5 finfinal - Smart Manufacturing Objects.pdf

Rapid developments in ICT totally reshape manufacturing as machines, objects and equipment on the shopfloors will be smart and online. Interactions with virtualisations and models of a manufacturing unit will appear exactly as interactions with the unit itself. These virtualisations may be driven by providers with novel ICT services on demand that might jeopardise even well established business models. Context aware equipment, autonomous orders, scalable machine capacity or networkable manufacturing unit will be the terminology to get familiar with in manufacturing and manufacturing management. Such newly appearing smart abilities with impact on network behaviour, collaboration procedures and human resource development will make distributed manufacturing a preferred model to produce. Keywords: virtualisation, networkability, autonomous unit, smart manufacturing

Financial and credit activity problems of theory and practice

The aim of the article is to learn the processes of smart economy, in particular such aspects as a development of a smart manufacturing and a formation of a smart market. With the help of graphic visualization methods, the trends of digitalization, the penetration of the latest ICT technologies into global production and logistics processes were characterized. The methods of system analysis and generalization, made it possible to formulate the key imperatives, which characterize the formation of smart manufacturing: comprehensive digitalization, the spread of artificial intelligence, the industrial robotics and the industrial Internet of Things, the formation of global supply chains and a new type of production networks. The important features of Industry 5.0 are: a trend of green economy and ensuring the stability and the resilience of the system. The extrapolation of the obtained conclusions to Ukrainian economy made it possible to determine the key imperatives for its recovery in...

International Journal of Production Research , 2018

Manufacturing has evolved and become more automated, computerised and complex. In this paper, the origin, current status and the future developments in manufacturing are disused. Smart manufacturing is an emerging form of production integrating manufacturing assets of today and tomorrow with sensors, computing platforms, communication technology , control, simulation, data intensive modelling and predictive engineering. It utilises the concepts of cyber-physical systems spearheaded by the internet of things, cloud computing, service-oriented computing, artificial intelligence and data science. Once implemented, these concepts and technologies would make smart manufacturing the hallmark of the next industrial revolution. The essence of smart manufacturing is captured in six pillars, manufacturing technology and processes, materials, data, predictive engineering, sustainability and resource sharing and networking. Material handling and supply chains have been an integral part of manufacturing. The anticipated developments in material handling and transportation and their integration with manufacturing driven by sustainability, shared services and service quality and are outlined. The future trends in smart manufacturing are captured in ten conjectures ranging from manufacturing digitisation and material-product-process phenomenon to enterprise dichotomy and standardisation.

IFIP Advances in Information and Communication Technology

Smart Manufacturing seeks to integrate advanced manufacturing methods, operational technologies (OT), and information and communication technologies (ICT) to drive the creation of manufacturing systems with greater capabilities in cost control and performance. A crucial differentiation of smart manufacturing systems (SMS) lies in their architectures, which are organized as networks of cooperating manufacturing components specialized for different functions as opposed to the previous organization characterized by rigid, hierarchically-integrated layers of application components. This "ecosystem" of manufacturing components enables SMS that can provide heretofore unattainable levels of performance for manufacturers with respect to agility, productivity, and quality. This paper provides a study of the architectural impact of individual ICT technologies on the emerging manufacturing ecosystem that potentially eliminates the need to design manufacturing systems based on the hierarchical levels of the legacy ISA 95 model. Additionally, we propose a service-oriented SMS architecture that leverages the benefits of ICT and the safety and security requirements from the OT domain. Key challenges of implementing such architectures are also presented.

Annual Reviews in Control, 2019

This paper summarizes a vision of the challenges facing the so-called "Industry of the Future" as studied by the research community of the IFAC Coordinating Committee 5 on Manufacturing and Logistics Systems, which includes four Technical Committees (TC). Each TC brings its own vision and puts forward trends and issues important and relevant for future research. The analysis is performed on the enterprise-level topics with an interface too other relevant systems (e.g., supply chains). The vision developed might lead to the identification of new scientific control directions such as Industry 4.0 technology-enabled new production strategies that require highly customised supply network control, the creation of resilient enterprise to cope with risks, developments in management decision-support systems for the design, and scheduling and control of resilient and digital manufacturing networks, and collaborative control. Cobots, augmented reality and adaptable workstations are a few examples of how production and logistic systems are changing supporting the operator 4.0. Sustainable manufacturing techniques, such closed-loop supply chains, is another trend in this area. Due to increasing number of elements and systems, complex and heterogeneous enterprise systems need to be considered (e.g., for decision-making). These systems are heterogeneous and build by different stakeholders. To make use of these, an environment is needed that allows the integration of the systems forming a System-of-Systems (SoS). The changing environment requires models which adapt over time. Some of the adaptation is due to learning, other mechanisms include self-organisation by intelligent agents. In general, models and systems need to be modular and support modification and (self-)adaptation. An infrastructure is needed that supports loose coupling and evolving systems of systems. The vision of the overall contribution from the research community in manufacturing and logistics systems, over the next few years is to bring together researchers and practitioners presenting and discussing topics in modern manufacturing modelling, management and control in the emerging field of Industry 4.0-based resilient and innovative production SoS and supply networks.

