Cloud Manufacturing: Strategic Vision and State-of-the-Art

Cloud manufacturing, a service oriented, customer centric, demand driven manufacturing model is explored in both its possible future and current states. A unique strategic vision for the field is documented, and the current state of technology is presented from both industry and academic viewpoints. Key commercial implementations are presented, along with the state of research in fields critical to enablement of cloud manufacturing, including but not limited to automation, industrial control systems, service composition, flexibility, business models, and proposed implementation models and architectures. Comparison of the strategic vision and current state leads to suggestions for future work, including research in the areas of high speed, long distance industrial control systems, flexibility enablement, business models, cloud computing applications in manufacturing, and prominent implementation architectures

Model similarity evidence and interoperability affinity in cloud-ready Industry 4.0 technologies

Cloud computing is revolutionizing IT environments in most fields of economy. Its service-based approach enables collaboration and data exchange on higher level, with better efficiency and parallel decreasing costs. Also manufacturing environments can benefit from cloud technology and better fulfill fast changes in market demands, by applying diverse cloud deployment models and by virtualizing manufacturing processes and assets into services. As cloud becomes the basis of most innovative manufacturing IT systems, its future role in Cyber-physical Production Systems has to be properly investigated, as their interoperability will play a role of vital importance. In this paper, after a brief introduction to cloud criticality and cloud-based manufacturing, the mutual conceptual similarities in modelling distributed industrial services of two of the major standardization frameworks for industrial Internet architectures are presented: the Industrial Internet Reference Architecture (IIRA) and the Reference Architectural Model Industrie (RAMI 4.0). It is also introduced how their integration feasibility finds a strong affinity in specifications of the Open Connectivity Unified Architecture, a service-oriented architecture candidate to the standardization of Industrial Internet of Things based manufacturing platforms. Finally, the preliminary architecture of a prototype Smart Factory is presented as a case study

Challenges of cloud technology in manufacturing environment

The rapid growth Information systems and advanced network technologies have significant impact on enterprises around the world. Enterprises are trying to gain competitive advantage in open global markets by using the latest technologies, along with advanced networks, to create collaboration, reduce costs, and maximize productivity. The combination of latest technologies and advanced manufacturing networks technologies lead to growth of new manufacturing model named Cloud Manufacturing which can shift the manufacturing industry from product-oriented manufacturing to services-oriented manufacturing. This paper explores the literature about the current Manufacturing problems, understands the concept of Cloud Computing Technology, introduces Cloud Manufacturing and its role in the enterprise, and investigates the obstacles and challenges of adopting Cloud Manufacturing in enterprises

Cloud-based manufacturing-as-a-service environment for customized products

This paper describes the paradigm of cloud-based services which are used to envisage a new generation of configurable manufacturing systems. Unlike previous approaches to mass customization (that simply reprogram individual machines to produce specific shapes) the system reported here is intended to enable the customized production of technologically complex products by dynamically configuring a manufacturing supply chain. In order to realize such a system, the resources (i.e. production capabilities) have to be designed to support collaboration throughout the whole production network, including their adaption to customer-specific production. The flexible service composition as well as the appropriate IT services required for its realization show many analogies with common cloud computing approaches. For this reason, this paper describes the motivation and challenges that are related to cloud-based manufacturing and illustrates emerging technologies supporting this vision byestablishing an appropriate Manufacturing-as-a-Service environment based on manufacturing service descriptions

Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

Special Session on Industry 4.0

No abstract available

A front-end system to support cloud-based manufacturing of customised products

In today’s global market, customized products are amongst an important means to address diverse customer demand and in achieving a unique competitive advantage. Key enablers of this approach are existing product configuration and supporting IT-based manufacturing systems. As a proposed advancement, it considered that the development of a front-end system with a next level of integration to a cloud-based manufacturing infrastructure is able to better support the specification and on-demand manufacture of customized products. In this paper, a new paradigm of Manufacturing-as-a-Service (MaaS) environment is introduced and highlights the current research challenges in the configuration of customizable products. Furthermore, the latest development of the front-end system is reported with a view towards further work in the research

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems