Showing papers on "Process modeling published in 2009"

Business process modeling - a comparative analysis

Abstract: Many business process modeling techniques have been proposed over the last decades, creating a demand for theory to assist in the comparison and evaluation of these techniques. A widely established way of determining the effectiveness and efficiency of modeling techniques is by way of representational analysis. This paper comparatively assesses representational analyses of 12 popular process modeling techniques in order to provide insights into the extent to which they differ from each other. We discuss several implications of our findings. Our analysis uncovers and explores representational root causes for a number of shortcomings that remain in process modeling practice, such as lack of process decomposition and integration of business rule specification. Our findings also serve as motivation and input to future research in areas such as context-aware business process design and conventions management.

From business process models to process-oriented software systems

Abstract: Several methods for enterprise systems analysis rely on flow-oriented representations of business operations, otherwise known as business process models. The Business Process Modeling Notation (BPMN) is a standard for capturing such models. BPMN models facilitate communication between domain experts and analysts and provide input to software development projects. Meanwhile, there is an emergence of methods for enterprise software development that rely on detailed process definitions that are executed by process engines. These process definitions refine their counterpart BPMN models by introducing data manipulation, application binding, and other implementation details. The de facto standard for defining executable processes is the Business Process Execution Language (BPEL). Accordingly, a standards-based method for developing process-oriented systems is to start with BPMN models and to translate these models into BPEL definitions for subsequent refinement. However, instrumenting this method is challenging because BPMN models and BPEL definitions are structurally very different. Existing techniques for translating BPMN to BPEL only work for limited classes of BPMN models. This article proposes a translation technique that does not impose structural restrictions on the source BPMN model. At the same time, the technique emphasizes the generation of readable (block-structured) BPEL code. An empirical evaluation conducted over a large collection of process models shows that the resulting BPEL definitions are largely block-structured. Beyond its direct relevance in the context of BPMN and BPEL, the technique presented in this article addresses issues that arise when translating from graph-oriented to block-structure flow definition languages.

Enterprise, Business-Process and Information Systems Modeling

Abstract: This book contains the proceedings of two long-standing workshops: The 10th International Workshop on Business Process Modeling, Development and Support, BPMDS 2009, and the 14th International Conference on Exploring Modeling Methods for Systems Analysis and Design, EMMSAD 2009, held in connection with CAiSE 2009 in Amsterdam, The Netherlands, in June 2009. The 17 papers accepted for BPMDS 2009 were carefully reviewed and selected from 32 submissions. The topics addressed by the BPMDS workshop are business and goal-related drivers; model-driven process change; technological drivers and IT services; technological drivers and process mining; and compliance and awareness. Following an extensive review process, 16 papers out of 36 submissions were accepted for EMMSAD 2009. These papers cover the following topics: use of ontologies; UML and MDA; ORM and rule-oriented modeling; goal-oriented modeling; alignment and understandability; enterprise modeling; and patterns and anti-patterns in enterprise modeling.

Context aware trace clustering : towards improving process mining results

Abstract: Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms have problems dealing with such unstructured processes and generate spaghetti-like process models that are hard to comprehend. An approach to overcome this is to cluster process instances (a process instance is manifested as a trace and an event log corresponds to a multi-set of traces) such that each of the resulting clusters correspond to a coherent set of process instances that can be adequately represented by a process model. In this paper, we propose a context aware approach to trace clustering based on generic edit distance. It is well known that the generic edit distance framework is highly sensitive to the costs of edit operations. We define an automated approach to derive the costs of edit operations. The method proposed in this paper outperforms contemporary approaches to trace clustering in process mining. We evaluate the goodness of the formed clusters using established fitness and comprehensibility metrics defined in the context of process mining. The proposed approach is able to generate clusters such that the process models mined from the clustered traces show a high degree of fitness and comprehensibility when compared to contemporary approaches.

