A model for business process automation in service oriented systems with knowledge management technologies

Ana Šaša (2009) A model for business process automation in service oriented systems with knowledge management technologies. PhD thesis.

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Abstract

Due to increasing requirements for efficiency, effectiveness and flexibility of business systems, automation of business processes has become an important topic. In the last years, the most successful and predominant approach to business process automation has become the service-oriented architecture approach. In a service-oriented architecture a business process is composed of services, which represent different tasks that have to be performed in a business system. Typically, a business process is implemented with one of the business process execution languages. Among them the prevalent language has become WS-BPEL (Web Services Business Process Execution Language). Business process execution systems perform orchestration of different services. Services can represent automated tasks or enable integration of human-performed tasks (human tasks). Integration of human tasks into business process execution is covered by a pair of specifications: BPEL4People and WS-HumanTask. The topic of this doctoral dissertation is to enable a higher degree of automation of business processes in service-oriented systems. We focus on human tasks, because they represent those tasks of a business process, which are not automated. We define an architectural model supported by innovative methods, which extend the possibilities of automation of human tasks. Every architectural component is responsible for automation of a certain part of a human task. In cases where automation is not enabled by the proposed model, the human task is delegated to the responsible person. For implementation of the model the dissertation also defines an extension to the WS-HumanTask specifications. The extension allows backward compatibility with the existing specifications. The model is based on observation that business process and human task execution can be seen as an opportunity to capture the knowledge based on which the execution is performed, and to capture the knowledge which is created during the execution. The goal is to enable direct reuse of the knowledge and possible automation for succeeding human task executions. In order to enable this, we define a decision making method, which is based on multi-criteria decision making and develops a decision model in an OWL ontology. The model enables the use of this method in human task execution as part of business process execution. With this it enables a higher level of automation of human tasks, which are based on decisions. The model also enables a higher level of automation of human tasks, which require collaboration between different human actors. The dissertation defines an innovative approach to defining business collaboration protocols, which are the basis for collaboration between agents in a multi-agent system, which represent the human actors. The approach enables separation of protocol definition and implementation and, with this, loose coupling of protocols and implementation. This means that changes in a collaboration protocol do not require changes in the implementation of the multi-agent system or the implementation of the behaviour of the agents, which use the protocols in their acts. As decision making and collaboration are among the most important activities of employees in business systems, the model improves a significant part of human tasks. It represents an important step closer to the vision of end-to-end business process automation. It heightens the degree of automation of human tasks and consequently enables more efficient business process execution. Another important advantage is a higher level of decision traceability. By this, the doctoral dissertation represents an integral solution to improving efficiency of human tasks within the business process context in service-oriented systems and defines a set of new and innovative methods, which are based on ontologies and multi-agent systems. Their common goal is automation of human tasks and, by this, enabling a higher degree of automation of business processes.

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