Discrete Modeling and Simulation of Business Processes Using Event Logs

Determining right model of business process from event log is the purpose of process discovery. However some problems i.e the inability to discover OR, noise and event log incompleteness are emmerged while determining right model of business process. First, OR relation is often discovered as AND relation. Second, noise problem is occured when there are truncated and low frequency traces in event log. Thus control-flow pattern is used to solve issues of same noise relation frequency hence it discovers relation based on transaction function of activity. Consequently, it can refine non noise relation in business process model. Third, incompleteness leads to incorrect discovery of parallel process model; therefore we used Timed-based Process Mining which utilized non-linear dependence to solve the incompleteness. Finally this paper proposed combination of Timed-based Process Mining and control-flow pattern to discover OR and handle same frequency noise and incompleteness. From the experiment in section 3, this proposed method manages to get right process model from event log.

Business process modeling (BPM) is one of the key technologies to benefit enterprises with higher efficiencies and greater business values. However, BPM requires intensive business expertise and human resources. Thus, it is valuable and challenging to enable fast delivery of reusable business process designs, regarding the existence of various popular business processes modeling languages and fast changing markets. In this paper, we generate language-specific business process models and process interaction semantics from UML 2.0 process models. A WS-BPEL metadata model and a process interaction semantics metadata model is defined to annotate UML 2.0 business process model as stereotypes; with a set of transformation patterns, we can generate a WS-BPEL business process model and a process interaction semantics file from each annotated UML 2.0 process model. Our approach can also be similarly applied to other process modeling languages to highly reuse the business process model in UML 2.0.

Business processes and information systems mutually affect each other in non-trivial ways. Frequently, the business process design and the information system design are not well aligned. This means that business processes are designed without taking the information system impact into account, and vice versa. Missing alignment at design time often results in quality problems at runtime, such as large response times of information systems, large process execution times, overloaded information systems or interrupted processes. Aligning business process quality and information system quality at design time requires to
\nsolve the following problems (P). Business process quality and information system quality have to be characterized. P1: In contrast to information system quality, which is specified in the ISO/IEC 9126 standard, for example, there is no common and comprehensive understanding of business process quality. P2: Beyond that, current business process
\nmodeling notations do not aim to represent quality aspects. The impact of a business process on the quality of an information system, and vice versa, is unknown at design
\ntime. P3: The mutual impact between business processes and information systems must be predicted at design time.
\nIn this thesis, the Business Process Quality Reference-Model (BPQRM), a quality model for business processes, is introduced. The model allows for a comprehensive characterization of business process quality (P1). The BPQRM is applied successfully in a case study to
\nidentify potential for process quality improvement in practice. Based on the BPQRM an existing process modeling notation is extended by model elements to represent quality
\naspects (P2). Simulation is a powerful means to predict the impact of a business process on the quality of an information system, and vice versa, at design time. This thesis proposes two simulation approaches to predict the mutual impact between business processes and information systems, in terms of performance (P3). The approach Business
\nIT Impact Simulation (BIIS) defines interfaces between the business process simulation and the information system simulation. Performance-relevant information is exchanged
\nvia the interfaces between both simulations. Using business process simulation and information system simulation in isolation, workload burstiness is not adequately reflected.
\nThis is especially true for occasional, volatile peak loads. Workload burstiness can significantly affect the performance of business processes and information systems. The approach Integrated Business IT Impact Simulation (IntBIIS) for the integration of business processes and information systems in a single simulation allows for reflecting workload burstiness correctly. The simulation approaches support the comparison of design alternatives and the verification of a certain design against requirements. A case study confirms the feasibility in practice and the acceptance from practitioners’ point of
\nview.

The achievement of business goals is heavily affected by the capability of enterprises to design, enforce and govern business processes. The dynamism of the market requires business goals to be constantly tuned, thus obliging the enterprise to continuously re-design processes. The cost for process re-engineering may be not negligible, if we consider that it may require several refinement steps and that tuning processes on-the-job may impair regular business activities. To this end, there is a growing interest towards tools that simulate the processes' performance before they get actually enforced. In this paper we propose a novel business process simulator which makes use of a cost-object resource model to allow for Activity Based Costing (ABC) analysis of the simulation results. The simulator works with business processes modelled in the Business Process Model and Notation (BPMN) and exploits the rigor of the Colored Petri Nets' (CPNets) formalism. A case study test has been conducted on a prototype implementation and related results are presented.

