosystem, in the age of Industry 4.0. Our hope is that this paper would enrich the extant literature on advanced manufacturing, help shape policy and research, and provide insights on how some of the identified pathways can be diffused into industry.

Navigation robot training with Deep Q-Learning monitored by Digital Twin

Conference Paper

Full-text available

Jan 2022

Digital Supply Chain Technologies and Sustainability

Chapter

Nov 2023

Digital supply chains employ many technologies, each influencing the environmental performance of the supply chain network to some degree. The technological ecosystem includes Additive Manufacturing (AM), Artificial Intelligence (AI), big data, Blockchain, Internet of Things (IoT), and robotics, among others. Technologies in digital supply chains have brought many opportunities and new challenges to sustainability in supply chain management. Sustainability in supply chains refers to adopting processes and technologies that minimize the environmental impact. Circular Economy (CE) supports I4,0 and improves sustainability. Moreover, sustainability applies to the different activities of supply chains, from sourcing to the last mile delivery, at various echelons to minimize the environmental impact. This chapter provides a holistic view of technologies in digital supply chains and their contribution to environmental sustainability.

Automation of Trimming Die Design Inspection by Zigzag Process Between AI and CAD Domains

Preprint

May 2023

Quality control in the manufacturing industry has improved with the use of artificial intelligence (AI). However, the manual inspection of trimming die designs, which is time-consuming and prone to errors, is still done by engineers. This study introduces an automatic design inspection system for automobile trimming dies by integrating AI modules and computer-aided design (CAD) software. The AI modules replace engineers' judgment, and the CAD software carries out operations requested by the AI modules. The inspection process involves a zigzag interaction between the AI modules and CAD software, enabling one-click operation without expert intervention. The AI modules are CAD-independent and data-efficient, making them adaptable to other CAD software. They achieve high performance even with limited training data, with an average length measurement error of only 2.4%. The inspection time is reduced to approximately one-fifth of the time required for manual inspection by experts.

Predicting Failure Probability in Industry 4.0 Production Systems: A Workload-Based Prognostic Model for Maintenance Planning

Article

Full-text available

Feb 2023

Maintenance of equipment is a crucial issue in almost all industrial sectors as it impacts the quality, safety, and productivity of any manufacturing system. Additionally, frequent production rescheduling due to unplanned and unintended interruptions can be very time consuming, especially in the case of centrally controlled systems. Therefore, the ability to estimate the likelihood that a monitored machine will successfully complete a predefined workload, taking into account both historical data from the machine’s sensors and the impending workload, may be essential in supporting a new approach to scheduling activities in an Industry 4.0 production system. This study proposes a novel approach for integrating machine workload information into a well-established PHM algorithm for Industry 4.0, with the aim of improving maintenance strategies in the manufacturing process. The proposed approach utilises a logistic regression model to assess the health condition of equipment and a neural network computational model to estimate its failure probability according to the scheduled workloads. Results from a prototypal case study showed that this approach leads to an improvement in the prediction of the likelihood of completing a scheduled job, resulting in improved autonomy of CPSs in accepting or declining scheduled jobs based on their forecasted health state, and a reduction in maintenance costs while maximising the utilisation of production resources. In conclusion, this study is beneficial for the present research community as it extends the traditional condition-based maintenance diagnostic approach by introducing prognostic capabilities at the plant shop floor, fully leveraging the key enabling technologies of Industry 4.0.

Success Factors of the Adoption of Smart Factory Transformation: An Examination of Korean Manufacturing SMEs

Article

Full-text available

Jan 2023

A smart factory is a fully automated production system enabled with novel digital technologies. Numerous studies consider its emergence as the arrival of a new wave of production innovation. However, research is scant on why its adoption rate has lagged behind the expectations of investors and policymakers. Thus, this study examined the effect of top management support for information systems, the existing production systems, the perceived usefulness of smart factories, and outsourcing experiences on firms’ intention to adopt smart factories. Using the data of 1,067 Korean manufacturing small and medium-sized enterprises and structural equation modeling, this study finds that the performance of the existing production systems significantly increases the benefits expected from smart production systems, thus strengthening firms’ intention to adopt smart factories. It also finds that the top management’s support for information systems does not have a significant impact on the benefits expected from smart production systems. Furthermore, the overall mechanism of smart factories’ adoption is strengthened when firms develop their production systems in-house. The results of this study provide useful insights for practitioners seeking to transform traditional production systems into smart factories. They also provide a strategic guideline regarding outsourcing experiences.

Novel industrial surface-defect detection using deep nested convolutional network with attention and guidance modules

Article

Full-text available

Nov 2022

Industrial defect inspection plays a crucial role in maintaining the high quality of the product. Although deep learning technologies have been applied to conduct automatic defect inspection, it is still difficult to detect industrial surface defects accurately due to complex variations. This study proposes a novel approach to industrial surface-defect detection that segments defect areas accurately and robustly from the complex background using a deep nested convolutional network (NC-Net) with attention and guidance modules. NC-Net consists of the encoder-decoder with nested residual U-blocks and feature enhancement modules. Each layer block of the encoder and decoder is also represented as a residual U-block. In addition, features are adaptively refined by applying the attention module to the skip connection between the encoder and decoder. Low-level encoder features are refined through edge guidance, and high-level encoder features through mask guidance, which can keep local and global contexts for accurate and robust defect detection. A comprehensive evaluation was conducted to verify the novelty and robustness of NC-Net using four datasets, including magnetic tile surface defects, steel surface defects, rail surface defects, and road surface defects. The proposed method outperformed previous state-of-the-art studies. An additional dataset was also evaluated to prove the extensibility and generality of the proposed approach.