IFAC-PapersOnLine, 2017

Future manufacturing is becoming "smart"capable of agilely adapting to a wide variety of changing conditions. This requires production plants, supply chains and logistic systems to be flexible in design and reconfigurable "on the fly" to respond quickly to customer needs, production uncertainties, and market changes. Service-Oriented Architecture (SOA) provides a promising platform to achieve such manufacturing agility. It has proven effective for business process adaptation. When combined with the emerging Internet of Things (IoT) technology and the concept of cyber-physical production systems, it is expected to similarly revolutionize real-time manufacturing systems. This paper proposes a new concept of cyberphysical manufacturing services (CPMS) for service-oriented smart manufacturing systems. In addition, we propose a modeling framework that provides appropriate conceptual models for developing and describing CPMS and enabling their composition. Specifically, the modeling framework separates service provision models from service request models and proposes the use of standardized functional taxonomies and a reference ontology to facilitate the mediation between service requests and service consumptions. A 3D-printing use case serves as an example implementation of an SOA-based smart manufacturing system based on our proposed modeling framework.

IFAC-PapersOnLine, 2016

Smart Factory of Industry 4.0 is a complex system containing various aspects and capabilitis of the factory of the future based on Internet of Things (IoT), Internet of Men (IoM), and Internet of Service (IoS). There have been numerous concepts and scenarios how it looks like, how it should be, and commercial vendors advocate their products can provide solutions to some parts of the Smart Factory. This often confuses stakeholders who want to adopt Smart Factory. To show and guide the multi-aspects and technology for Smart Factory in a comprehensive fashion, our research team developed a conceptual framework, called Cyber Physical Manufacturing System (CPMS PS). In this paper, we focus on the manufacturing information bus from the perspective of CPMS. Specifically, we developed a reference architecture for the manufacturing information bus for the Smart Factory that can be used for information acquisition, analysis, and application for the various stakeholders at the levels of Machine, Factory, and Enterprise Resource Planning. Also in this paper, an implementation process of the reference architecture is presented and demonstrated via case study.

Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems

Smart Factory concepts describe fully networked, autonomous factories and form an essential part of flexible, but still highly efficient production systems. The requirements for the further development of existing production environments towards a Smart Factory are multidimensional and vastly complex. Many companies therefore fail in the structured realization of a holistic Smart Factory concept. They either focus one dimension of the challenge or merely address the maximum penetration of powerful technologies. This chapter addresses this issue and describes a systematic development path towards a Smart Factory by means of a domain specific maturity model. Based on the analysis of existing maturity models, requirements are derived which must be considered when realizing a Smart Factory. In total, 20 design fields (e.g., degree of intelligence, communication protocols, human-machine-interface and IT security) and respective detail descriptions result from this research. They holistic...

Computers in Industry, 2020

Smart manufacturing is characterized as transparent shop floor production, rapid and intelligent responses to dynamic changes, and a utilization of high-performance inter-cooperation networks. Smart manufacturing and a global appetite for personalized products have transitioned industry from mass production into the age of mass customization. Increased autonomy is slowly changing customer expectations as well, enabling customers to modify a product design not only during an order, but sometimes even long after placing an order. In this context, this paper fills a gap by presenting a data-centric infrastructure to enable interaction with a "global, virtual data space," which overcomes the problems with traditional direct access methods such as interoperability and compatibility. Using a Cyber-Physical System (CPS), resource monitoring on the shopfloor as well as multiple parities beyond the enterprise boundary will be interconnected through this data-centric infrastructure. A semantic knowledge management system, which encompasses product lifecycle knowledge and manufacturing process ontology, is developed as the data schema in the data-centric infrastructure. In comparison to relational databases which are effective at handling paper forms and tabular structure, the flexible schema of graph databases enable these to handle dynamic and uncertain variables. These capabilities are deemed critical for a platform supporting real-time information exchange between customer, manufacturer and collaborators. One advantage of such a system allowing for real-time information exchange is that it enables last minute order changes by the customer, allowing for product design changes even after production has started on the order. The other advantage is that it allows manufacturing managers to monitor the productivity of customer-directed, dynamic manufacturing processes by utilizing Dynamic Value Stream Mapping (DVSM) methods.

2018 IEEE 16th International Conference on Industrial Informatics (INDIN), 2018

Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic.