Contextsensitive Online Adaption of Workflows

Innovations in Systems …, 2007

Workflow management systems usually interpret a workflow definition rigidly. However, there are real life situations where users should be allowed to deviate from the prescribed static workflow definition for various reasons, including lack of information, unavailability of the required resources and unanticipated situations. Furthermore, workflow complexity may grow exponentially if all possible combinations of anticipated scenarios must be compiled into the workflow definition. To flexibilize workflow execution and help reduce workflow complexity, this paper proposes a dual strategy that combines a library of predefined typical workflows with a planner mechanism capable of incrementally synthesizing new workflows, at execution time. This dual strategy is motivated by the difficulty of designing emergency plans, modeled as workflows, which account for reallife complex crisis or accident scenarios.

2010

The success of an enterprise heavily depends on its ability to respond to changes in its environment in an effective and dynamic way. To cope with emerging business trends, automatic workflow generation provides a significant competitive advantage .This paper presents a goal-driven workflow generation, which is pattern-oriented and knowledge-based. First, a process pattern is proposed as a vehicle for knowledge representation. Then, a heuristic intelligent planning algorithm is deployed to construct a workflow automatically according to the goal specified by the users and the business context.

Knowledge-Based Systems, 2002

There is a variety of applications that can benefit from the ability to find optimal or good solutions to a proposed problem automatically. The Artificial Intelligent (AI) community has been actively involved in efficient problem-solving in complex domains such as military or spacecraft problems with successful results. In this paper we describe the integration of AI planning techniques with an existing Workflow Management System. We show how these techniques can improve overall system functionality and can help to automate the definition of business processes. The work is based on a short study carried out at BT Research Laboratories as part of a larger programme that aims to provide technologies for a new generation of business support systems.

1999

Business environments have become exceedingly dynamic and competitive in recent times. Workflow technology is currently one of the most promising fields of research in business process automation. However, workflow systems to date do not provide the flexibility necessary to support the dynamic nature of business processes. In this paper we primarily present the issues and challenges related to managing workflows in dynamic environments, and provide feasibility considerations for the automation of this process. We also present an analysis of workflow modifications and potential solutions in this regard. Recent technological advancements have made it possible for organizations to automate their business processes extensively. Specialized information systems have emerged, which are tailored to specific functional divisions of organizations. At the same time, there have been giant leaps in connectivity, owing to advancement in communication infrastructure and protocols. Organizations now seek to achieve higher goals by consolidating their specialized, but distributed and often disconnected resources. The introduction of the workflow paradigm, after considerable maturity of information systems, database management, and networking infrastructure, was the next logical step in business process automation. A Workflow is defined as the automation of a business process, in whole or part, during which documents, information or tasks are passed from one participant to another for action, according to a set of procedural rules [WFM Coalition 1998]. Even though every business process will have some form of 'flow of work', there are of course, certain processes which are more suited for automation with workflow technology. Workflows have been classified in many ways. The trade press classifies workflows into three categories: Ad-hoc, Production, Administrative, on the basis or repetitiveness, predictability and functionality. classifies on the basis of processing entities: system-oriented and human oriented. ] adds a further category to the trade press classification: Collaborative, and divides the classes on the basis of mission criticality and workflow complexity. Another important property of business processes is Rigidity. The degree of rigidity dictates the nature of the process, from production, assembly line type of processes for which the work required is exactly known and set before the process starts, to strategic, mission critical processes where the work required cannot be predicted or fixed. Processes that fall in the middle may very well be the ones most likely to be chosen for and to benefit from automation through workflow technology. These processes are defined prior to execution, but also allow for some flexibility. They are characterized by the phrase "This is the way we do things around here" ]. Such processes may be of a similar nature, but can have different procedures in different organizations. However, due to the continually accelerating pace of technological advancements, changing requirements and regulations, and introduction of new methods, business processes are being constantly reviewed, improved and adapted to the changing environment. The stability of even those processes which, can be characterized as rigid, repetitive or predictable, is put in doubt. Organizations seeking to employ workflow technology have to be prepared for a large undertaking. Setting up (process mapping, workflow model definition, resource allocations, constraint specification) of even the simplest business processes through workflow technology would incur significant investment of time, effort and resources, successful deployment is yet another issue. One has to question the appropriateness of processes that are ready to be changed as soon as they are set up. Whether workflows in dynamic environments, would actually deliver the superior management and monitoring the management aspires for, or it would convert the process to an inflexible structure, engaging the workforce in managing the support tool? The first question to be asked is the suitability of the business process for automation by workflow technology. Assuming that organizations would endeavor to introduce workflows in dynamic environments, the next question is how best to capture the dynamism of the business process within the workflow model. One possible approach is to provide flexibility within the definition of the workflow, such that later modifications can be avoided as far as possible. These are slippery grounds since the distinction between ad-hoc and production workflows becomes fuzzy. If everything is kept flexible at build time, activity coordination and control at runtime cannot be satisfactorily provided. A workflow allowed to run freely, devoid of any control or constraints, will wipe out the very reason for which workflow technology was introduced. On the other hand, highly prescriptive models will impose a control that is too rigid for even the repetitive production workflows. Such inflexible structures can kill the individualism, dynamism and adaptability necessary for the organization to survive in a competitive environment. Finding the right balance between precise definition and flexible