Multimodal Interface for Human–Robot Collaboration

Article

Full-text available

Oct 2022

Human–robot collaboration (HRC) is one of the key aspects of Industry 4.0 (I4.0) and requires intuitive modalities for humans to communicate seamlessly with robots, such as speech, touch, or bodily gestures. However, utilizing these modalities is usually not enough to ensure a good user experience and a consideration of the human factors. Therefore, this paper presents a software component, Multi-Modal Offline and Online Programming (M2O2P), which considers such characteristics and establishes a communication channel with a robot with predefined yet configurable hand gestures. The solution was evaluated within a smart factory use case in the Smart Human Oriented Platform for Connected Factories (SHOP4CF) EU project. The evaluation focused on the effects of the gesture personalization on the perceived workload of the users using NASA-TLX and the usability of the component. The results of the study showed that the personalization of the gestures reduced the physical and mental workload and was preferred by the participants, while overall the workload of the tasks did not significantly differ. Furthermore, the high system usability scale (SUS) score of the application, with a mean of 79.25, indicates the overall usability of the component. Additionally, the gesture recognition accuracy of M2O2P was measured as 99.05%, which is similar to the results of state-of-the-art applications.

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

Article

Full-text available

Oct 2022
J INTELL MANUF

For several industries, the traditional manufacturing processes are time-consuming and uneconomical due to the absence of the right tool to produce the products. In a couple of years, machine learning (ML) algorithms have become more prevalent in manufacturing to develop items and products with reduced labor cost, time, and effort. Digitalization with cutting-edge manufacturing methods and massive data availability have further boosted the necessity and interest in integrating ML and optimization techniques to enhance product quality. ML integrated manufacturing methods increase acceptance of new approaches, save time, energy, and resources, and avoid waste. ML integrated assembly processes help creating what is known as smart manufacturing, where technology automatically adjusts any errors in real-time to prevent any spillage. Though manufacturing sectors use different techniques and tools for computing, recent methods such as the ML and data mining techniques are instrumental in solving challenging industrial and research problems. Therefore, this paper discusses the current state of ML technique, focusing on modern manufacturing methods i.e., additive manufacturing. The various categories especially focus on design, processes and production control of additive manufacturing are described in the form of state of the art review.

A conceptual framework for smart production planning and control in Industry 4.0

Article

Sep 2022
COMPUT IND ENG

This article aims to introduce the challenge (i.e., integration of new collaborative models and tools) posed by the automation and collaboration of industrial processes in Industry 4.0 (I4.0) smart factories. Small- and medium-sized enterprises (SMEs) are particularly confronted with new technological and organisational changes, but a conceptual framework for production planning and control (PPC) systems in the I4.0 context is lacking. The main contributions of this article are to: (i) identify the functions making up traditional PPC and smart production planning and control in I4.0 (SPPC 4.0); (ii) analyse the impact of I4.0 technologies on PPC systems; (iii) propose a conceptual framework that provides the systematic structuring of how a PPC system operates in the I4.0 context, dubbed SPPC 4.0. Thus SPPC 4.0 is proposed by adopting the axes of the RAMI 4.0 reference architecture model, which compiles and contains the main concepts of PPC systems and I4.0. It also provides the technical description, organisation and understanding of each aspect, which can provide a guide for academic research and industrial practitioners to transform PPC systems towards I4.0 implementations. Finally, theoretical implications and research gaps are provided.

International Journal of Data and Network Science 6 (2022). ***-*** International Journal of Data and Network Science The effect of industry 4.0 on sustainability of industrial organizations in Jordan

Article

Full-text available

May 2022

The study aim is to examine the impact of industry 4.0 on sustainability of industrial organizations in Jordan. The population of the study consists of employees at various administrative levels of industrial organizations in Jordan. Due to the large population and the spatial and temporal limitations of the research, it was difficult to collect data using the comprehensive method. Therefore, the random sampling method was applied to collect data from the research population. The structural equation modeling (SEM) technique was used to test the impact of industry 4.0 dimensions on sustainability. The study results confirmed that all dimensions of industry 4.0 had an impact on sustainability. The greatest effect was for cyber-physical systems. Based on this result, researchers recommend the management of industrial organizations to invest in information technology to provide a large variety of data in a very short time and providing appropriate programs for analyzing big data and producing accurate and reliable information that can be used by employees.

Lean methods digitization towards lean 4.0: a case study of e-VMB and e-SMED

Article

Full-text available

Aug 2022
Int J Interact Des Manuf

In the last decade, industry across the globe has been under a massive change in its manufacturing paradigm triggered by the emergence of concepts such as Industry 4.0. Established streamlining philosophies such as Lean manufacturing had to cope with this paradigm shift. In this regard, expansive literature has developed concepts such as Digital Lean or Lean 4.0 to address such change. This publication fits in this same research stream as it provides a comprehensive and detailed conjunction on how to adapt lean instruments and the concepts of Lean Manufacturing to the Industry 4.0 environment. Two Lean tools/methods are taken as examples in this research to showcase something bigger: the difference between a pure digital conversion of a Lean tool (Visual Management Boards) and a possible “novel” Lean method (Single Minute Exchange of Die), enabled by its digitalization. New ways to apply both techniques are proposed. The analysis done in this study shows the feasibility to upgrade and modernize established Lean tools and methods, improving its efficiency and effectiveness, and also the possibility to give new features and scope to some of them, causing not only an improvement but a transformation.

Improving Biological Manufacturing Systems Through A Synthesis Of Methods from Organic Computing Systems

Conference Paper

Full-text available

Jul 2022

Allen Garske

Reinforcement learning based Biological Manufacturing Systems are a promising approach to enhance modern day factories to meet the increasingly demanding market demands, through the use of bio-inspired self-organization methods on the factory floor. Organic Computing is a systems design philosophy created to plan out highly autonomous yet controllable systems which also incorporates some bio-inspired concepts. In order to unify the Biological Manufacturing Systems design with the practical requirements of the factory operators it is proposed to synthesize methods from the both highly compatible design concepts. In this work the need for new factory layouts it presented, as well as a brief overview of the design approaches. Then a case study of a reinforcement learning based Biological Manufacturing System is presented, as well as its properties explored. It is then discussed how it is lacking in terms of real world practicality and how methods from organic computing can be used to make up for some of its weaknesses.

Smart manufacturing systems: a futuristics roadmap towards application of industry 4.0 technologies

Article

Jun 2022

The information and communication technology (ICT) field is rapidly advancing and has developed several disrupting technologies, including artificial intelligence, virtual reality, big data, cloud computing solutions, and the Internet of Things (IoT). This new automation is pervasive throughout production or manufacturing. It allows the integration of the next generation commuting system popularly called Cyber-Physical Systems (CPS) to join the physical and simulated worlds, marking the arrival of industry 4.0, commonly referred to as a fourth industrial revolution. The term ”Industry 4.0” refers to a wide range of technologies applied in the manufacturing industry, encompassing everything from product design to Supply Chain Management (SCM). To contribute to the execution of research in industry 4.0, the current study investigates the specific application of fourth industrial revolution technologies in smart manufacturing systems. First, a theoretical outline of various applications of Industry 4.0 is presented for smart manufacturing systems. Second, CPS-enabled smart (design, control, monitoring, and machining) is introduced through distinct illustrative scenarios. Third, based on these illustrative scenarios, new advancements and their potential applicability through Industry 4.0 in manufacturing industries are discussed. Finally, various challenges and prospects are recognized for Industry 4.0 and explored to assist manufacturing sectors in achieving further growth.

Asynchronous Communication Between Modular Cyber-Physical Production Systems and Arduino Based Industrial Controllers

Chapter

Full-text available

Jan 2022

In a new world where the virtual and physical world is more and more connected, there is a need to project physical devices as digital clones, but the inverse is also true, projecting physical objects from software assets. The proposed work is an approach to connect virtual (software) and the physical (machines) twins using two asynchronous solutions: persistent bi-directional communication and publish subscribe methods on Arduino based controllers. The focus will be in the interaction of virtual and physical reality in order to track the products mainly for academic and investigation proposes but with focus on the applicability on legacy controllers from shop floors, which were not conceived and projected to have these features.KeywordsModular cyber-physical production systemsVirtual environmentIndustrial agentsIndustrial controllersAsynchronous communicationMQTTWebsocketsFIPA

Assessing the readiness of South Africa for Industry 4.0 - analysis of government policy, skills and education.

Conference Paper

Full-text available

Oct 2018

The Fourth Industrial Revolution (Industry 4.0) is imminent in the South African economy. Industry 4.0 is disruptive and challenges the status quo. This paper investigates the preparedness of South Africa for Industry 4.0 implementation. Government policies and initiatives on innovation and manufacturing are reviewed and presented to determine their position relative to Industry 4.0. Key statistics on education, skills and employment are presented and analysed to assess how well prepared the education system is to supply skills required in Industry 4.0. Based on the analysis and reviews of policy and key data recommendations are presented which highlight important actions to ensure optimal Industry 4.0 implementation.

Evaluation of key factors for industry 4.0 technologies adoption in small and medium enterprises (SMEs): an emerging economy context

Article

Apr 2022

Purpose Industry 4.0 (I4.0) not only turns traditional industrial activities upside down but also demonstrates its potential to enhance industrial competitiveness and productivity. In this context, technological advancement and I4.0 is a strategy to be pursued. This study aims to consider different I4.0 technologies by analysing Indian small and medium enterprises (SMEs). Design/methodology/approach Key factors and promising I4.0 technologies were selected using literature analysis and experts’ panel. The appropriate I4.0 technology for Indian SMEs is recommended using the fuzzy complex proportional assessment (COPRAS) method. Findings Results reveal that ability to expand IT infrastructure, change in the organization’s structure and the capacity to analyse key performance indicators as three crucial key factors in I4.0 implementation. In particular, the smart factory is identified as a better I4.0 for Indian SMEs. Originality/value This work has analysed Indian SMEs, but it is appropriate for other developing economies with limited technical resources, financial resources and inadequate skill sets. This work identifies a gap in the current literature, and the findings proposed by this work are oriented to assist decision makers, industrial managers and practitioners in selecting I4.0 technology and enhancing the industrial infrastructure. At the same time, cooperation between the government and industrial community is required to develop programmes for imparting the knowledge of I4.0 among SMEs. The framework used in this study will arm the industrial management in adopting I4.0.

Intelligent Machinery Product Service Blueprint Development and Verification: An Empirical Study of Machine Tool Industry

Article

Full-text available

Jan 2022

Integrating of products and services is regarded as an effective strategy to meet the rapidly changing needs of customers and to create more value for customers. The academic community is also paying more and more attention to the study of product and service integration. In order to verify whether the development of the product service blueprint is suitable for the machine tool industry, this study is divided into four sub-studies, namely service attributes analysis, service requirement analysis, service innovation modeling, and service establishment and validation. Through qualitative and quantitative study and design, product service blueprints of universal standard machines, customized special machines, and composite machining machines for metal deposition are constructed in this study. At the same time, the three dimensions of smart manufacturing of machine tools are constructed in this study, namely virtual factory design and automation system integration, massive data and cloud computing, and smart systems and smart devices. Furthermore, the reliability, validity and importance of the development of new services in this study have been verified.

