Concept Of Cloud Manufacturing Research Articles

Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology

Blockchain technology has been enjoying rapid development in numerous areas where trust, safety, and global payments are deemed important. In this research, we introduce a framework that integrates blockchain technology with the emerging concept of cloud manufacturing. It has the potential to dramatically improve the feasibility and applicability of cloud manufacturing. Our focus is on the pricing strategies for service providers in bidding for jobs in such a system. A scenario is developed based on cloud additive manufacturing services. A game theoretic approach for pricing simulation is proposed in the research, and a fuzzy algorithm is employed in the pricing decision. Two pricing policies are considered: one is that the information of players is unknown to each other, and the other is that the information of players who are within a limit of Euclidean space is known to each other. The effects of system load and the weight coefficients in KNN recommendation algorithm are also studied. The results show that the pricing policy has significant effect on revenue generation for providers, and the increase of system load helps to grow revenue for providers only when the machine utilization is low and job waiting time is short. In addition, the system seems to be less sensitive to the change of KNN weights in terms of individual provider and system revenues.

Cloud manufacturing: key issues and future perspectives

ABSTRACTSince the introduction of the concept of cloud manufacturing in 2010, research on it has been ongoing for more than eight years, and much progress has been made. However, existing research indicates that people lack common and comprehensive understandings of some of the key issues with cloud manufacturing such as the concept, operation model, service mode, technology system, architecture, and essential characteristics. Moreover, few studies discuss in depth the relationships between cloud manufacturing and some closely related concepts such as cloud computing-based manufacturing, Cyber-Physical Systems (CPS), smart manufacturing, Industry 4.0, and Industrial Internet. Knowledge as a core supporting factor in cloud manufacturing has rarely been discussed systematically. Also, so far there has been no standardised definition for cloud manufacturing yet. All these are key issues to be further discussed and analysed in cloud manufacturing. In order to clarify the issues above and provide reference for future research and implementation, this paper conducts a comprehensive, systematic, and in-depth discussion and analysis of the aforementioned issues in cloud manufacturing and presents an alternative definition for cloud manufacturing based on the analysis of 12 existing definitions. Future perspectives of cloud manufacturing are also discussed with respect to both academic research and industrial implementation.

A decision-making methodology for the cloud-based recycling service of smart products: a robot vacuum cleaner case study

ABSTRACTThe smart product represents a new type of products, which contains software and hardware components. Many obsolete smart products are required to be recycled each year. In the developing countries, the inappropriate treatment of obsolete smart products contaminates the natural environment. This study aims to coordinate the abilities of social recycling organisations and improve the recovery rate of waste smart products. A framework of the recycling service for smart products is proposed based on the concept of cloud manufacturing. In the framework, a smart product ontology is designed to integrate the lifecycle data generated by the smart product. To decide the recycling choice of the components of smart products with the lifecycle data, a fuzzy-rule-based decision method is proposed. In cloud-based recycling service, the abilities of different recycling factories are virtualised as a pool of recycling resources. The virtualisation is achieved by the recycling resource ontology. In order to select optimal recycling resources and encapsulate the recycling service, a grey-relational-analysis-based method is proposed. A robot vacuum cleaner, which is a smart product, is adopted to demonstrate the proposed decision methods. The results show that the methods are effective for deciding the cloud-based recycling service for smart products.

Cloud Manufacturing Platform and Architecture Design

Abstract Cloud Manufacturing (CMfg) is an emerging networked manufacturing paradigm and service-oriented manufacturing model, in which distributed manufacturing resources are made available by providers according to consumers’ requirements as on-demand manufacturing services via networks (manufacturing clouds) and cloud manufacturing service platforms. Considering the concept of cloud manufacturing and its operation principle, the paper designs and introduces new proposal of cloud manufacturing service platform architecture, including the following six layers: physical resources layer, soft resources layer, virtual resources layer, services layer, application layer and service-oriented interface layer. After surveying majority of papers introducing architectures of CMfg service platforms, the paper recommends to map both hard as well as soft resources into cloud services from resource layers to virtual resource layer which highlights the core idea of the concept. The paper discusses also the fundamentals of the CMfg paradigm, introduces three groups of actors that participate in a cloud manufacturing system, as well as indicates briefly a typical hierarchy architecture of cloud manufacturing system.