Data & Knowledge Engineering, 2004

Current workflow management systems still lack support for dynamic and automatic workflow adaptations. However, this functionality is a major requirement for next-generation workflow systems to provide sufficient flexibility to cope with unexpected failure events. We present the concepts and implementation of AGENT GENTWO RK OR K, a workflow management system supporting automated workflow adaptations in a comprehensive way. A rule-based approach is followed to specify exceptions and necessary workflow adaptations. AGENT GEN TWOR K OR K uses temporal estimates to determine which remaining parts of running workflows are affected by an exception and is able to predictively perform suitable adaptations. This helps to ensure that necessary adaptations are performed in time with minimal user interaction which is especially valuable in complex applications such as for medical treatments. Ó 2004 Published by Elsevier B.V.

Proceedings of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2013

Dynamic adaptation is the customization of a business process to make it applicable to a particular situation at any time of its life cycle. Adapting requires experience, and involves knowledge about various, internal and external, aspects of business. Thus, we argue for the application of adaptation rules, considering the context of a particular process instance. Furthermore, we state that a context-based adaptation environment should go beyond, and learn from decisions, as well as continuously identify new unforeseen situations (context definitions). The aim of this paper is to present a computational engine that infers the need to update situations and adaptation rules, suggesting changes to them. An application scenario is presented to discuss the usage of the proposal.

2007

Workflow management systems usually interpret a workflow definition rigidly. However, there are real life situations where users should be allowed to deviate from the prescribed static workflow definition for various reasons, including lack of information, unavailability of the required resources and unanticipated situations. Furthermore, work-flow complexity may grow exponentially if all possible com-binations of anticipated scenarios must be compiled into the workflow definition. To flexibilize workflow execution and help reduce workflow complexity, this paper proposes a dual strategy that combines a library of predefined typical work-flows with a planner mechanism capable of incrementally synthesizing new workflows, at execution time. This dual

International Journal of Web Services Research, 2000

The advent of Web services has made automated workflow composition relevant to web based applications. One technique, that has received some attention, for automatically composing workflows is AI-based classical planning. However, classical planning suffers from the paradox of first assuming deterministic behavior of Web services, then requiring the additional overhead of execution monitoring to recover from unexpected behavior of services. To address these concerns, we propose using Markov decision processes (MDPs), to model workflow composition. Our method models both, the inherent stochastic nature of Web services, and the dynamic nature of the environment. The resulting workflows are robust to non-deterministic behaviors of Web services and adaptive to a changing environment. Using an example scenario, we demonstrate our method and provide empirical results in its support.

2010

Creation and adaptation of workflows is a difficult and costly task that is currently performed by human workflow modeling experts. Our paper describes a new approach for the automatic adaptation of workflows, which makes use of a case base of former workflow adaptations. We propose a general framework for case-based adaptation of workflows and then focus on novel methods to represent and reuse previous adaptation episodes for workflows. An empirical evaluation demonstrates the feasibility of the approach and provides valuable insights for future research.

Journal of Next-Generation Research 5.0, 2025

This paper introduces a novel application of generative AI models to enterprise workflow automation, emphasizing adaptive process design and continuous improvement. By utilizing transformer-based models like GPT for real-time decision-making, the framework empowers workflows to self-optimize based on operational data and evolving business needs. The proposed system integrates Robotic Process Automation (RPA) with generative AI to dynamically suggest process improvements, reducing design time and human intervention. A case study in the e-commerce sector showcases the system's ability to adapt order fulfillment workflows, achieving a 35% reduction in processing time while enhancing customer satisfaction. This research establishes generative AI as a transformative tool for intelligent and adaptive workflow automation, offering unprecedented flexibility and efficiency in enterprise environments.