A collaboration mechanism for service-oriented manufacturing processes with uncertain duration: a perspective of efficiency

2022 ◽  
pp. 1-18
Author(s):  
Minglun Ren ◽  
Liangjia Shao
Keyword(s):  
Manufacturing Processes ◽  
Uncertain Duration ◽  
Service Oriented

scholarly journals Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing ‡

2018 ◽  
Author(s):  
Luca Mazzola ◽  
Philipp Waibel ◽  
Patrick Kaphanke ◽  
Matthias Klusch
Keyword(s):  
Business Process ◽  
Process Analysis ◽  
Building Blocks ◽  
Process Models ◽  
Just In Time ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Time Service ◽  
Business Process Models ◽  
Service Oriented

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we~propose a novel pragmatic approach for the process analysis, implementation and execution. This~is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual available services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Service (QoS)-based Constraint Optimization Problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by means of the introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources and dynamic replanning in the case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models' implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach and the technical architecture and depicts one initial industrial application in the manufacturing domain of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

scholarly journals A Smart Cloud-Based System for the WEEE Recovery/Recycling

2014 ◽  
Author(s):  
Xi Vincent Wang ◽  
Brenda N. Lopez N. ◽  
Lihui Wang ◽  
Jinhui Li ◽  
Winifred Ijomah
Keyword(s):  
Manufacturing Systems ◽  
Service Oriented Architecture ◽  
Intelligent System ◽  
Hazardous Materials ◽  
Cloud Manufacturing ◽  
Data Management System ◽  
Manufacturing Processes ◽  
Component Level ◽  
Recovery System ◽  
Service Oriented

Waste Electrical and Electronic Equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus it is necessary to develop a distributed and intelligent system to support WEEE recovery and recycling. In recent years, the Cloud concept has gained increasing popularity since it provides a service-oriented architecture that integrates various resources over the network. Cloud Manufacturing systems are proposed world-wide to support operational manufacturing processes. In this research, Cloud Manufacturing is further extended to the WEEE recovery and recycling context. A Cloud-based WEEE Recovery system is developed to provide modularized recovery services on the Cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also proposed with the help of the Quick Respond code method.

scholarly journals Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing

2018 ◽  
Author(s):  
Luca Mazzola ◽  
Philipp Waibel ◽  
Patrick Kaphanke ◽  
Matthias Klusch
Keyword(s):  
Business Process ◽  
Process Analysis ◽  
Building Blocks ◽  
Process Models ◽  
Just In Time ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Time Service ◽  
Business Process Models ◽  
Service Oriented

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we propose a novel pragmatic approach for the process analysis, implementation and execution. This is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual avaialble services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Services (QoS) based constraint optimization problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by the means of introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources, and dynamic replanning in case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach, the technical architecture and depicts one initial industrial application in the manufacturing domains of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

Cloud Manufacturing

2018 ◽  
Vol 8 (2) ◽  
pp. 39
Author(s):  
Matthew Sadiku ◽  
Yonghui Wang ◽  
Suxia Cui ◽  
Sarhan Musa
Keyword(s):  
Cloud Computing ◽  
Manufacturing Industry ◽  
Cloud Manufacturing ◽  
Manufacturing Processes ◽  
Web Based ◽  
Collaborative Manufacturing ◽  
On Demand ◽  
The Future ◽  
Service Oriented ◽  
Basic Concepts

Cloud manufacturing is emerging as a new manufacturing paradigm which applies well-known basic concepts from cloud computing to manufacturing processes and deliver shared, ubiquitous, on-demand manufacturing services. It  is an innovative, web-based manufacturing model. It is promising to transform today’s manufacturing industry from production-oriented to service-oriented, highly collaborative manufacturing of the future. This paper provides a brief introduction to cloud manufacturing.

scholarly journals Smart Process Optimization and Adaptive Execution with Semantic Services in Cloud Manufacturing ‡

Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 279 ◽  
Author(s):  
Luca Mazzola ◽  
Philipp Waibel ◽  
Patrick Kaphanke ◽  
Matthias Klusch
Keyword(s):  
Business Process ◽  
Process Analysis ◽  
Building Blocks ◽  
Process Models ◽  
Just In Time ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Time Service ◽  
Business Process Models ◽  
Service Oriented

A new requirement for the manufacturing companies in Industry 4.0 is to be flexible with respect to changes in demands, requiring them to react rapidly and efficiently on the production capacities. Together with the trend to use Service-Oriented Architectures (SOA), this requirement induces a need for agile collaboration among supply chain partners, but also between different divisions or branches of the same company. In order to address this collaboration challenge, we propose a novel pragmatic approach for the process analysis, implementation and execution. This is achieved through sets of semantic annotations of business process models encoded into BPMN 2.0 extensions. Building blocks for such manufacturing processes are the individual available services, which are also semantically annotated according to the Everything-as-a-Service (XaaS) principles and stored into a common marketplace. The optimization of such manufacturing processes combines pattern-based semantic composition of services with their non-functional aspects. This is achieved by means of Quality-of-Service (QoS)-based Constraint Optimization Problem (COP) solving, resulting in an automatic implementation of service-based manufacturing processes. The produced solution is mapped back to the BPMN 2.0 standard formalism by means of the introduced extension elements, fully detailing the enactable optimal process service plan produced. This approach allows enacting a process instance, using just-in-time service leasing, allocation of resources and dynamic replanning in the case of failures. This proposition provides the best compromise between external visibility, control and flexibility. In this way, it provides an optimal approach for business process models’ implementation, with a full service-oriented taste, by implementing user-defined QoS metrics, just-in-time execution and basic dynamic repairing capabilities. This paper presents the described approach and the technical architecture and depicts one initial industrial application in the manufacturing domain of aluminum forging for bicycle hull body forming, where the advantages stemming from the main capabilities of this approach are sketched.

Modeling extended manufacturing processes with service-oriented entities

2008 ◽  
Vol 3 (1) ◽  
pp. 31-50 ◽  
Author(s):  
Rubén Darío Franco ◽  
Ángel Ortiz Bas ◽  
Francisco Lario Esteban
Keyword(s):  
Manufacturing Processes ◽  
Service Oriented

scholarly journals Sustainability Benefits Analysis of Cyber-Manufacturing Systems

2020 ◽  
Author(s):  
Zhengyi Song ◽  
Young Moon
Keyword(s):  
Manufacturing Systems ◽  
Sustainability Assessment ◽  
The Internet ◽  
Manufacturing Processes ◽  
Self Monitoring ◽  
Narrow Scope ◽  
System Service ◽  
Assessment Approach ◽  
Service Oriented ◽  
Factory Of The Future

Abstract Cyber-Manufacturing System (CMS) is a vision for the factory of the future, where manufacturing processes and physical components are seamlessly integrated with computational processes to provide agile, adaptive, and scalable manufacturing services. Functional elements of CMS are digitized, registered, and shared with users and stakeholders through various computer networks and the Internet. CMS incorporates recent advances in the Internet of Things, Cloud Computing, Cyber-Physical System, Service-Oriented Technologies, Modeling and Simulation, Sensor Networks, Machine Learning, Data Analytics, and Advanced Manufacturing Processes. CMS possesses intelligence such as self-monitoring, self-adjustment, self-prediction, self-allocation, self-configuration, self-scalability, self-remediating, and self-reusing. Such intelligent capabilities enable CMS to contribute to manufacturing sustainability. However, prior studies are limited in addressing a narrow scope of CMS or in covering only a subset of sustainability dimensions. This paper addresses the research gap by developing a holistic CMS infrastructure and adopting a Distance-to-Target based sustainability assessment approach to measure the sustainability benefits of CMS. To illustrate how the infrastructure and metrics are used to analyze the sustainability benefits of CMS, an example case is presented. The results show that CMS can deliver substantial sustainability benefits through increased productivity, profitability & energy efficiencies, and reduction of working-in-process (WIP) inventory levels & logistics costs.

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