Moving towards Real-time Data-driven Quality Monitoring: A Case Study of Hard Disk Drives

Since its emergence, the cloud manufacturing concept has been transforming the manufacturing and remanufacturing industry into a big data and service-oriented environment. The aggressive push toward data collection in cloud-based and cyber-physical systems provides both challenges and opportunities for predictive analytics. One of the key applications of predictive analytics in such domains is predictive quality management that aims to fully exploit the potentials provided by the enormous data collected via cloud-based systems. As a case study, a data set of hard disk drives’ Self-Monitoring, Analysis and Reporting Technology (SMART) attributes from a cloud-storage service provider has been analyzed to derive some insights about the challenges and opportunities of using product lifecycle data. An analysis of time-to-failure monitoring of hard disk drives in real-time has been carried out and the corresponding challenges have been discussed.

A Mathematical Model for Task Scheduling in Cloud Manufacturing Systems focusing on Global Logistics

By emerging modern technologies and novel concepts in recent decade a revolution has been introduced, known as Industry 4.0 in modern manufacturing systems. In this revolution, cloud manufacturing has a critical role as a major pillar. The idea behind the cloud manufacturing concept is establishing a cloud manufacturing platform, which aggregates distributed manufacturing resources, then transforms them into manufacturing services, and manages them in a centralized manner. One of the critical aspects of this centralized management is scheduling of the tasks. The scheduling problem of single/multiple tasks is previously considered in cloud computing transactions, but the structure of this problem is different in cloud manufacturing, regarding logistic aspects. In this paper, a brief review over the prior researches related to the task scheduling in cloud computing and cloud manufacturing is presented. This model is capable of addressing to main types of sharing in cloud manufacturing systems known as operation sharing and logistic sharing. Next, the paper presents a basic model for task scheduling problem in cloud manufacturing systems; and by using an illustrative example the validation and verification of the proposed model are examined. Finally, the paper discusses the results, concludes the remarks and presents the roadmap of the future researches.

Real-Time Monitoring System to Lean Manufacturing

Future of the manufacturing industry is the combination of lean and cloud manufacturing which is a promising paradigm for next-generation manufacturing system. Lean practice is one of the best methods used by the manufactures around the world to enhance their competitiveness. It is believed that lean practice will result in reducing waste and control the essential processes related to the production. Even though lean manufacturing system is very reliable and trustworthy concept in large scale industries but still there are some flaws and challenges faced by SMEs industries to make it run successfully. To overcome these challenges and problems, we will rely on the cloud manufacturing concept while applying lean manufacturing methodology. Cloud platform will have a potential to collect the real-time production monitoring and will have a very close look at the inventory stock so that next order for raw material could be placed whenever it is required. With the combination of lean and cloud manufacturing, the new approach will provide us with a very flexible approach towards the production and will keep monitoring the scheduling the dispatching of the finished product as per the market requirement. In this paper, discuss a case study based on the cloud manufacturing and lean manufacturing system together to see how it will benefit and can be used to enhance productively in SMEs industry. With this combination of cloud and lean manufacturing and with the help of electronics system in it a partial automation system was established.

An Overview of Cloud Implementation in the Manufacturing Process Life Cycle

The advancement of information and communication technology (ICT) has changed the structure and functions of various sectors and it has also started to play a significant role in modern manufacturing in terms of computerized machining and cloud manufacturing. It is important for industries to keep up with the current trend of ICT for them to be able survive and be competitive. Cloud manufacturing is an approach that wanted to realize a real-world manufacturing processes that will apply the basic concept from the field of Cloud computing to the manufacturing domain called Cloud-based manufacturing (CBM) or cloud manufacturing (CM). Cloud manufacturing has been recognized as a new paradigm for manufacturing businesses. In cloud manufacturing, manufacturing companies need to support flexible and scalable business processes in the shop floor as well as the software itself. This paper provides an insight or overview on the implementation of cloud manufacturing in the modern manufacturing processes and at the same times analyses the requirements needed regarding process enactment for Cloud manufacturing and at the same time proposing a STEP-NC concept that can function as a tool to support the cloud manufacturing concept.

