A Knowledge-Based Approach for Business Process Reengineering, SHAMASH

In this paper we present an initial overview of shamash, a process modeling tool for Business Process Reengineering. The main features that differentiate it from most current related tools are its ability to define and use organisation standards, and functional structure, and make automatic model simulation and optimisation of them. shamash is a knowledge based system, and we include a discussion on how knowledge acquisition did take place. Furthemore, we introduce a high level description of the architecture, the conceptual model, and other important modules of the system.Publicad

Shamash: an AI tool for modelling and optimizing business processes

Proceeding of: IEEE 13th International Conference on Tools for Artificial Intelligence, 7-9 Nov. 2001 DallasIn this paper we describe SHAMASH, a tool for modeling and automatically optimizing Business Processes. The main features that differentiate it from most current related tools are its ability to define and use organisation standards, and functional structure, and make automatic model simulations and optimisation of them. SHAMASH is a knowledge based system, and we include a discussion on how knowledge acquisition takes place. Furthermore, we introduce a high level description of the architecture, the conceptual model, and other important modules of the system.Publicad

Integrating planning and scheduling in workflow domains

One of the main obstacles in applying AI planning techniques to real problems is the difficulty to model the domains. Usually, this requires that people that have developed the planning system carry out the modeling phase since the representation depends very much on a deep knowledge of the internal working of the planning tools. On some domains such as business process reengineering (BPR), there has already been work on the definition of languages that allow non-experts entering knowledge on processes into the tools. We propose here the use of one of such BPR languages to enter knowledge on the organisation processes to be used by planning tools. Then, planning tools can be used to semi-automatically generate business process models. As instances of this domain, we will use the workflow modeling tool SHAMASH, where we have exploded its object oriented structure to introduce the knowledge through its user-friendly interface and, using a translator transform it into predicate logic terms. After this conversion, real models can be automatically generated using a planner that integrates planning and scheduling, IPSS. We present results in a real workflow domain, the telephone installation (TI) domain.The SHAMASH project has being carried out in the course of the R&D project funded by the Esprit Program of the Commission of the European Communities as project number 25491. A complementary grant was given by the Spanish research commission, CICYT, under project number TIC98-1847-CE. We thank the partners of this project, who have originated and contributed to the ideas reported: UF (Unio´n Fenosa), SAGE (Software AG Espan˜ a), SEMA GROUP sae, UC3M (Universidad Carlos III de Madrid), WIP (Wirstchaft und infrastruktur & Co Planungs KG), and EDP (Electricidade de Portugal). We would specially like to thank all the UC3M team, the PLANET people and Paul Kearney (BT). Through talks with him we have outlined many ideas. This work has also been partially funded by grant MCyT TIC2002-04146-C05-05 and the UAH project PI2005/084.Publicad

A planning approach to the automated synthesis of template-based process models

The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment

Planeamento inteligente em gestão de projetos

The decision to opt for a dissertation in the area of Project Management, emerged from the desire to develop my knowledge in this area, gaining fundamental tools that will no doubt be an asset to my career. The aim of this thesis is to present both the research carried out on the use of artificial intelligence in planning and scheduling for project management, as well as to report the experience lived during the internship. The opportunity to undertake an internship, at the same time as I worked on my thesis, emerged from an interview performed with the goal of acquiring some advice and suggestions from an experienced professional in the position of project manager and it allowed me to increase my practical knowledge in the area. Since the internship I undertook is inserted in the project management area, it allowed me to put into practice some of the skills acquired during the research for the thesis. This thesis starts with the report of my internship, since it can be viewed as an introduction to project management and only afterwards do I present the results of the investigation I conducted on Artificial Intelligence Planning and Scheduling. I started by documenting the important concepts and definitions, followed by the results of my research completed with examples of existing systems. To conclude spoke of the projects for which I contributed during my internship and I finished with the results of my work during the internship attached in the end of the document.A decisão de optar por uma dissertação na área de Gestão de Projetos, surgiu da vontade de aprofundar o meu conhecimento nessa área, ganhando mais ferramentas que serão sem dúvida uma mais-valia para a minha carreira profissional. A minha tese pretende apresentar tanto a investigação desenvolvida sobre o uso de inteligência artificial em planeamento e scheduling para gestão de projetos, assim como relatar a experiência vivida durante a realização do estágio. A oportunidade de realizar um estágio ao mesmo tempo que trabalhava na minha tese, surgiu de uma entrevista realizada com o intuito de obter a opinião de um profissional experiente no cargo de gestor de projetos e permitiu-me aprofundar o meu conhecimento prático na área. Uma vez que o estágio que realizei está inserido na área de gestão de projetos, este, permitiu-me por em prática algumas das competências adquiridas durante a investigação para a tese. A dissertação inicia-se pelo relato do estágio que realizei, uma vez que este pode ser visto como uma introdução ao tema de gestão de projetos. Seguem-se os resultados da investigação que realizei no tema de Planeamento e Scheduling de Inteligência Artificial, completo com alguns exemplos de sistemas já existentes. Para concluir falo dos projetos e das tarefas com as quais contribui durante o estágio e anexei no final do documento, alguns exemplos das tarefas que realizei

SmartPM: automatic adaptation of dynamic processes at run-time

The research activity outlined in this thesis is devoted to define a general approach, a concrete architecture and a prototype Process Management System (PMS) for the automated adaptation of dynamic processes at run-time, on the basis of a declarative specification of process tasks and relying on well-established reasoning about actions and planning techniques. The purpose is to demonstrate that the combination of procedural and imperative models with declarative elements, along with the exploitation of techniques from the field of artificial intelligence (AI), such as Situation Calculus, IndiGolog and automated planning, can increase the ability of existing PMSs of supporting dynamic processes. To this end, a prototype PMS named SmartPM, which is specifically tailored for supporting collaborative work of process participants during pervasive scenarios, has been developed. The adaptation mechanism deployed on SmartPM is based on execution monitoring for detecting failures at run-time, which does not require the definition of the adaptation strategy in the process itself (as most of the current approaches do), and on automatic planning techniques for the synthesis of the recovery procedure