@conference {148,
	title = {A BPMN extension for modeling Cyber-Physical-Production-Systems in the context of Industry 4.0},
	booktitle = {Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017},
	year = {2017},
	publisher = {Institute of Electrical and Electronics Engineers Inc.},
	organization = {Institute of Electrical and Electronics Engineers Inc.},
	abstract = {<p>Industry 4.0 denotes a recent trend that aims at exploiting Cyber Physical Systems (CPS), based on IoT (Internet of Things) and cloud computing technologies, to obtain increased degrees of cooperation and communication in production systems, thus leading to what is referred to as Cyber Physical Production Systems (CPPS) or {\textquoteright}Smart Factories{\textquoteright}. {\textcopyright} 2017 IEEE.</p>},
	keywords = {Administrative data processing, BPMN, Business process management, Cloud computing technologies, CPPS, Cyber Physical System, Cyber physicals, Cyber-physical systems (CPS), Distributed computer systems, Embedded systems, Enterprise resource management, Industrial plants, Internet of things, Production system, Resources management},
	isbn = {9781509044283},
	doi = {10.1109/ICNSC.2017.8000159},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028506510\&doi=10.1109\%2fICNSC.2017.8000159\&partnerID=40\&md5=21f941fe91fbcb4bc02afe439cad2075},
	author = {Bocciarelli, P. and D{\textquoteright}Ambrogio, A. and Giglio, A. and Paglia, E.},
	editor = {Guerrieri A., Fortino G., Vasilakos A.V., Zhou M., Lukszo Z., Palau C., Liotta A., Vinci A., Basile F., Fanti M.P.}
}
@conference {Bocciarelli2014278,
	title = {Empowering business process simulation through automated model transformations},
	booktitle = {Simulation Series},
	volume = {46},
	number = {4},
	year = {2014},
	note = {cited By 2},
	pages = {278-286},
	publisher = {The Society for Modeling and Simulation International},
	organization = {The Society for Modeling and Simulation International},
	abstract = {Simulation is one of the most relevant techniques that can be used in the business process management domain to effectively enact a continuous enhancement of business processes (BPs). However, the effectiveness of BP simulation is still limited for several reasons (e.g., lack of simulation know-how of BP analysts, simulation model parameters hard to determine, semantic gap between the business process model and the simulation model). To overcome these limitations, this paper proposes a model-driven method that introduces a set of model transformations to automate the generation of executable simulation code of a BP from its abstract definition in BPMN, the standard language for specifying business processes. The simulation code is specified in eBPMN, a Java-based domain-specific language that has been designed and implemented according to the BPMN execution semantics.},
	keywords = {Administrative data processing, BPM, BPMN, Computer simulation, Computer simulation languages, EBPMN, Enterprise resource management, Mathematical models, MDA, Model transformation, Problem oriented languages, Semantics, Software architecture, Technology transfer},
	isbn = {9781632662156},
	issn = {07359276},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901985241\&partnerID=40\&md5=ebb5d7bb28209e8901e06a4b70f40735},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio and Giglio, A. and Paglia, E. and Gianni, D.}
}
@article {Bocciarelli2014573,
	title = {A model-driven method for enacting the design-time QoS analysis of business processes},
	journal = {Software and Systems Modeling},
	volume = {13},
	number = {2},
	year = {2014},
	note = {cited By 6},
	pages = {573-598},
	publisher = {Springer Verlag},
	abstract = {<p>Business Process Management (BPM) is a holistic approach for describing, analyzing, executing, managing, and improving large enterprise business processes. A business process can be seen as a flow of tasks that are orchestrated to accomplish well-defined goals such as goods production or services delivery. From an IT perspective, BPM is closely related to a business process automation approach carried out by use of IT standards and technologies, such as service-oriented architectures (SOAs) and Web Services. This paper specifically focuses on fully automated business processes that are defined and executed as orchestrations of software services. In a BPM context, the ability to predict at design time the business process behavior assumes a strategic relevance, both to early assess whether or not the business goals are achieved and to gain a competitive advantage. A business process is typically specified by use of Business Process Modeling Notation (BPMN), the standard language for the high-level description of business processes. Unfortunately, BPMN does not support the characterization of the business process in terms of nonfunctional or QoS properties, such as performance and reliability. To overcome such a limitation, this paper introduces Performability-enabled BPMN (PyBPMN), a lightweight BPMN extension for the specification of performance and reliability properties. PyBPMN enables the design time prediction of the business processes behavior, in terms of performance and reliability properties. Such prediction activity requires the use of models that are to be first built and then evaluated. In this respect, this work introduces a model-driven method that exploits PyBPMN to predict, at design time, the performance and the reliability of a business process, either to select the process configuration that provides the best behavior or to check if a given configuration satisfies the overall requirements. The proposed model-driven method that enacts the automated analysis of a business process behavior embraces the complete business process development cycle, from the specification phase down to the implementation phase. The paper also describes how the proposed model-driven method is implemented. The several model transformations at the core of the method have been implemented by use of QVT, and the standard language for specifying model transformations provided by OMG{\textquoteright}s MDA. The availability of such automated model transformations allows business analysts to predict the process behavior with no extra effort and without being required to own specific skills of performance or reliability theory, as shown by use of an example application. {\textcopyright} 2013 Springer-Verlag Berlin Heidelberg.</p>},
	keywords = {Administrative data processing, Automation, Availability, BPMN, Business Process, Competition, Design, Enterprise resource management, Forecasting, High level languages, Information services, LQN, Mathematical models, MDA, Performance, Quality of service, Reliability, Service oriented architecture (SOA), Software architecture, Specifications, Web services},
	issn = {16191366},
	doi = {10.1007/s10270-013-0345-5},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899754418\&partnerID=40\&md5=ac7ae348f9d39ccb87a9aedb7d7524bd},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio}
}
@conference {Bocciarelli2011160,
	title = {A BPMN extension for modeling non functional properties of business processes},
	booktitle = {Simulation Series},
	volume = {43},
	number = {1 BOOK 4},
	year = {2011},
	note = {cited By 27},
	pages = {160-168},
	abstract = {Business Process Management (BPM) is an holistic approach for describing, analyzing, executing, managing and improving large enterprise business processes, which can be seen as collections of related tasks executed to accomplish well-defined goals. This paper introduces a notation for the description of a business process in terms of both functional and non-functional properties, specifically addressing the performance and reliability characterization of a business process. In the BPM context, the Business Process Modeling Notation (BPMN) is the de-facto standard for the high-level description of business processes. Unfortunately BPMN does not support the characterization of the business process in terms of non-functional properties such as performance and reliability. To overcome such limitation, this paper introduces PyBPMN (Performability-enabled BPMN), a lightweight BPMN extension for the specification of properties that address both performance and reliability. The proposed extension is based on an approach that exploits principles and standards introduced by the Model Driven Architecture (MDA), thus obtaining significant advantages in terms of easy customization and improved automation. The paper also presents an example application of the proposed extension to show how it enables the automated transformation of a business process model into a parameterized performance model whose execution gives insights about the process behavior.},
	keywords = {Administrative data processing, BPMN, Business Process, Business process management, Business process model, Business Process Modeling Notation (BPMN), Computer simulation, Enterprise resource management, MDA, Model driven architectures, Performance and reliabilities, Reliability, Software architecture, Systems engineering},
	isbn = {9781617828386},
	issn = {07359276},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887029950\&partnerID=40\&md5=286bf26106c501019949590c37d312e2},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio}
}