Deconstructing Industry 4.0: Defining the Smart Factory

Conference Paper

Nov 2021

The advent of the industrial digital transformation and the related technologies of the Industry 4.0 agenda has uncovered new concepts and terminology in the manufacturing domain. Clear definitions represent a solid foundation for supporting the manufacturing research community in addressing this field consistently. This paper addresses this need focusing on the “smart factory”. Starting from a review of the extant literature and integrating it with the outcome of a Delphi study, we propose a new definition of a “smart factory” and discuss its key characteristics. These are related to interconnectivity capabilities and adaptability to the surrounding environment in order to generate and appropriate value. Eventually, such characteristics are exemplified in an empirical context. The aim of this paper is to provide the research community with an updated definition of a smart factory taking both industrial and societal values into account. Furthermore, it may represent a reference for practitioners engaged in the digital transformation of their factories.

Digital twin technologies for automated vehicles in smart healthcare systems

Chapter

Jan 2023

Using Lean Production Tools to Optimize the Business Processes of Locomotive Stock Units of Russian Railroads OJSC

Chapter

Jul 2023

This article explores potential efficiency improvement techniques for locomotive stock units of Russian Railroads, OJSC, as exemplified by a locomotive servicing depot. It analyzes the locomotives technical conditions in the servicing depot based on the rolling stock conditions. The results showed an overall deterioration of the rolling stock technical conditions at the locomotive depot. The key factors behind the increase in the depot’s faulty locomotive percentage were identified. A primary factor increasing the faulty locomotives number is the low quality of spare parts. When analyzing the locomotive depot warehouses, we identified key problems with its incorrect operations. To solve these problems, the authors use Lean Production methods and tools. Material assets and incoming products storage locations were arranged at all locomotive servicing depot warehouses. Acceptance procedures were established for new material assets and material assets removed for replacement, storage, or warehouse issue. The current needs of the depot are assessed based on the material asset records, submit justified refitting applications, upgrade repair technology based on the failure and defect cause statistics, and the operations carried out with each material assets type. An automation option for the warehouse asset movement recording and inventory is suggested. It is efficient only when warehouse logistics processes settle in. A mathematical model used for the suggested automated set of warehouse operations is described. A set of criteria was developed for the timely supply of the required material assets to the locomotive servicing depot and account for the aims to reduce all kinds of production losses.KeywordsLean productionLocomotive depotMaterial assetsProduction toolsOperation automationItem identificationAssigning barcodes

Design of Context-Aware Information Systems in Manufacturing Industries: Overview and Challenges

Chapter

Jul 2023

In the last 30 years, several academic and commercial projects have explored the context-awareness concept in multiple domains. Ubiquitous computing and ambient intelligence are features associated with the 4th generation industry empowering space to interact and respond appropriately according to context. In the scope of Industry 4.0, context-aware systems aim to improve productivity in smart factories and offer assistance to workers through services, applications, and devices, delivering functionalities and contextualised content. This article, through descriptive research, discusses the concepts related to context, presents and analyses projects related to ubiquitous computing and associated with Industry 4.0, and discusses the main challenges in systems and applications development to support intelligent environments for increased productivity, supporting informed decision-making in the factories of the future. The study results indicate that many research questions regarding the analysed projects remain the same, leading the research in the context-aware systems area to minimise issues related to context-aware features, improving the incorporation of Industry 4.0 paradigm concepts.KeywordsContext-awarecontext-aware systemsmanufacturing industriesubiquitous computing

Smart Factory Transformation Using Industry 4.0 toward ESG Perspective: A Critical Review and Future Direction

Article

Jul 2023

The future manufacturing system is rapidly developing owing to the advances in artificial intelligence, the Internet-of-Things, robotics, big data, and cloud-computing technologies. Recently, company valuation using environmental, social, and governance (ESG) evaluation indicators has drawn the attention of many companies and is becoming an essential condition for sustainable development and attraction of investments. However, few studies have quantitatively evaluated smart factories using ESG indicators. Therefore, by reviewing the current status of smart factories, this study evaluates how ESG evaluation indicators are reflected in the implementation and operation of smart factories. Therefore, we reviewed and summarized the literature on the 4M core elements of smart factories: men/women, machines, materials, and methods. In addition, evaluation indicators related to smart factories were selected and classified from the ESG evaluation indicators, and the correlations between them were summarized quantitatively. Based on this, we analyzed how ESG is reflected in current smart factories and revealed core element technologies that have not yet been associated with ESG evaluation indicators. Finally, for the sustainable development of smart factories in the future, the development of smart factory technology and factors that should be considered from the perspective of ESG management are suggested.

Ground Network Security

Chapter

Mar 2023

After the global financial crisis in 2008, IBM introduced the notion of smart earth for the first time, which aims to fully utilize the new generation of information and communication technologies in the sustainable development of the earth. The concept of smart city comes from smart earth, which refers to utilizing information and communication technology (ICT) to improve the quality and performance of urban services, such as energy, transportation and public utilities, reducing resource consumption, waste and overall cost. With the rapid evolution of network communication technologies, networks are of paramount importance to provide ubiquitous connectivity for lots of critical applications in daily life. In recent years, the wireless broadcast system has gained wide attention, and it has been applied in many fields, such as entertainment services, environmental monitoring and military surveillance. However, individual privacy is one of the serious challenges in smart industrial applications since a large amount of confidential information (e.g., credit card information, physiological information for e-health) is transferred over the open wireless channels. In this chapter, we use three parts to introduce the ground network security, including mobile communication network security, Internet of Things security and Internet of Vehicles security.

How Virtual and Augmented Reality Can Boost Manufacturing

Chapter

Jun 2023

Immersive technologies, namely Augmented Reality and Virtual Reality, have immense capacity to improve manufacturing processes in any kind of industry. These are not newly created technologies, some documented experiments date back to the 1960’s, initially with military applications in the United States of America and also development in Universities. Recently an increase in adoption, due to considerable reduction not only in the cost of production of the electronic and optical equipment, but also in the cost and ease of developing experiences with software for use, often free of charge. This article presents not only the theory, existing equipment and use cases of each of these two immersive technologies, but also, through five different themes in the industries (Simulation and Training; Remote Field Services; Team Collaboration; Sales and Marketing; Product or Project Design), the article presents possible use cases and an indication of how to plan and implement experiments with effective results.KeywordsAugmented RealityVirtual RealityIndustry 4.0ManufacturingTrainingField ServiceRemote CollaborationInformation Technology

Dijital Dönüşümün Örgütsel Çevikliğe Etkisi

Thesis

Full-text available

Jan 2023

Adem Özdemir

Günümüz iş dünyasında işletmeler rekabet avantajı elde ederek kar marjlarını artırmak için çeşitli arayışlara girmişlerdir. Bu arayışın en büyük destekçilerinden biri de gelişen teknolojik yeniliklerdir. Gelişen teknoloji işletmeleri, iş yapış şekillerini değiştirmeye mecbur bırakmaya başlamıştır. Teknoloji beraberinde yeni kavram ve uygulamaları getirmiş; işletmeler ise bu yeniliklere uyum sağlamak ve bu yenilikleri kendi lehlerine fırsata çevirmek için mücadele etmektedirler. Teknolojik gelişmelerle iş dünyasına giren kavramların başında hiç şüphe yok ki dijitalleşme ve dijital dönüşüm gelmektedir. Dijital dönüşüm yönetsel süreçlerden, insan kaynaklarına, tedarik zincirinden üretim sistemlerine, bilgi teknolojilerinden finansa kadar pek çok işletme fonksiyonunun yeniden yapılanması gerekliliğini ortaya çıkarmıştır. Bu gereklilikle birlikte işletmelerin ataletten kurtulup çevik olmaları da önem kazanmıştır. Bu önemlilikten hareketle; dijital dönüşümün örgütsel çevikliğe olan etkisinin araştırılması ve dijital dönüşüm ve örgütsel çeviklik arasında nasıl bir ilişkinin olduğunun ortaya konulması amacıyla bu çalışma yapılmıştır. Bu amaçla işletmelerin dijital dönüşüm olgunluk seviyesini ölçebilecek bir olgunluk modeli geliştirilmiştir. Araştırma İSO500/1000 listesinde yer alan Türkiye’nin en büyük işletmelerine uygulanmış ve araştırmaya 409 işletme katılmıştır. Araştırma sonucunda araştırmaya katılan işletmelerin dijital dönüşüm olgunluk seviyesi 4.44, örgütsel çeviklik seviyeleri ise 4.65 bulunmuştur. Araştırmada yapılan yapısal eşitlik modellemesi sonuçlarına göre dijital dönüşümün örgütsel çevikliği etkilediği (β=.89, p=.000) ve dijital dönüşüm ile örgütsel çeviklik arasındaki ilişkiyi belirlemek için yapılan korelasyon analizleri sonucuna göre de aralarında pozitif yönlü ve kuvvetli bir ilişki olduğu (r=.76, p=.000) istatistiksel olarak belirlenmiştir.

Energy efficiency via Industry 4.0: A way to increase organizational resilience in the post-COVID era. A scoping review

Article

Full-text available

Oct 2022

Times of crisis unquestionably reduce economic and social well-being. However, throughout history, companies have been able to survive, to adapt and to grow from sudden and detrimental circumstances mainly through their organizational resilience. Energy efficiency has always been a lifeline for companies during times of crises, a way to reinforce organizational resilience. COVID-19 crisis produced disastrous effects on the global economy. Simultaneously, industry 4.0 which generates a substantial energy efficiency potential, has gained credibility as a viable path to organizational resilience.

Indústria 4.0: componentes e princípios de design

Article

Full-text available

Apr 2023

Nesse trabalho realizou-se um estudo a respeito da Indústria 4.0 cuja definição remete a uma nova era das fábricas denominada a Quarta Revolução Industrial. Um conhecimento necessário para o cenário mundial atual corresponde a uma onda de mudanças tecnológicas que as indústrias começam a experimentar. Embora existam pesquisas e discussões sobre o assunto, permanece ainda certa dificuldade acerca do entendimento e abrangência do assunto entre os pesquisadores. Vivenciada a grandes passos pela Alemanha, nem mesmo as suas empresas que já atuam com smart factoy conseguem ter uma definição clara e precisa dessa nova fase industrial. São estas questões em aberto que motivaram o desenvolvimento desta pesquisa com objetivo de esclarecer algumas dúvidas especificamente sobre os princípios e designs da Indústria 4.0. A pesquisa é classificada no que se refere à metodologia, como qualitativa, quanto aos fins é aplicada e quanto aos meios é bibliográfica. Para adentrar no objetivo da pesquisa foi necessário realizar um estudo de várias fontes bibliográficas, que permitiu identificar grandes vantagens que estão em curso e se referem ao aumento eficiência, capacidade de gerar informações em tempo real sobre toda a operação industrial, capacidade de “ver” e interagir máquinas entre si e máquinas e funcionários a fim de restringir retrabalho e consumo de energia. No entanto, também se encontrou diversos desafios a serem vencidos, tais como a necessidade de existir novas qualificações profissionais a serem oferecidas pelas instituições de ensino e novas formas destes profissionais interagir com todo o processo produtivo. Portanto, a Indústria 4.0 possui potencial significativo para aumentar a competitividade das empresas ao mesmo tempo que a interação entre funcionários e máquinas dos setores da empresa demandam novas atitudes.