Business Process Modeling: Current Issues and Future Challenges

Abstract: Business process modeling has undoubtedly emerged as a popular and relevant practice in Information Systems. Despite being an actively researched field, anecdotal evidence and experiences suggest that the focus of the research community is not always well aligned with the needs of industry. The main aim of this paper is, accordingly, to explore the current issues and the future challenges in business process modeling, as perceived by three key stakeholder groups (academics, practitioners, and tool vendors). We present the results of a global Delphi study with these three groups of stakeholders, and discuss the findings and their implications for research and practice. Our findings suggest that the critical areas of concern are standardization of modeling approaches, identification of the value proposition of business process modeling, and model-driven process execution. These areas are also expected to persist as business process modeling roadblocks in the future.

Petri Net Transformations for Business Processes --- A Survey

Abstract: In Process-Aware Information Systems, business processes are often modeled in an explicit way. Roughly speaking, the available business process modeling languages can be divided into two groups.Languages from the first group are preferred by academic people but shunned by business people, and include Petri nets and process algebras. These academic languages have a proper formal semantics, which allows the corresponding academic models to be verified in a formal way. Languages from the second group are preferred by business people but disliked by academic people, and include BPEL, BPMN, and EPCs. These business languages often lack any proper semantics, which often leads to debates on how to interpret certain business models. Nevertheless, business models are used in practice, whereas academic models are hardly used. To be able to use, for example, the abundance of Petri net verification techniques on business models, we need to be able to transform these models to Petri nets. In this paper, we investigate a number of Petri net transformations that already exist.For every transformation, we investigate the transformation itself, the constructs in the business models that are problematic for the transformation and the main applications for the transformation.

Modeling Languages for Business Processes and Business Rules: A Representational Analysis

Abstract: Process modeling and rule modeling languages are both used to document organizational policies and procedures. To date, their synergies and overlap are under-researched. Understanding the relationship between the two modeling types would allow organizations to maximize synergies, avoid content duplication, and thus reduce their overall modeling effort. In this paper we use the Bunge-Wand-Weber (BWW) representation theory to compare the representation capabilities of process and rule modeling languages. We perform a representational analysis of four rule modeling specifications: The Simple Rule Markup Language (SRML), the Semantic Web Rules Language (SWRL), the Production Rule Representation (PRR) and the Semantics of Business Vocabulary and Business Rules (SBVR) specification. We compare their BWW representation capabilities with those of four popular conceptual process modeling languages. In our analysis we focus on the aspects of maximum ontological completeness and minimum ontological overlap. The outcome of this study shows that no single language is internally complete with respect to the BWW representation model. We also show that a combination of two languages, in particular SRML and BPMN, appears to be better suited for combined process and rule modeling than any of these modeling languages used independently.

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.

Similarity search of business process models

Abstract: Similarity search is a general class of problems in which a given object, called a query object, is compared against a collection of objects in order to retrieve those that most closely resemble the query object. This paper reviews recent work on an instance of this class of problems, where the objects in question are business process models. The goal is to identify process models in a repository that most closely resemble a given process model or a fragment thereof.

Questionnaire-based variability modeling for system configuration

Abstract: Variability management is a recurrent issue in systems engineering. It arises for example in enterprise systems, where modules are configured and composed to meet the requirements of individual customers based on modifications to a reference model. It also manifests itself in the context of software product families, where variants of a system are built from a common code base. This paper proposes an approach to capture system variability based on questionnaire models that include order dependencies and domain constraints. The paper presents analysis techniques to detect circular dependencies and contradictory constraints in questionnaire models, as well as techniques to incrementally prevent invalid configurations by restricting the space of allowed answers to a question based on previous answers. The approach has been implemented as a toolset and has been used in practice to capture configurable process models for film post-production.

