Showing papers on "Process modeling published in 2011"

Flexible Heuristics Miner (FHM)

Abstract: One of the aims of process mining is to retrieve a process model from a given event log. However, current techniques have problems when mining processes that contain nontrivial constructs, processes that are low structured and/or dealing with the presence of noise in the event logs. To overcome these problems, a new process representation language is presented in combination with an accompanying process mining algorithm. The most significant property of the new representation language is in the way the semantics of splits and joins are represented; by using so-called split/join frequency tables. This results in easy to understand process models even in the case of non-trivial constructs, low structured domains and the presence of noise. This paper explains the new process representation language and how the mining algorithm works. The algorithm is implemented as a plug-in in the ProM framework. An illustrative example with noise and a real life log of a complex and low structured process are used to explicate the presented approach.

Conformance Checking Using Cost-Based Fitness Analysis

Abstract: The growing complexity of processes in many organizations stimulates the adoption of business process analysis techniques. Typically, such techniques are based on process models and assume that the operational processes in reality conform to these models. However, experience shows that reality often deviates from hand-made models. Therefore, the problem of checking to what extent the operational process conforms to the process model is important for process management, process improvement, and compliance. In this paper, we present a robust replay analysis technique that is able to measure the conformance of an event log for a given process model. The approach quantifies conformance and provides intuitive diagnostics (skipped and inserted activities). Our technique has been implemented in the ProM 6framework. Comparative evaluations show that the approach overcomes many of the limitations of existing conformance checking techniques.

A Study Into the Factors That Influence the Understandability of Business Process Models

Abstract: Business process models are key artifacts in the development of information systems. While one of their main purposes is to facilitate communication among stakeholders, little is known about the factors that influence their comprehension by human agents. On the basis of a sound theoretical foundation, this paper presents a study into these factors. Specifically, the effects of both personal and model factors are investigated. Using a questionnaire, students from three different universities evaluated a set of realistic process models. Our findings are that both types of investigated factors affect model understanding, while personal factors seem to be the more important of the two. The results have been validated in a replication that involves professional modelers.

APROMORE : an advanced process model repository

Abstract: Business process models are becoming available in large numbers due to their widespread use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: how can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionality and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.

Efficient Consistency Measurement Based on Behavioral Profiles of Process Models

Abstract: Engineering of process-driven business applications can be supported by process modeling efforts in order to bridge the gap between business requirements and system specifications. However, diverging purposes of business process modeling initiatives have led to significant problems in aligning related models at different abstract levels and different perspectives. Checking the consistency of such corresponding models is a major challenge for process modeling theory and practice. In this paper, we take the inappropriateness of existing strict notions of behavioral equivalence as a starting point. Our contribution is a concept called behavioral profile that captures the essential behavioral constraints of a process model. We show that these profiles can be computed efficiently, i.e., in cubic time for sound free-choice Petri nets w.r.t. their number of places and transitions. We use behavioral profiles for the definition of a formal notion of consistency which is less sensitive to model projections than common criteria of behavioral equivalence and allows for quantifying deviation in a metric way. The derivation of behavioral profiles and the calculation of a degree of consistency have been implemented to demonstrate the applicability of our approach. We also report the findings from checking consistency between partially overlapping models of the SAP reference model.

Enterprise, business-process and information systems modeling : 12th international conference, BPMDS 2011, and 16th international conference, EMMSAD 2011, held at CAiSE 2011, London, UK, June 20-21, 2011 ; proceedings

Abstract: This book contains the refereed proceedings of the 12th International Conference on Business Process Modeling, Development and Support (BPMDS 2011) and the 16th International Conference on Exploring Modeling Methods for Systems Analysis and Design (EMMSAD 2011), held together with the 23rd International Conference on Advanced Information Systems Engineering (CAiSE 2011) in London, UK, in June 2011. The 22 papers accepted for BPMDS were selected from 61 submissions and cover a wide spectrum of issues related to business processes development, modeling, and support. They are grouped into sections on BPMDS in practice, business process improvement, business process flexibility, declarative process models, variety of modeling paradigms, business process modeling and support systems development, and interoperability and mobility. The 16 papers accepted for EMMSAD were chosen from 31 submissions and focus on exploring, evaluating, and enhancing current information modeling methods and methodologies. They are grouped in sections on workflow and process modeling extensions, requirements analysis and information systems development, requirements evolution and information systems evolution, data modeling languages and business rules, conceptual modeling practice, and enterprise architecture.