Cloud manufacturing based service encapsulation and optimal configuration method for injection molding machine

This paper aims to introduce the concept of cloud manufacturing (CMfg) in the injection molding industry. The CMfg platform for injection molding enterprises is built to improve the sharing, circulation and integration of the injection molding resources. With the implementation of the Internet of Things technologies in the traditional injection molding shop, the real-time manufacturing information of resources can be accurately captured and the entire molding process becomes more visible and traceable. The virtual machining service of the injection molding machine is encapsulated as a cloud service that published into the platform for on-demand use. When task orders are published, through the presented task-driven proactive service discovery method, competent services can be quickly found. The custom-oriented evaluation method based on technique for order preference by similarity to ideal solution is designed to help the demanders to find satisfying services according to their customized criteria. Since the task orders arrive dynamically, after these orders are assigned to the specified machine, a real-time order dispatching mechanism is developed to provide an optimal scheduling plan for the cloud service. Finally, the proposed framework and methods are illustrated by a numerical simulation.

Taxonomy and uncertainties of cloud manufacturing

The manufacturing industry is currently undergoing rapid changes because of the rapid growth of advanced technologies in information systems and networks, which allow for collaboration around the world. This combination of the latest information technologies and advanced manufacturing networks has led to the growth of a new manufacturing model known as cloud manufacturing. Because cloud manufacturing is considered an emerging research area, there are significant gaps in the literature regarding the concept of cloud manufacturing, its implementation, and in particular the uncertainties coming with this new technology. This research aims to explain the concept of cloud manufacturing, its capabilities and potential. This work also introduces cloud manufacturing taxonomy, and investigates uncertainties that come with employing cloud manufacturing. Finally, proposals for future research in the context of cloud manufacturing are presented to address opportunities in cloud manufacturing.

Cloud Manufacturing: Current Trends and Future Implementations

Manufacturing technology changes with the needs of consumers. The globalization of the world economy has helped to create the concept of cloud manufacturing (CM). The purpose of this paper is to provide both an overview and an update on the status of CM and define the key technologies that are being developed to make CM a dependable configuration in today's manufacturing industry. Topics covered include: cloud computing (CC), the role of small and medium enterprises (SMEs), pay-as-you-go, resource virtualization, interoperability, security, equipment control, and the future outlook of the development of CM.

Current status and advancement of cyber-physical systems in manufacturing

This paper presents the current status and the latest advancement of cyber-physical systems (CPS) in manufacturing. In order to understand CPS and its future potential in manufacturing, definitions and characteristics of CPS are explained and compared with cloud manufacturing concept. Research and applications are outlined to highlight the latest advancement in the field. CPS shows great promise in factories of the future in the areas of future trends as identified at the end of this paper.

From Cloud manufacturing to Cloud remanufacturing: A Cloud-based approach for WEEE recovery

The modern manufacturing industry calls for a new generation of integration models that are more interoperable, intelligent, adaptable and distributed. Evolved from service-oriented architecture, web-based manufacturing and Cloud computing, a Cloud manufacturing model has been discussed worldwide which enables manufacturing enterprises to respond quickly and effectively to the changing global market. Especially for Waste Electrical and Electronic Equipment (WEEE), it is a critical necessity to reuse, remanufacture, recycle and recover it by re-shaping the lifecycle management patterns. In this paper, recent WEEE research works are briefly reviewed. Next, a novel service-oriented remanufacturing platform is introduced based on the Cloud manufacturing concept.

Cloud manufacturing: key characteristics and applications

Cloud manufacturing is emerging as a new manufacturing paradigm as well as an integrated technology, which is promising in transforming today’s manufacturing industry towards service-oriented, highly collaborative and innovative manufacturing in the future. In order to better understand cloud manufacturing, this paper provides a critical review of relevant concepts and ideas in cloud computing as well as advanced manufacturing technologies that contribute to the evolution of cloud manufacturing. The key characteristics of cloud manufacturing are also presented in order to clarify the cloud manufacturing concept. Furthermore, a four-process structure is proposed to describe the typical scenario in cloud manufacturing, hoping to provide a theoretical reference for practical applications. Finally, an application case of a private cloud manufacturing system for a conglomerate is presented.

Virtualise manufacturing capabilities in the cloud: requirements, architecture and implementation

In recent years, cloud manufacturing concept has been proposed by taking advantage of cloud computing to enhance the performance of manufacturing industry. Cloud manufacturing can be perceived as two types, i.e., manufacturing version of computing cloud, and a distributed environment that is networked around manufacturing cloud. This paper discusses manufacturing resources, abilities and relevant essentials from the service-oriented perspective. The functional requirements of a cloud manufacturing environment are also discussed, along with an interoperable manufacturing system framework. Cloud resource integration methods have been developed based on the function block and software agent technologies. It is possible to achieve a collaborative, intelligent, and distributed environment via cloud manufacturing technologies.

A cloud-based approach for WEEE remanufacturing

The modern manufacturing industry calls for a new generation of integration models that are more interoperable, intelligent, adaptable and distributed. Evolved from service-oriented architecture, web-based manufacturing and cloud computing, cloud manufacturing is considered worldwide a new enabling technology for manufacturing enterprises to respond quickly and effectively to the changing global market. For Waste Electrical and Electronic Equipment (WEEE) in particular, it is a critical necessity to recycle, reuse and remanufacture WEEE products by setting up a cloud-based information system. In this paper, a novel service-oriented remanufacturing platform is proposed based on the cloud manufacturing concept.

Cloud manufacturing: from concept to practice

The concept of cloud manufacturing is emerging as a new promising manufacturing paradigm, as well as a business model, which is reshaping the service-oriented, highly collaborative, knowledge-intensive and eco-efficient manufacturing industry. However, the basic concepts about cloud manufacturing are still in discussion. Both academia and industry will need to have a commonly accepted definition of cloud manufacturing, as well as further guidance and recommendations on how to develop and implement cloud manufacturing. In this paper, we review some of the research work and clarify some fundamental terminologies in this field. Further, we developed a cloud manufacturing systems which may serve as an application example. From a systematic and practical perspective, the key requirements of cloud manufacturing platforms are investigated, and then we propose a cloud manufacturing platform prototype, MfgCloud. Finally, a public cloud manufacturing system for small- and medium-sized enterprises (SME) is presented. This paper presents a new perspective for cloud manufacturing, as well as a cloud-to-ground solution. The integrated solution proposed in this paper, including the terminology, MfgCloud, and applications, can push forward this new paradigm from concept to practice.

Cloud Manufacturing Concept as a Tool of Multimodal Manufacturing Systems Integration

Abstract The following article deals with a novel approach to manufacturing in the context of the increasing demand for system and process integration. This integration chiefly applies to concrete facets of manufacturing tasks which must be taken into consideration in the stage of planning and preparation for complex production processes. Those facets are primarily exemplified by order types (such as production, service and cooperative commissions etc.), production models (e.g. discrete and process modeling), product categorization based on established criteria (e.g. production technology, complexity level, used materials and extras, weight, etc.) as well as many other aspects that hold great significance in the automatization of manufacturing processes. When more advanced orders are to be realized, one of the main challenges posed by this situation is the need to accomplish multiple operations which due to their different nature, scope and scale (e.g. varied processing types: heat and plastic treating, machining etc.) have to be conducted by different contractors. In order to address those key problems and reduce the negative impact of multimodality, the author proposes a manufacturing cloud (also known as cloud manufacturing) which is a variant of a groundbreaking, yet well-established concept - cloud computing. This paper presents the chief notions of this method created specifically with integrated multimodal systems and production processes. The author also highlights key problems that should be addressed before this solution can be used in practice.

Research of Distributed Software Resource Sharing in Cloud Manufacturing System

The concept of cloud manufacturing is introduced and the importance of software resource sharing is elaborated. In cloud manufacturing system, server-based architecture is the best solution to provide solutions to address the application of the software resource requirements for small and medium enterprises(SMEs) . And the virtualization technology which have developed and mature will provide a strong technical support for it. The system through deploy Citrix's XenApp application servers to achieve application virtualization. On this basis, the distributed software resource sharing platform which mainly for small and medium company had being developed.

Cloud Manufacturing

The concept of cloud manufacturing (CMfg) is discussed, as well as its core enabling technologies. A seven-phases running mode for CMfg was proposed, and the related inputs, enabling technologies and tools, knowledge and algorithm repositories, and intermediate products and results for each phase are described in detail. Two kinds of CMfg service platforms, i.e., private and public CMfg service platforms are analyzed.