Abstractions in Process Mining: A Taxonomy of Patterns

Abstract: Process mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms have problems dealing with such unstructured processes and generate spaghetti-like process models that are hard to comprehend. One reason for such a result can be attributed to constructing process models from raw traces without due pre-processing. In an event log, there can be instances where the system is subjected to similar execution patterns/behavior. Discovery of common patterns of invocation of activities in traces (beyond the immediate succession relation) can help in improving the discovery of process models and can assist in defining the conceptual relationship between the tasks/activities. In this paper, we characterize and explore the manifestation of commonly used process model constructs in the event log and adopt pattern definitions that capture these manifestations, and propose a means to form abstractions over these patterns. We also propose an iterative method of transformation of traces which can be applied as a pre-processing step for most of today's process mining techniques . The proposed approaches are shown to identify promising patterns and conceptually-valid abstractions on a real-life log. The patterns discussed in this paper have multiple applications such as trace clustering, fault diagnosis/anomaly detection besides being an enabler for hierarchical process discovery.

Trace clustering based on conserved patterns : towards achieving better process models

Abstract: Process mining refers to the extraction of process models from event logs Real-life processes tend to be less structured and more flexible Traditional process mining algorithms have problems dealing with such unstructured processes and generate “spaghetti-like” process models that are hard to comprehend An approach to overcome this is to cluster process instances such that each of the resulting clusters correspond to coherent sets of process instances that can each be adequately represented by a process model In this paper, we present multiple feature sets based on conserved patterns and show that the proposed feature sets have a better performance than contemporary approaches We evaluate the goodness of the formed clusters using established fitness and comprehensibility metrics defined in the context of process mining The proposed approach is able to generate clusters such that the process models mined from the clustered traces show a high degree of fitness and comprehensibility Further, the proposed feature sets can be easily discovered in linear time making it amenable to real-time analysis of large data sets

Business Process Modeling: Perceived Benefits

Abstract: The process-centered design of organizations and information systems is globally seen as an appropriate response to the increased economic pressure on organizations. At the methodological core of process-centered management is process modeling. However, business process modeling in large initiatives can be a time-consuming and costly exercise, making it potentially difficult to convince executive management of its benefits. To date, and despite substantial interest and research in the area of process modeling, the understanding of the actual benefits of process modeling in academia and practice is limited. To address this gap, this paper explores the perception of benefits derived from process modeling initiatives, as reported through a global Delphi study. The study incorporates the views of three groups of stakeholders --- academics, practitioners and vendors. Our findings lead to the first identification and ranking of 19 unique benefits associated with process modeling. The study in particular found that process modeling benefits vary significantly between practitioners and academics. We argue that the variations may point to a disconnect between research projects and practical demands.

Flexibility in Process-Aware Information Systems

Abstract: Process-aware information systems (PAIS) must be able to deal with uncertainty, exceptional situations, and environmental changes. Needed business agility is often hindered by the lacking flexibility of existing PAIS. Once a process is implemented, its logic cannot be adapted or refined anymore. This often leads to rigid behavior or gaps between real-world processes and implemented ones. In response to this drawback, adaptive PAIS have emerged, which allow to dynamically adapt or evolve the structure of process models under execution. This paper deals with fundamental challenges related to structural process changes, discusses how existing approaches deal with them, and shows how the various problems have been exterminated in ADEPT2 change framework. We also survey existing approaches fostering flexible process support.

Providing Integrated Life Cycle Support in Process-Aware Information Systems

Abstract: The need for more flexibility of process-aware information systems (PAISs) has been discussed for several years and different approaches for adaptive process management have emerged. However, only few of them provide support for both changes of individual process instances and the propagation of process type changes to a collection of related process instances. Furthermore, knowledge about process changes has not yet been exploited by any of these systems. This paper presents the ProCycle approach which overcomes this practical limitation by capturing the whole process life cycle and all kinds of changes in an integrated way. Users are not only allowed to deviate from the predefined process in exceptional situations, but are also assisted in retrieving and reusing knowledge about previously performed changes in this context. If similar instance deviations occur frequently, process engineers will be supported in deriving improved process models from them. This, in turn, allows engineers to evolve the PAIS (including the knowledge about the changes) over time. Feasability of the ProCycle approach is demonstrated by a proof-of-concept prototype which combines adaptive process management technology with concepts and methods provided by case-based reasoning (CBR) technology.