Modeling Business Processes: A Petri Net-Oriented Approach

Abstract: An introduction to the modeling of business information systems, with processes formally modeled using Petri nets

Analysis on demand: Instantaneous soundness checking of industrial business process models

Abstract: We report on a case study on control-flow analysis of business process models. We checked 735 industrial business process models from financial services, telecommunications, and other domains. We investigated these models for soundness (absence of deadlock and lack of synchronization) using three different approaches: the business process verification tool Woflan, the Petri net model checker LoLA, and a recently developed technique based on SESE decomposition. We evaluate the various techniques used by these approaches in terms of their ability of accelerating the check. Our results show that industrial business process models can be checked in a few milliseconds, which enables tight integration of modeling with control-flow analysis. We also briefly compare the diagnostic information delivered by the different approaches and report some first insights from industrial applications.

User-guided discovery of declarative process models

Abstract: Process mining techniques can be used to effectively discover process models from logs with example behaviour. Cross-correlating a discovered model with information in the log can be used to improve the underlying process. However, existing process discovery techniques have two important drawbacks. The produced models tend to be large and complex, especially in flexible environments where process executions involve multiple alternatives. This “overload” of information is caused by the fact that traditional discovery techniques construct procedural models explicitly showing all possible behaviours. Moreover, existing techniques offer limited possibilities to guide the mining process towards specific properties of interest. These problems can be solved by discovering declarative models. Using a declarative model, the discovered process behaviour is described as a (compact) set of rules. Moreover, the discovery of such models can easily be guided in terms of rule templates. This paper uses DECLARE, a declarative language that provides more flexibility than conventional procedural notations such as BPMN, Petri nets, UML ADs, EPCs and BPEL. We present an approach to automatically discover DECLARE models. This has been implemented in the process mining tool ProM. Our approach and toolset have been applied to a case study provided by the company Thales in the domain of maritime safety and security.

Imperative versus Declarative Process Modeling Languages: An Empirical Investigation

Abstract: Streams of research are emerging that emphasize the advantages of using declarative process modeling languages over more traditional, imperative approaches. In particular, the declarative modeling approach is known for its ability to cope with the limited flexibility of the imperative approach. However, there is still not much empirical insight into the actual strengths and the applicability of each modeling paradigm. In this paper, we investigate in an experimental setting if either the imperative or the declarative process modeling approach is superior with respect to process model understanding. Even when task types are considered that should better match one or the other, our study finds that imperative process modeling languages appear to be connected with better understanding.

Intelligent process modeling and optimization of die-sinking electric discharge machining

Abstract: This paper reports an intelligent approach for process modeling and optimization of electric discharge machining (EDM). Physics based process modeling using finite element method (FEM) has been integrated with the soft computing techniques like artificial neural networks (ANN) and genetic algorithm (GA) to improve prediction accuracy of the model with less dependency on the experimental data. A two-dimensional axi-symmetric numerical (FEM) model of single spark EDM process has been developed based on more realistic assumptions such as Gaussian distribution of heat flux, time and energy dependent spark radius, etc. to predict the shape of crater, material removal rate (MRR) and tool wear rate (TWR). The model is validated using the reported analytical and experimental results. A comprehensive ANN based process model is proposed to establish relation between input process conditions (current, discharge voltage, duty cycle and discharge duration) and the process responses (crater size, MRR and TWR) .The ANN model was trained, tested and tuned by using the data generated from the numerical (FEM) model. It was found to accurately predict EDM process responses for chosen process conditions. The developed ANN process model was used in conjunction with the evolutionary non-dominated sorting genetic algorithm II (NSGA-II) to select optimal process parameters for roughing and finishing operations of EDM. Experimental studies were carried out to verify the process performance for the optimum machining conditions suggested by our approach. The proposed integrated (FEM-ANN-GA) approach was found efficient and robust as the suggested optimum process parameters were found to give the expected optimum performance of the EDM process.