We show how a basic discrete event simulation language can be enabled for business process modeling and simulation by adding an activity construct. While activities are often not considered at all or not treated in a conceptually satisfactory way in the discrete event simulation literature, the great majority of business process modeling languages are based on an activity construct. However, unlike a simulation language, the predominant business process modeling languages, including UML Activity Diagrams and the Business Process Modeling Notation (BPMN), are not executable. So, the challenge for business process modeling is to define an executable semantics for activities, while the challenge for discrete event simulation is to find a way how to introduce an activity construct on top of the basic discrete event simulation concepts of objects and events. The main idea is to define an activity as a complex event having a start event and an end event. This idea is well-known from the business process modeling literature, e.g. from the Business Process Definition Metamodel (Bock 2008), but it has also been used in a rudimentary way in some discrete event simulation approaches, e.g. in (Fishman 2001). Our research contribution consists of two achievements: 1) we define a conceptual model of activities for discrete event simulation and implement it in our ER/AOR simulation language; 2) we show how to use BPMN for the purpose of simulation modeling.

This contribution explores the role of business process simulation to address change management projects dealing with organizational growth. In particular, we consider the adoption of new ICT applications in the context of a growing Small Medium Enterprise based in northern Italy. As income doubled in few years, managers exploited the opportunity to implement a more efficient material resource planning together with an accurate business process analysis. First, the organization was modeled by adopting standard notation BPMN 2.0. Second, data analysis explores organization details as orders arrival, duration of activities, staff working hours. Finally, discrete-event simulation of business processes offers interesting suggestions by varying incoming transactions as well as different parameters in the model. The approach clearly shows how modeling, computational simulation and scenario analysis of business processes are suitable tools to support organizational change.

Although Business process modelling is an increasingly popular research area for both organisations and enterprises due to its usefulness in optimizing resources management, business reengineering and business performance, it is not yet widely accepted in Small and Medium size Enterprises (SMEs), which are vital for sustainable economy development. The understanding of Business Process is an essential approach for an Organization to achieve set objectives and improve its operations. It has been able to show Business Analysts, and Managers where bottleneck exists in the system, how to optimize the Business Process to reduce cost of running the Organization, and the required resources needed for an Organization. This is clear for large scale organizations and enterprises but under research investigation for SMEs. Business Process Modelling (BPM) is a representation of the processes of the Organization. Several modelling techniques have been proposed and used to capture the characteristics of business processes. However, limited guidelines exist for selecting appropriate modelling techniques based on the characteristics of the problem and its requirements. This is even more accurate in the case of selecting proper BPM software tools to achieve those BPM modelling and simulation goals. This paper aims at presenting a comparative analysis of some relatively popular business process modelling techniques focusing on the associated software tools. The comparative framework proposed is based on the following major criteria: data flow capability, logical reasoning and understandability, specification of roles, and capability of simulation, flexibility and ease of use, simulation support and scope. However, the emphasis of this investigation is put on SME applicability of these tools and techniques. Therefore, the first goal is to define proper selection criteria for the application of BPM tools to SMEs. The proposed framework can serve as the basis for evaluating further modelling techniques and generating selection procedures focusing on a comparison of existing tools to implement these techniques properly for SMEs. This is to enable a potential user/modeller choose the right technique and tool in modelling critical SME Business Processes in order to analyse and optimize its operations.

Computer-based simulation models of business processes offer a powerful mechanism for modelling organizational structures and arriving at informed recommendations for change and improvement. In this article, the authors review the current status of the business process modelling (BPM) and business process simulation (BPS) domains, discuss some pertinent issues for their successful deployment, and suggest a number of research directions for organizational modelling.

