JIMÉNEZ RAMÍREZ , Andrés

Automating business processes is one of the most recurrent topics in indus tries, independent of its digital orientation. Competitiveness pushes companies to deliver their products or services efficiently and effectively. Besides providing the appropriate value, they are required to do it faster and with higher quality. This agile context leads...

La calidad de los modelos de los procesos de negocio (es decir, artefactos software que capturan las relaciones entre las unidades organizacionales de un negocio) es esencial para la mejora de la gestión de los procesos de negocio. Sin embargo, dicho modelado se hace normalmente a mano. Esa tarea puede representar un gran reto para el analista...

Nowadays, Machine Learning (ML) algorithms are being widely applied in virtually all possible scenarios. However, developing a ML project entails the effort of many ML experts who have to select and configure the appropriate algorithm to process the data to learn from, between other things. Since there exist thousands of algorithms, it becomes...

La Automatización Robótica de Procesos (RPA) ha ganado especial atención en los últimos años tanto en la industria como en la academia. RPA surge como una forma de automatizar tareas humanas mundanas y repetitivas. En comparación con la automatización tradicional, RPA requiere un menor nivel de intrusión en la infraestructura informática. Una...

The Robotic Process Automation (RPA) paradigm has received increasing attention in recent years. It enables task automation by software components which interact with user interfaces in a similar way to that of humans. An RPA project follows a similar lifecycle as a software project. However, in certain contexts (e.g., business process...

There is an increasing interest in aligning information systems in a process-oriented way. As an alternative of the traditional imperative models which tend to be too rigid, processes may be specified in a declarative (e.g., constraint-based) way. Nonetheless, in general, offering operational support (e.g., generating possible execution...

Recent studies show that the success rate of Robotic Process Automation (RPA) projects is between 50 and 70%. In cases where they are not successful, most failures are caused by organizational factors, i.e., people and their social environment. People in the organization have a significant influence on the success of a RPA project. Likewise,...

Several reports indicate that the highest business priorities include: business improvement, security, and IT management. The importance of security and risk management is gaining that even government statements in some cases have imposed the inclusion of security and risk management within business management. Risk assessment has become an...

Business processes which require a high flexibility are com- monly specified in a declarative (e.g., constraint-based) way. In general, offering operational support (e.g., generating possible execution traces) to declarative business process models entails more complexity when compared to imperative modeling alternatives. Such support becomes...

The verification of the properties of a business process (BP) has become a significant research topic in recent years. In the early stages of development, the BP model (e.g. BPMN, EPC), the BP contract (task contract, regulations and laws, business rules), and the test objectives (requirements) are the only elements available. In order to...

Robotic process automation (RPA) is a technology that is presented as a universal tool that solves major problems of modern busi nesses. It aims to reduce costs, improve quality and create customer value. However, the business reality differs from this aspiration. After interviews with managers, we found that implementation of robots does not...

Robotic process automation (RPA) has received increasing attention in recent years. It enables task automation by software components, which interact with user interfaces in a similar way to that of humans. An RPA project life cycle is closely resembling a software project one. However, in certain contexts (e.g., business process outsourcing),...

Nowadays, Machine Learning (ML) algorithms are being widely applied in virtually all possible scenarios. However, developing a ML project entails the effort of many ML experts who have to select and configure the appropriate algorithm to process the data to learn from, between other things. Since there exist thousands of algorithms, it becomes...

In order to be able to flexibly adjust a company's business processes (BPs) there is an increasing interest in flexible process-aware information systems (PAISs). This increasing flexibility, however, typically implies decreased user guidance by the PAIS and thus poses significant challenges to its users. As a major contribution of this work,...

In this work, an automatic and intelligent system for integrated healthcare processes management is developed on a constraint based system. This project has been carried out in collaboration with a real assisted repro-duction clinic. Our goal is to improve the efficiency of the clinic by facilitating the management of the integrated healthcare...

Managing large collections of business process (BP) models is increasingly being necessary for organizations. For this, configurable BP models can be used for managing these BPs while allowing analysts to understand what these BPs share and what their differences are. Before the execution of the configurable BP model, a BP model has to be...

Unlike imperative models, the specifi cation of business process (BP) properties in a declarative way allows the user to specify what has to be done instead of having to specify how it has to be done, thereby facilitating the human work involved, avoiding failures, and obtaining a better optimization. Frequently, there are several enactment...

The aim of this study is to provide an extensive systematic literature review about the use of dynamic programming in the management of appointments in health centers, providing a view of the current research environment. Dynamic programming of appointments improves the efficiency through algorithmic decision support tools. This technology has...

Robotic Process Automation (RPA) provides a means to automate mundane and repetitive human tasks. Task Mining approaches can be used to discover the actions that humans take to carry out a particular task. A weakness of such approaches, however, is that they cannot deal well with humans who carry out the same task differently for different...

Business process (BP) models are usually defined manually by business analysts through imperative languages considering activity properties, constraints imposed on the relations between the activities as well as different performance objectives. Furthermore, allocating resources is an additional challenge since scheduling may significantly...

The manual specification of imperative business process (BP) models can be very complex and time-consuming, potentially leading to non-optimized models or even errors. To support process analysts in the definition of these models, a method for generating optimized configurable BP models from a constraint-based specification by considering...

Declarative business process (BP) models are increasingly used allowing their users to specify what has to be done instead of how. Due to their flexible nature, there are several enactment plans related to a specific declarative model, each one presenting specific values for different objective functions, e.g., completion time or profit. In...

The rise of robotic process automation (RPA) fuels areas like robotic process mining and task mining. Although traditional process mining research can exploit a range of resources (i.e., event logs) to test and benchmark new techniques, that is not the case for robotic process mining. Moreover, benchmark data for RPA needs to incorporate...

Context: The quality of business process models (i.e., software artifacts that capture the relations between the organizational units of a business) is essential for enhancing the management of business processes. However, such modeling is typically carried out manually. This is already challenging and time consuming when (1) input uncertainty...