Editorial: Mining business process variants: Challenges, scenarios, algorithms

Abstract: During the last years a new generation of process-aware information systems has emerged, which enables process model configurations at buildtime as well as process instance changes during runtime. Respective model adaptations result in a large number of model variants that are derived from the same process model, but slightly differ in structure. Generally, such model variants are expensive to configure and maintain. In this paper we address two scenarios for learning from process model adaptations and for discovering a reference model out of which the variants can be configured with minimum efforts. The first one is characterized by a reference process model and a collection of related process variants. The goal is to improve the original reference process model such that it fits better to the variant models. The second scenario comprises a collection of process variants, while the original reference model is unknown; i.e., the goal is to ''merge'' these variants into a new reference process model. We suggest two algorithms that are applicable in both scenarios, but have their pros and cons. We provide a systematic comparison of the two algorithms and further contrast them with conventional process mining techniques. Comparison results indicate good performance of our algorithms and also show that specific techniques are needed for learning from process configurations and adaptations. Finally, we provide results from a case study in automotive industry in which we successfully applied our algorithms.

A robust F-measure for evaluating discovered process models

Abstract: Within process mining research, one of the most important fields of study is process discovery, which can be defined as the extraction of control-flow models from audit trails or information system event logs. The evaluation of discovered process models is an essential but difficult task for any process discovery analysis. With this paper, we propose a novel approach for evaluating discovered process models based on artificially generated negative events. This approach allows for the definition of a behavioral F-measure for discovered process models, which is the main contribution of this paper.

Managing process model complexity via abstract syntax modifications

Abstract: As a result of the growing adoption of Business Process Management (BPM) technology different stakeholders need to understand and agree upon the process models that are used to con?gure BPM systems. However, BPM users have problems dealing with the complexity of such models. Therefore, the challenge is to improve the comprehension of process models. While a substantial amount of literature is devoted to this topic, there is no overview of the various mechanisms that exist to deal with managing complexity in (large) process models. It is thus hard to obtain comparative insight into the degree of support offered for various complexity reducing mechanisms by stateof-the-art languages and tools. This paper focuses on complexity reduction mechanisms that affect the abstract syntax of a process model, i.e. the structure of a process model. These mechanisms are captured as patterns, so that they can be described in their most general form and in a language- and tool-independent manner. The paper concludes with a comparative overview of the degree of support for these patterns offered by state-of-theart languages and language implementations.

Syntax highlighting in business process models

Abstract: Sense-making of process models is an important task in various phases of business process management initiatives. Despite this, there is currently hardly any support in business process modeling tools to adequately support model comprehension. In this paper we adapt the concept of syntax highlighting to workflow nets, a modeling technique that is frequently used for business process modeling. Our contribution is three-fold. First, we establish a theoretical argument to what extent highlighting could improve comprehension. Second, we formalize a concept for syntax highlighting in workflow nets and present a prototypical implementation with the WoPeD modeling tool. Third, we report on the results of an experiment that tests the hypothetical benefits of highlighting for comprehension. Our work can easily be transferred to other process modeling tools and other process modeling techniques.

Modeling process-related RBAC models with extended UML activity models

Abstract: ContextBusiness processes are an important source for the engineering of customized software systems and are constantly gaining attention in the area of software engineering as well as in the area of information and system security. While the need to integrate processes and role-based access control (RBAC) models has been repeatedly identified in research and practice, standard process modeling languages do not provide corresponding language elements. ObjectiveIn this paper, we are concerned with the definition of an integrated approach for modeling processes and process-related RBAC models - including roles, role hierarchies, statically and dynamically mutual exclusive tasks, as well as binding of duty constraints on tasks. MethodWe specify a formal metamodel for process-related RBAC models. Based on this formal model, we define a domain-specific extension for a standard modeling language. ResultsOur formal metamodel is generic and can be used to extend arbitrary process modeling languages. To demonstrate our approach, we present a corresponding extension for UML2 activity models. The name of our extension is Business Activities. Moreover, we implemented a library and runtime engine that can manage Business Activity runtime models and enforce the different policies and constraints in a software system. ConclusionThe definition of process-related RBAC models at the modeling-level is an important prerequisite for the thorough implementation and enforcement of corresponding policies and constraints in a software system. We identified the need for modeling support of process-related RBAC models from our experience in real-world role engineering projects and case studies. The Business Activities approach presented in this paper is successfully applied in role engineering projects.