Advanced Technology in Aquaculture – Smart Feeding in Marine Fish Farms

Chapter

Apr 2023

In this chapter, we discuss how digital tools can be used to achieve more intelligent feeding and nutrition in commercial cage-based farming. Using farmed salmon as a model species, we first outline industrial practices in cage-based farming, and then present the state-of-the-art in how digital technologies are being utilized in aquaculture research and industry. We then discuss how the intelligent feeding methods of the future could be devised based on the current state-of-the-art, and further how these could potentially be important for ongoing industrial developments toward new production concepts for fish farming.Our findings show that many of the digital components required to realize intelligent feeding systems in commercial fish farms are already in place, or under development. It is thus already possible to start combining existing systems into new technological solutions that improve our ability to monitor, adjust, and optimize the feeding process in aquaculture fish production. This is the focus of several ongoing research efforts that aspire to apply the principles of precision fish farming. A similar trend is also present in the industrial sector, manifested through the rapid growth in the portfolio of commercially available products for feeding optimization in aquaculture.KeywordsFish farmingSmart fish nutritionFeeding technologyPrecision fish farmingAtlantic salmonAquacultureIntelligent fish feedingSustainable fish farmingBiosensorsTelemetryOptical sensorsHydroacoustic sensorsMathematical fish modellingSensor fusionUnderwater roboticsIntensive fish farmingMarine fish farmsFeedback controlState estimationFuture methods for fish farming

AI Factory: Theories, Applications and Case Studies

Book

Mar 2023

The implementation of Thread Network for a Smart Factory

Conference Paper

Dec 2022

A Taxonomy Study on Key Dimensions Which May Help SMEs for Industry 4.0 Implementation

Article

Dec 2022

The fourth industrial revolution is enticing businesses to go digital. In this paper, we have determined the dimensions that help in implementing industry 4.0 in SMEs. A systematic literature review (SLR) protocol has been used to identify the dimensions. A database search has been conducted to get an overview of industry 4.0 adoption that includes 68 studies from 2007 to 2022. The results of SLR revealed 15 potential dimensions which affect industry 4.0 implementation. The evidence in support of these dimensions is assessed by performing rigor and relevance study. Quality assessment of the studies has been done based on rigor and relevance criterion. 21 of the 32 studies have a high degree of significance. The studies’ relevance score, on an average, is around 3, indicating strong evidence in support of industry 4.0. Research for industry 4.0 requires a high level of rigor. The findings of this study can be applied to industry 4.0 implementation research, with an emphasis on empirical evidence. More research can be undertaken on the dimensions with the help of industry professionals for successful implementation of industry 4.0 concept.

Smart Factory Navigator

Chapter

Dec 2022

In recent years, the adoption and application of new technologies - Internet of Things (IoT), cloud computing, augmented reality (AR) and artificial intelligence (AI), to name a few - has accelerated in manufacturing. To remain competitive, manufacturing companies are looking to these digital technologies as a way to increase the efficiency and flexibility of their production. This chapter describes the fundamentals of smart manufacturing, including key concepts and technologies. Implementing the smart factory approach is a complex transformation and goal-oriented process. The Smart Factory Navigator therefore proposes an integrated approach.

MGA-Net+: Acceleration-based packaging work recognition using motif-guided attention networks

Article

Dec 2022

This study presents a new method for recognizing complex human activities within the logistics domain, such as packaging operations, using acceleration data from a body-worn sensor. The recognition of packaging tasks using standard supervised machine learning is complex because the observed data vary considerably depending on the number of items to be packed, the size of the items, and other parameters. In this study, we focused on the characteristics and necessary key actions (motions) that occur during a specific operation. For instance, when the packaging tape is stretched while assembling the shipping boxes. To focus on these characteristic actions when recognizing data, we propose the use of an attention-based neural network. With our method, the attention-based neural network’s training is guided such that it’s focus is on the motifs. In addition, this method was designed to accurately recognize short operations by leveraging data augmentation techniques. We tested our method on two logistics datasets and achieved a 3.9% improvement over the previous MGA-Net approach.

Detection and Correction of Buffer Occupancy Data Error in Two-Machine Bernoulli Serial Lines

Conference Paper

Aug 2022

ОСОБЛИВОСТІ ФОРМУВАННЯ СИСТЕМИ МЕНЕДЖМЕНТУ «РОЗУМНИМИ ПІДПРИЄМСТВАМИ»

Article

Aug 2022

Стаття присвячена опису особливостей формування системи менеджменту «розумними підприємствами». Проаналізовано погляди науковців та практиків на трактування терміну «розумне підприємство». Охарактеризовано основні типи підприємств, в залежності від епіцентру діджитал-трансформацій, – «цифрові» (Digital), «розумні» (Smart) і «віртуальні» (Virtual). Обґрунтована актуальність переходу суб’єктів господарювання на рівень «розумного підприємства». Описано основні елементи процесу переходу суб’єкта господарювання на рівень «розумного підприємства», що в сукупності забезпечать синергетичний ефект у досягненні максимальної ефективності від цифрової трансформації та значне зростання результатів діяльності підприємства. Виокремлено основні переваги підприємств, у яких відбулася цифрова трансформація бізнесу. Метою статті є дослідження теоретичних та практичних аспектів щодо особливостей цифрової трансформації сучасних підприємств.

