Resource Utilization Prediction in Decision-Intensive Business Processes

An appropriate resource utilization is crucial for organizations in order to avoid, among other things, unnecessary costs (e.g. when resources are under-utilized) and too long execution times (e.g. due to excessive workloads, i.e. resource over-utilization). However, traditional process control and risk measurement approaches do not address resource utilization in processes. We studied an often-encountered industry case for providing large-scale technical infrastructure which requires rigorous testing for the systems deployed and identi ed the need of projecting resource utilization as a means for measuring the risk of resource underand over-utilization. Consequently, this paper presents a novel predictive model for resource utilization in decision-intensive processes, present in many domains. In particular, we predict the utilization of resources for a desired period of time given a decision-intensive business process that may include nested loops, and historical data (i.e. order and duration of past activity executions, resource pro les and their experience etc.). We have applied our method using a real business process with multiple instances and presented the outcome.Austrian Research Promotion Agency (FFG) 845638 (SHAPE)Austrian Science Fund (FWF) V 569-N31 (PRAIS

SHAPEworks: A BPMS Extension for Complex Process Management

Abstract. Complex engineering projects, such as the deployment of a railway infrastructure or the installation of an interlocking system, involve human safety and make use of heterogeneous data sources, as well as customized engineering tools. These processes are currently carried out in an ad-hoc fashion, relying on the experience of experts who need to plan, control, and monitor the execution of processes for delivering value to the customers. This setting makes an automated overarching-process a crucial step towards supporting engineers and project managers to deal with safety-critical constraints and the plethora of details entailed by the process. This paper demonstrates a tool that combines methods from automatic reasoning, ontologies and process mining, implemented on top of a real Business Process Management System (BPMS)

(Re)configuration based on model generation

Reconfiguration is an important activity for companies selling configurable products or services which have a long life time. However, identification of a set of required changes in a legacy configuration is a hard problem, since even small changes in the requirements might imply significant modifications. In this paper we show a solution based on answer set programming, which is a logic-based knowledge representation formalism well suited for a compact description of (re)configuration problems. Its applicability is demonstrated on simple abstractions of several real-world scenarios. The evaluation of our solution on a set of benchmark instances derived from commercial (re)configuration problems shows its practical applicability.Comment: In Proceedings LoCoCo 2011, arXiv:1108.609

A Heuristic, Replay-based Approach for Reconfiguration

Abstract. Reconfiguration is an important aspect of industrial product configuration. Once an industrial artefact has been built according to an initial configuration, constant reconfigurations are necessary during its lifetime due to changed requirements or a changed product specification. This reconfigurations should affect as few parts of the running system as possible. Due to the large number of involved components, approaches based on optimization are often not usable in practice. This paper introduces a novel approach for reconfiguration based on a replay heuristic (the product is rebuilt from scratch while trying to use as many decisions from the legacy configuration as possible) and describes its realisation using the standard solving technologies Constraint Satisfaction and Answer Set Programming

Safety-critical Human- and Data-centric Process Management in Engineering Projects

Complex technical systems, industrial systems or infrastructure systems are rich of customizable features and raise high demands on quality and safety-critical aspects. The activities to create complete, valid and reliable planning and customization process data for a product deployment are part of an overarching engineering process that is crucial for the successful completion of a project and, particularly, for verifying compliance to existing regulations in a distributed, heterogeneous environment. In this paper, we discuss the challenges that process management needs to address in such complex engineering projects, and present an architecture that comprises the functionality required together with ndings and results already obtained for its di erent components.Austrian Research Promotion Agency (FFG) 845638 (SHAPE

Solver Requirements for Interactive Configuration

Interactive configuration includes the user as an essential factor in the configuration process. The two main components of an interactive configurator are a user interface at the front-end and a knowledge representation and reasoning (KRR) framework at the back-end. In this paper we discuss important requirements for the underlying KRR system to support an interactive configuration process. Representative of many reasoning systems and tools used for implementing product configurators, we selected MiniZinc, Choco, Potassco, Picat, CP-SAT solver, and Z3 for evaluation and reviewed them against the identified requirements. We observe that many of those requirements are not well supported by existing stand-alone solvers

A Framework for Safety-critical Process Management in Engineering Projects

Complex technical systems, industrial systems or infrastructure systems are rich of customizable features and raise high demands on quality and safety-critical aspects. To create complete, valid and reliable planning and customization process data for a product deployment, an overarching engineering process is crucial for the successful completion of a project. In this paper, we introduce a framework for process management in complex engineering projects which are subject to a large amount of constraints and make use of heterogeneous data sources. In addition, we propose solutions for the framework components and describe a proof-of-concept implementation of the framework as an extension of a well-known BPMS.Austrian Research Promotion Agency (FFG) 845638 (SHAPE