Statistical Process Optimization Through Multi-Response Surface Methodology

Abstract: In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages. Keywords—Multi-Response Surface Methodology (MRSM), Design of Experiments (DOE), Process modeling, Quality improvement; Robust Design.

Process-Aware Information Systems: Lessons to Be Learned from Process Mining

Abstract: A Process-Aware Information System (PAIS) is a software system that manages and executes operational processes involving people, applications, and/or information sources on the basis of process models. Example PAISs are workflow management systems, case-handling systems, enterprise information systems, etc. This paper provides a brief introduction to these systems and discusses the role of process models in the PAIS life-cycle. Moreover, it provides a critical reflection on the state-of-the-art based on experiences with process mining . Process mining techniques attempt to extract non-trivial and useful information from event logs. One aspect of process mining is control-flow discovery, i.e., automatically constructing a process model (e.g., a Petri net) describing the causal dependencies between activities. The insights provided by process mining are very valuable for the development of the next generation PAISs because they clearly show a mismatch between the models proposed for driving these systems and reality. On the one hand, models tend to oversimplify things resulting in systems that are too restrictive. On the other hand, models fail to capture important aspects of business processes.

Communication flow orientation in business process modeling and its effect on redesign success: Results from a field study

Abstract: Business process redesign has been intensely studied, particularly since the mid 1990s. One aspect that received little attention, however, is the relationship between business process modeling choices and redesign success. This research gap is addressed through a multi-methods study of 18 business process redesign projects conducted in 18 different organizations. A structural equation model is developed and tested based on data collected from those projects; the results are then triangulated with qualitative data. The structural equation model depicts relationships between the following broad perceptual constructs: communication flow orientation of a business process model, quality of a business process model, and business process redesign success. The communication flow orientation of a business process model is defined as the extent to which a model explicitly shows how communication interactions take place in a process. A model's perceived quality is defined as the degree to which the model presents the following perceptual sub-constructs: ease of generation, ease of understanding, completeness, and accuracy. The results of the study suggest that the degree of communication flow orientation of a business process model is significantly related to the model's perceived quality. Perceived model quality, in turn, is significantly related to perceived business process redesign success. Interestingly, a business process model's perceived completeness does not seem to be influenced by a model's communication flow orientation. The structural equation model accounted for 56% of the explained variance in the business process redesign success construct. The main implication of this study is that a focus on communication flows in business processes is an important ingredient in successful business process redesign projects.

Discovering Reference Models by Mining Process Variants Using a Heuristic Approach

Abstract: Recently, a new generation of adaptive Process-Aware Information Systems (PAISs) has emerged, which enables structural process changes during runtime. Such flexibility, in turn, leads to a large number of process variants derived from the same model, but differing in structure. Generally, such variants are expensive to configure and maintain. This paper provides a heuristic search algorithm which fosters learning from past process changes by mining process variants. The algorithm discovers a reference model based on which the need for future process configuration and adaptation can be reduced. It additionally provides the flexibility to control the process evolution procedure, i.e., we can control to what degree the discovered reference model differs from the original one. As benefit, we cannot only control the effort for updating the reference model, but also gain the flexibility to perform only the most important adaptations of the current reference model. Our mining algorithm is implemented and evaluated by a simulation using more than 7000 process models. Simulation results indicate strong performance and scalability of our algorithm even when facing large-sized process models.