Application of Machine Learning in the Machining Processes: Future Perspective Towards Industry 4.0

Chapter

Feb 2023

Cellular manufacturing design 1996–2021: a review and introduction to applications of Industry 4.0

Article

Sep 2022

As globalisation and competition grow rapidly, adopting a flexible manufacturing philosophy becomes more critical for manufacturers. Cellular Manufacturing System (CMS) is among one of the most favourable ones which has been deeply studied in academia since this philosophy was coined in 1925. To design the manufacturing system efficiently and effectively, the management team needs to have a comprehensive representation of the definitions, classifications, solution approach to cellular manufacturing design problems. In this study, exact methods, heuristic approaches, metaheuristic techniques, and artificial intelligence strategies for cellular manufacturing design are reviewed. A comparison of solution approaches is discussed and based on this analysis, some suggestions for future research are proposed. Moreover, we tried to highlight the importance of investigating sustainability decisions related to CMS problems, and integration of supply chain decisions with CMS decisions which have not been sufficiently studied to identify a research direction for researchers to model and analyse those issues. Finally, we briefly discuss the placement of CMS as one of the major production systems in the industry 4.0 evolution paradigm. Reviewing the adoption of industry 4.0 techniques by CMS sheds light on the contribution of methodological approaches in transition to intelligent CMS.

Acceleration-based Human Activity Recognition of Packaging Tasks Using Motif-guided Attention Networks

Conference Paper

Mar 2022

Research on Motion Control of Mobile Manipulator for Dynamic Target Grasping

Conference Paper

Aug 2022

Economia da Informação na Indústria 4.0

Article

Full-text available

Aug 2022

O objetivo geral do ensaio é verificar de que forma a economia da informação se beneficia das ferramentas da Indústria 4.0. Os objetivos secundários são mapear as principais plataformas digitais utilizadas para a disseminação de informação industrial rapidamente e em larga escala e identificar as vantagens econômicas utilizadas por empresas dentro da indústria 4.0. A instrumentalização de coleta de informações deste ensaio se deu a partir de um apanhado bibliográfico e referencial das áreas de (i) Economia da Informação, (ii) Indústria 4.0 e (iii) Digitalização empresarial. Os principais resultados demonstram que soluções como big data, data science e inteligência artificial podem corroborar ampliando os efeitos multiplicadores da Economia da Informação. A contribuição teórica se dá por evidenciar para as pesquisas seminais, os fluxos informacionais estabelecidos nas novas plataformas de negócios contempladas na Indústria 4.0. Metodologicamente, o ensaio contribui em trazer à luz novas perspectivas sobre como a economia da informação pode contribuir para o avanço da Indústria 4.0, explorando caminhos pouco pavimentados nas literaturas de ciências da informação, econômicas e sociais. A relevância do presente ensaio está em apontar plataformas que exercem soluções para economia da informação pavimentando o campo de estudo para análises posteriores. Também objetiva-se apresentar novas possibilidades de ferramentas teóricas para a Indústria 4.0 e enquadrar o fenômeno no campo de estudo da economia e administração.

Emerging Smart Manufactory: Industry 4.0 and Manufacturing in India: The Next Wave

Chapter

Jan 2023

Today design-manufacturing industry is automated and digital, where machines communicate with every other. A clever factory equipped with statistics alternate in industrial, the Internet of Things (IoT) is the forthcoming, and specialists are shouting it uprising Industry 4.0. The future factory is going to comprise a new integrative, where now not only all manufacturing sources (sensors, actuators, machines etc.) are connected and trade data automatically and Industry 4.0 implies a whole communication network will exist between a range of companies, factories, supplier, logistics, resources, customers. Reports peg the clever manufacturing facility enterprise to contact $215 billion through 2025, and there has been vital financial device in the world that is now embracing it. The contemporary globalization is confronted by way of the usage of the challenge to meet the always-growing global demand for capital and purchaser items by means of using concurrently making certain a sustainable evolve of human existence in its social. Industrial revolutions and future view of Industry 4.0 see the introduction of disruptive new applied sciences, the current developments of automation, and knowledge alternate that is opening to arise in manufacturing technologies. This consists of cyber-bodily techniques IoT, information analytics, cloud computing, and artificial Intelligence (AI). Implementation will advocate radically altering the documents framework and industry organization methods of your entire operation.KeywordsIndustry 4.0Manufacturing systemsCloud manufacturingIoTSensorDeployment

PLC as the Main Controller for Additive Manufacturing Machines

Chapter

Jun 2022

Additive manufacturing (AM) is the process of manufacturing a physical object, layer by layer, from a 3D digital model. Despite the advantages of using this technology, its adoption, especially by users with fewer resources, is still limited by the high cost of machines, raw materials, and the complexity of the process. To make this technology more accessible, increasing the cost-effectiveness of the machines, this work analyzes the feasibility of using a single programmable logic controller (PLC) as the main controller of an additive manufacturing machine, as an alternative to the CNC and PLC structure used in most of the applications of this type. Through a PLC programming structure, it was possible to load an instruction file in G code generated by a market slicer program, convert it into axis position commands, and verify that the deposition trajectory was executed.KeywordsAdditive manufacturingFused filament fabricationWire arc additive manufacturingDirect energy depositionPLCPosition axis controlIndustry 4.0

SMART Technologies: New Normal Manufacturing Industry 2020

Chapter

May 2022

The manufacturing industry plays a paramount role in the world economy, accounting for almost 16% of the global GDP in 2018. Manufacturing has been identified as the key driver of dynamic growth and development of the country. The COVID-19 pandemic has caused immense devastation around the world. Due to the downturn in the manufacturing industry along with the factory blackout, the coronavirus epidemic reduced the global FDI by 5-15%. This chapter aims to throw light on measures taken by manufacturers to combat the impact of the COVID-19 havoc. It will discuss how internet of things and artificial intelligence will help manufacturing industry to recover effectively and efficiently post pandemic. It would suggest a framework to manufacturing industry on how it can come back in a new normal position post-COVID-19 scenario. Manufacturers, who acknowledge the new standard policies discussed in the present paper and operate on it, will get enough growth opportunities and can have long-term sustainable success in the future.