Managing Process Model Complexity Via Abstract Syntax Modifications

Abstract: As a result of the growing adoption of Business Process Management (BPM) technology, different stakeholders need to understand and agree upon the process models that are used to configure BPM systems. However, BPM users have problems dealing with the complexity of such models. Therefore, the challenge is to improve the comprehension of process models. While a substantial amount of literature is devoted to this topic, there is no overview of the various mechanisms that exist to deal with managing complexity in (large) process models. As a result, it is hard to obtain an insight into the degree of support offered for complexity reducing mechanisms by state-of-the-art languages and tools. This paper focuses on complexity reduction mechanisms that affect the abstract syntax of a process model, i.e., the formal structure of process model elements and their interrelationships. These mechanisms are captured as patterns so that they can be described in their most general form, in a language- and tool-independent manner. The paper concludes with a comparative overview of the degree of support for these patterns offered by state-of-the-art languages and tools, and with an evaluation of the patterns from a usability perspective, as perceived by BPM practitioners.

Process compliance analysis based on behavioural profiles

Abstract: Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. In order to judge on compliance of the business processing, the degree of behavioural deviation of a case, i.e., an observed execution sequence, is quantified with respect to a process model (referred to as fitness, or recall). Recently, different compliance measures have been proposed. Still, nearly all of them are grounded on state-based techniques and the trace equivalence criterion, in particular. As a consequence, these approaches have to deal with the state explosion problem. In this paper, we argue that a behavioural abstraction may be leveraged to measure the compliance of a process log – a collection of cases. To this end, we utilise causal behavioural profiles that capture the behavioural characteristics of process models and cases, and can be computed efficiently. We propose different compliance measures based on these profiles, discuss the impact of noise in process logs on our measures, and show how diagnostic information on non-compliance is derived. As a validation, we report on findings of applying our approach in a case study with an international service provider.

Recommendation-based editor for business process modeling

Abstract: To ensure proper and efficient modeling of business processes, it is important to support users of process editors adequately. With only minimal modeling support, the productivity of novice business process modelers may be low when starting process modeling. In this article, we present a theoretically sound and empirically validated recommendation-based modeling support system, which covers different aspects of business process modeling. We consider basic functionality, such as an intuitive search interface, as well as advanced concepts like patterns observed in other users' preferences. Additionally, we propose a multitude of interaction possibilities with the recommendation system, e.g., different metrics that can be used in isolation or an overall recommender component that combines several sub metrics into one comprehensive score. We validate a prototype implementation of the recommendation system with exhaustive user experiments based on real-life process models. To our knowledge, this is the only comprehensive recommendation system for business process modeling that is available.

Causal nets: a modeling language tailored towards process discovery

Abstract: Process discovery--discovering a process model from example behavior recorded in an event log--is one of the most challenging tasks in process mining. The primary reason is that conventional modeling languages (e.g., Petri nets, BPMN, EPCs, and ULM ADs) have difficulties representing the observed behavior properly and/or succinctly. Moreover, discovered process models tend to have deadlocks and livelocks. Therefore, we advocate a new representation more suitable for process discovery: causal nets. Causal nets are related to the representations used by several process discovery techniques (e.g., heuristic mining, fuzzy mining, and genetic mining). However, unlike existing approaches, we provide declarative semantics more suitable for process mining. To clarify these semantics and to illustrate the non-local nature of this new representation, we relate causal nets to Petri nets.

Object-Aware Business Processes: Fundamental Requirements and their Support in Existing Approaches

Abstract: Despite the increasing maturity of process management technology not all business processes are adequately supported by it. Support for unstructured and knowledge-intensive processes is missing, especially since they cannot be straight-jacketed into predefined activities. A common characteristic of these processes is the role of business objects and data as drivers for process modeling and enactment. This paper elicits fundamental requirements for effectively supporting such object-aware processes; i.e., their modeling, execution, and monitoring. Imperative, declarative, and data-driven process support approaches are evaluated and how well they support object-aware processes are investigated. A tight integration of process and data as major steps towards further maturation of process management technology is considered.