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

被引:16
|
作者
Mazzola, Luca [1 ,5 ]
Waibel, Philipp [2 ]
Kaphanke, Patrick [3 ]
Klusch, Matthias [4 ]
机构
[1] HSLU Lucerne Univ Appl Sci, Sch Informat Technol Informat, CH-6343 Rotkreuz, Switzerland
[2] TU Wien, Distributed Syst Grp, A-1040 Vienna, Austria
[3] EVANA AG, D-60325 Frankfurt, Germany
[4] DFKI German Res Ctr Artificial Intelligence, Saarland Informat Campus D3-2, D-66123 Saarbrucken, Germany
[5] DFKI German Res Ctr Artificial Intelligence, Kaiserslautern, Germany
来源
INFORMATION | 2018年 / 9卷 / 11期
基金
欧盟地平线“2020”;
关键词
Industry; 4.0; XaaS; SemSOA; business process optimization; scalable cloud service deployment; process service plan just-in-time adaptation; BPMN partial fault tolerance;
D O I
10.3390/info9110279
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:28
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