Analyzing resource behavior using process mining

Abstract: It is vital to use accurate models for the analysis, design, and/or control of business processes. Unfortunately, there are often important discrepancies between reality and models. In earlier work, we have shown that simulation models are often based on incorrect assumptions and one example is the speed at which people work. The “Yerkes-Dodson Law of Arousal” suggests that a worker that is under time pressure may become more efficient and thus finish tasks faster. However, if the pressure is too high, then the worker’s performance may degrade. Traditionally, it was difficult to investigate such phenomena and few analysis tools (e.g., simulation packages) support workload-dependent behavior. Fortunately, more and more activities are being recorded and modern process mining techniques provide detailed insights in the way that people really work. This paper uses a new process mining plug-in that has been added to ProM to explore the effect of workload on service times. Based on historic data and by using regression analysis, the relationship between workload and services time is investigated. This information can be used for various types of analysis and decision making, including more realistic forms of simulation.

Semantic Process Modeling – Design and Implementation of an Ontology-based Representation of Business Processes

Abstract: An extension of process modeling languages is designed which allows representing the semantics of model element labels which are formulated in natural language by using concepts of a formal ontology. This combination of semiformal models with formal ontologies will be characterized as semantic process modeling. The approach is exemplarily applied to the languages EPC (Event-driven Process Chain), BPMN (Business Process Modeling Notation) and OWL (Web Ontology Language) and is generalized by means of an information model. The proposed formalization of the semantics of individual model elements in conjunction with the usage of inference engines allows the improvement of query functionalities in modeling tools and enables new possibilities of model validation. The integration of the approach in the IT-based work environments of modelers is demonstrated by a system architecture and a prototypical implementation. Evidently, advantages in the areas of modeling, model management, IT-business alignment, and compliance can be achieved by the application of modeling tools augmented with semantic technologies.

Redesigning business processes: a methodology based on simulation and process mining techniques

Abstract: Nowadays, organizations have to adjust their business processes along with the changing environment in order to maintain a competitive advantage. Changing a part of the system to support the business process implies changing the entire system, which leads to complex redesign activities. In this paper, a bottom-up process mining and simulation-based methodology is proposed to be employed in redesign activities. The methodology starts with identifying relevant performance issues, which are used as basis for redesign. A process model is “mined” and simulated as a representation of the existing situation, followed by the simulation of the redesigned process model as prediction of the future scenario. Finally, the performance criteria of the current business process model and the redesigned business process model are compared such that the potential performance gains of the redesign can be predicted. We illustrate the methodology with three case studies from three different domains: gas industry, government institution and agriculture.

Role of process knowledge in business process improvement methodology: a case study

Abstract: Purpose – The purpose of this paper is to analyse the importance and role of process knowledge in the business process (BP) improvement methodology with the help of a case study.Design/methodology/approach – The approach takes the form of a literature review that highlights the challenges and issues in the existing BP improvement methodologies. An in‐depth case study that has embarked on a major BP improvement initiative that emphasizes individual and collective process knowledge in a real‐life complex organization is presented.Findings – The paper confirms that BP improvement is, in fact, a complex, knowledge‐intensive, collaborative process that consists of a set of coordinated, contextualized knowledge management processes. The design of the “to‐be” process in this study is a knowledge co‐creation process that uses collaborative exploration of different scenarios and contexts. Compared with the traditional BP improvement methodologies where the main emphasis is on the design of a new process model, the...

Improved model management with aggregated business process models

Abstract: Contemporary organizations invest much efforts in creating models of their business processes. This raises the issue of how to deal with large sets of process models that become available over time. This paper proposes an extension of Event-driven Process Chains, called the aggregate EPC (aEPC), which can be used to describe a set of similar processes with a single model. By doing so, the number of process models that must be managed can be decreased. But at the same time, the process logic for each specific element of the set over which aggregation takes place can still be distinguished. The presented approach is supported as an add-on to the ARIS modeling tool box. To show the feasibility and effectiveness of the approach, we discuss its practical application in the context of a large financial organization.

