Antonio Di Leva

Organization and information system design of manufacturing environments: the new M∗ approach

Abstract Development of CIM systems requires models for enterprise and information system modelling and analysis, and tools and methods for database design. M ∗ methodology addresses these issues. In the paper, the new integrated high-level model of M ∗ , based on high-level Petri-nets, for modelling engineering and manufacturing information systems is introduced. It allows description of an organization at two different levels (organization and conceptual) and, most importantly, description of, in an integrated way, both the organization behaviour and the manipulation actions on the database which support the information system activies. Moreover, the conceptual specification is executable.

The BP-M* Methodology for Process Analysis in the Health Sector

In this paper we present the main phases of the BP-M* methodology and its application to a care pathway for patients in the Oncology Division of a large hospital, to evaluate pros and cons of different drug administration modalities and the impact of these modalities to the organizational process. BP-M* has been developed for the manufacturing sector but the relevance of business modeling, analysis and reorganization is not restricted to a specific sector. The aim of this work is to show its application to a real life study of a complex process in the health sector.

The M*-COMPLEX Approach to Enterprise Modeling, Engineering, and Integration

A hot topic on the agenda of corporate management in order to improve the enterprise competitiveness factors concerns the operational, even continuos and rapid, transformation of business processes, support interoperability and integration with other business partners. The paper overviews through a simple case study concerning the definition of a virtual enterprise, the methodology M*-COMPLEX (extending authors previous word on M*-OBJECT) for design of process centered highly complex systems and its supporting tool M*-PROCESS.

Rule management for heterogeneous knowledge-based systems

The work described in this paper concerns the management of rules coming from a variety of knowledge sources and shared by several expert systems. In the ESPRIT Project ESTEAM-316 an architecture has been defined for integrating cooperating agents. A significant help to the designer of an expert system, made by several cooperating agents, is given by a set of predefined agents for Data and Knowledge Base Management (for short KAgents). One kind of K-Agent, to which the present paper is devoted, is the Rule Ba~e Management System (RBMS) which handles all accesses to a Rule Base (RB) stored on secondary memory. The RBMS has a layered structure, in which three main levels can be identified (external, logical and physical). The ezternal level is the one concerned with the way in which the rule base is viewed by the agents. The logical level provides a high level interface built on top of an access method system, the physical level. Since each RB is described by the same schema the RBMS does not have the generality of a DBMS, but it is a specific application system suited to manage large rule bases.

A Simulation-driven Approach in Risk-aware Business Process Management: A Case Study in Healthcare.

Risk management in business process is a key factor of success for organization as risks are part of every business activity. Errors may bring to increased costs, loss of quality as well as time delays, which in healthcare can bring to serious damages. This paper proposes a methodological framework to investigate risks in organizations by adopting a Business Process Management perspective that includes modeling and simulation of business processes. We applied our methodology to processes in the Blood Bank department of a large hospital. Our results show that a simulation-driven approach is an effective way to intercept and estimate real risks and to provide a decision support to guide the of department’s managers.

An Agent-Based Model of a Business Process: The Use Case of a Hospital Emergency Department

An application of Artificial Intelligence is computational simulation which reproduces the behavior of a system, such as an organization. Simulations provide benefits into business process management, also by combining scenarios and what-if analysis. This study explores the adoption of agent-based modeling technique, in addition to traditional discrete event simulations. The focus is on a real case study of an hospital emergency department. Following the construction of a new hospital, managers are interested in simulating the actual flows in the new configuration before the moving. In our model, patients and operators are agents, acting due to simple behavioral rules in the environment. The different activities are placed on the map of the department, to provide immediate understanding of bottlenecks and queues. While first results were validated from managers, next steps include the comparison of resulting flows between the new and the old department. Logistics analysis includes the time for moving agents between different wards.

Process analysis and reengineering in the health sector

In this paper we present the application of a methodology for business process analysis and reengineering to a care pathway for patients of an Oncology Hospital. This process has been analyzed to evaluate different drug administration modalities and the impact of these modalities to the organizational process.