Autonome Produktion: Die Vision der vernetzten und selbstoptimierenden Fabrik

Chapter

Apr 2022

How energy efficiency, smart factory, and mass personalization affect companies in industry 4.0

Conference Paper

Apr 2022

The concept of industry 4.0 has significant potentials to enhance organizational performance so as to cope with industrial change and to ensure market competitiveness in the world coordinated by industrial and scientific organizations using technical, economic, and sociopolitical parameters. The objectives of this research are to investigate the effects of energy efficiency improvement, smart factory, and mass personalization on organizational performance; describe the causality between the independent and the response variables; develop a new model and build theories based on Partial Least Squares Structural Equation Model (PLS-SEM); and generate specific propositions for industrial practitioners to improve their organizational performance. The study validated and assessed the proposed model using discriminant validity, reliability of measures, item loadings, and convergent validity based on the data gathered from employees of various industrial organizations. This study found that energy efficiency improvement, smart factory, and mass personalization were key driving factors on organizational performance in industry 4.0.

ANALYSIS OF THE COMPETENCY OF FRESH GRADUATED HIGHER EDUCATION IN SUPPORTING INDUSTRIAL ERA 4.0

Article

Full-text available

Feb 2020

This article analyzes the need for Industry 4.0 HR competencies. The study was conducted at a number of tertiary institutions in Medan, where the sample was determined by purposive random sampling. The variables used in this study include; a) sense-making, b) social intelligent, c) novel and adaptive thinking, d) cross-cultural competency, e) computational thinking, f) new-media literacy, g) transdisciplinarity, h) design thinking, i) cognitive load management, j) virtual collaboration. Furthermore, the data were analyzed using the Confirmatory Factor Analysis approach. The output of this research is expected to provide input and strategies for universities in strengthening the quality of the fresh graduated HR output produced. The results of this study indicate that based on the results of Confirmatory Factor Analysis, the 10 variables used have a positive relationship between variables and can be an estimator to see how fresh graduated human resources are ready to face industry 4.0.DOI: 10.24071/ijiet.2020.040107

Beyond the Hype: Smart Manufacturing and Sustainable Excellence for SMEs

Chapter

Mar 2022

The concept of business excellence has grown worldwide as a new trend that takes TQM implementation frameworks and quality award schemes to the next level. However, the business excellence trend has primarily focused on enterprise longevity and financial security, leaving out the environment and societal dimensions (Edgeman, Rick, and Jacob Eskildsen. 2014. “Modeling and Assessing Sustainable Enterprise Excellence.” Business Strategy and the Environment 23 (3). Wiley Online Library: 173–87.).

The Stuttgart Enterprise Model-Integrated Engineering of Strategic & Operational Functions

Article

Jan 2006

The Computer for the 21st Century

Article

Sep 1991

Mark Weiser

Specialized elements of hardware and software, connected by wires, radio waves and infrared, will be so ubiquitous that no one will notice their presence.

Hémoglobine glyquée

Article

Feb 2008

Jean-Marie Manus

A Novel Broadband Ultrasonic Location System

Conference Paper

Nov 2002

Indoor ultrasonic location systems provide fine-grained position data to ubiquitous computing applications. However, the ultrasonic location systems previously developed utilize narrowband transducers, and thus perform poorly in the presence of noise and are constrained by the fact that signal collisions must be avoided. In this paper, we present a novel ultrasonic location system which utilizes broadband transducers. We describe the transmitter and receiver hardware, and characterize the ultrasonic channel bandwidth. The system has been deployed as a polled, centralized location system in an office. Test results demonstrate that the system can function in high levels of environmental noise, and that it has the capability for higher update rates than previous ultrasonic location systems.

Smart Factory - Bridging the gap between digital planning and reality

Article

May 2005

In basic research projects the Stuttgart model of adaptive, changeable, and virtual enterprises has been for-mulated. Regarding to this model a new perspective with the usage of ubiquitous computing is discussed, which allows the collection and distribution of information and knowledge at all places of work. This informa-tion is used to bridge the gap between digital planning and work shop reality. The approach is a dynamic system that manages production fluctuations using decentralized communication, planning, and information support. Using a meta-model of the smart factory location, sensor integration, and communication structures are developed that are integrated into an augment reality device. This provides a decentralized system, which uses intelligent manufacturing equipment in order to accomplish a highly flexible production as well as a feedback tool to further reduce inefficient preparation results. As a result a minimum in complexity, costs, and time consumption is created. In this paper, the potential and architecture of smart factories based on wireless communication, location technologies, augmented reality, and integrated sensors are presented with a focus on real-time data to manage mobile resources in the production environment.

Grundlagen ubiquitärer Systeme und deren Anwendung in der "Smart Factory"

Article

Jan 2003

Die rasch fortschreitende Entwicklung kleiner mobiler Geräte sowie mit eingebetteter Sensorik und Aktorik versehener Alltagsgegenstände ermöglicht eine Vielzahl neuartiger Anwendungen. Die Fähigkeit zur drahtlosen Kommunikation und zur Positionsbestimmung bereitet die Basis lokations- und kontextbezogener Systeme, die seit einigen Jahren im Projekt Nexus an der Universität Stuttgart untersucht werden. Der Einsatz dieser Technologien im produktionstechnischem Umfeld, z.B. der hier vorgestellten dezentralen Betriebsmittelverwaltung, eröffnet dabei ein vollkommen neues Anwendungsgebiet.

The Computer for the Twenty-First Century

Smart Factory - A Step towards the Next Generation of Manufacturing

Abstract

No full-text available

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