Activity patterns in process-aware information systems: basic concepts and empirical evidence

Abstract: Recently, a variety of workflow patterns have been suggested for capturing different aspects in process-aware information systems (PAISs), including control and data flow, resources, process change and exception handling. All these patterns are highly relevant for implementing PAISs and for designing process modelling languages. However, current patterns provide only a partial answer to the question of which business functions a designer might want to reuse when modelling processes. This paper presents a revised version of a collection of activity patterns to deal with this challenge. Each of them is related to a recurrent business function as it can be frequently found in process models (e.g., task execution request, notification, approval). We describe the identified activity patterns and their variants in detail. The main purpose of our paper is to discuss results from empirical studies in which we analysed more than 200 process models in order to evidence the practical relevance of the patterns. This includes a detailed analysis of the context in which activity patterns occur as well as the frequency of this occurrence. These empirical findings can be used for the design of more intelligent, pattern-based process modelling tools.

Modelling and simulation of process: machine interaction in grinding

Abstract: This article presents an overview of current simulation methods describing the interaction of grinding process and grinding machine structure, e.g., vibrations, deflections, or thermal deformations. Innovative process models which describe the effects of the grinding wheel–workpiece interaction inside the contact zone are shown in detail. Furthermore, simulation models representing the static and dynamic behaviour of a grinding machine and its components are discussed. Machine tool components with a high influence on the process results are modelled more detailed than those with low influence. The key issue of the paper is the coupling of process and machine tool models for predicting the interactions of process and machine. Several coupling methods are introduced and the improvements of the simulation results are documented. On the basis of the presented simulation approaches, grinding processes and machines can be designed more effectively resulting in higher workpiece quality and process stability.

Managing variability in process-aware information systems

Abstract: Configurable process models are integrated representations of multiple variants of a process model in a given domain, e.g. multiple variants of a shipment-to-delivery process in the logistics domain. Configurable process models provide a basis for managing variability and for enabling reuse of process models in Process-Aware Information Systems. Rather than designing process models from scratch, analysts can derive process models by configuring existing ones, thereby reusing proven practices. This thesis starts with the observation that existing approaches for capturing and managing configurable process models suffer from three shortcomings that affect their usability in practice. Firstly, configuration in existing approaches is performed manually and as such it is error-prone. In particular, analysts are left with the burden of ensuring the correctness of the individualized models. Secondly, existing approaches suffer from a lack of decision support for the selection of configuration alternatives. Consequently, stakeholders involved in the configuration of process models need to possess expertise both in the application domain and in the modeling language employed. This assumption represents an adoption obstacle in domains where users are unfamiliar with modeling notations. Finally, existing approaches for configurable process modeling are limited in scope to control-flow aspects, ignoring other equally important aspects of process models such as object flow and resource management. Following a design science research method, this thesis addresses the above shortcomings by proposing an integrated framework to manage the configuration of process models. The framework is grounded on three original and interrelated contributions: (i) a conceptual foundation for correctness-preserving configuration of process models; (ii) a questionnaire-driven approach for process model configuration, providing decision support and abstraction from modeling notations; (iii) a meta-model for configurable process models covering control-flow, data objects and resources. While the framework is language-independent, an embodiment of the framework in the context of a process modeling language used in practice is also developed in this thesis. The framework was formally defined and validated using four scenarios taken from different domains. Moreover, a comprehensive toolset was implemented to support the validation of the framework.

Defining ETL worfklows using BPMN and BPEL

Abstract: Decisional systems are crucial for enterprise improvement. They allow the consolidation of heterogeneous data from distributed enterprise data stores into strategic indicators. An essential component of this data consolidation is the Extract, Transform, and Load (ETL) process. In the research literature there has been very few work defining conceptual models for ETL processes. At the same time, there are currently many tools that manage such processes. However, each tool uses its own model, which is not necessarily able to communicate with the models of other tools. In this paper, we propose a platform-independent conceptual model of ETL processes based on the Business Process Model Notation (BPMN) standard. We also show how such a conceptual model can be implemented using Business Process Execution Language (BPEL), a standard executable language for specifying interactions with web services.