Process mining is an emerging discipline incorporating methods and tools for the analysis of system/process executions captured in the form of event logs [1]. Traditionally process mining can be divided into three research areas: discovery (construction of process models from event logs), conformance checking (finding log and model deviations), and enhancement of existing process models with additional event log data.BPMN (Business Process Model and Notation) 2.0 [2] is a widely used process modeling notation, supported by various process modeling and analysis tools, and is a de-facto process modeling standard. Using BPMN within process mining opens perspectives for applicability of the existing process mining techniques: for instance discovered process models can be analyzed or enacted using existing BPMN-based software, and vice versa, manually created models can be imported to a process mining tool, verified against event logs, and enhanced with additional data.In this work we bridge the gap between conventional process modeling formalisms used in the context of process mining (e.g., Petri nets, causal nets, process trees) and BPMN. For that purpose we developed a suite of conversion algorithms and provide formal guarantees relating the behavior of Petri nets (including non-free-choice nets) to the corresponding BPMN models (and vice versa). The derived relations are used to enhance the BPMN models with information learned from the event logs.The developed conversion techniques are described in detail in [3] and have been implemented [4] as a part of ProM (Process Mining Framework) [5] -- an open source tool for process mining and verified on real event log data. Moreover, cases for which conversion algorithms give more compact process models in comparison with the initial models are identified. Although the developed algorithms deal with basic control flow constructs only, they can be applied in the discovery of advanced BPMN modeling elements [2], including subprocesses [6-7], cancellations [8], conditional branching and data objects, swimlanes, message flows, and others.

Most actual information systems save transactions in event logs. These logs are not often used to improve the quality of the process model. The area of Process Mining provides techniques and tools which allow the extraction of persistent information about the business process model from event logs in order to incorporate them in a decisional system, and optimise the future executions of the business processes. In this paper, we present an approach using (in addition of event logs) some properties of the tasks composing the business processes like minimum and maximum durations. These properties are used to improve the quality of the underlying processes by a best detection of parallelism, loops and duplicated tasks.

Business process modeling is one of the most important steps in managing the lifecycle of a business process. A digital twin of a business process is a virtual model of a business process designed to replicate the behavior of a real business process. The difference between a digital twin and a business process simulation is that the simulation does not require real-time data, while a digital twin is created based on real-time data. A digital twin comprises a physical entity in the real world, a software-based digital counterpart, and the data that links them both. When a created process communicates in real time with IoT devices and adapts its execution based on the information received in real time, this is referred to as a process digital twin. As the field of digital twins becomes increasingly popular, the challenge is to investigate how the process digital twin communicates with IoT devices in real time and updates its execution state.

Business process modeling aims to construct digital representations of processes being executed in the company. However, models derived from the event logs of their execution tend to overcomplicate the desired representation, making them difficult to apply. The most accurate recovery of the business process model requires a comprehensive study of the various artifacts stored in the company's information system. This paper, however, aims to explore the possibility to automatically obtain the most accurate model of business process, using mutual optimization of models recovered from a set of event logs. Further, the obtained models are executed in multi-agent simulation model of company, and the resulting event logs are examined to determine patterns that are specific to distinct employees and those that generally characterize business process.

The lifecycles of business processes and business software interact with each other since business software is used to support business processes, and requirements on business software are derived from business processes. By integrating these lifecycles, it is possible to test if the business software meets the process-based requirements as well as to identify which impacts changes of the software product have on the business process. In this chapter, the authors give an introduction into these interdependencies. Foundations of lifecycle management, business process modeling, and performance engineering are presented, followed by the description of a framework for an integrated lifecycle management for business processes and business software. This framework is based on business process simulation and software performance prediction. The evaluation of the framework is described by applying it to an example of use and the results are discussed. The chapter closes with a conclusion and an outlook on future work.

Prosimos is an open-source tool that discovers business process simulation models from execution data (event logs) and that enables users to perform what-if analysis using the resulting models. Prosimos distinguishes itself from other data-driven business process simulation approaches in the way it models resources. Existing data-driven simulation approaches treat resources as undifferentiated entities, grouped into resource pools, and assume that all resources in a pool have the same performance and availability calendars. In contrast, Prosimos allows resources (within a pool) to have different performance and availability profiles. For example, instead of treating all claims officers in an insurance claims handling process as having the same performance and availability, Prosimos may capture scenarios where senior resources perform some tasks faster than junior ones, or scenarios where some resources work part-time. To this end, Prosimos integrates algorithms for discovering differentiated resource profiles from event logs.

Business processes are implemented in an organization. When a business process is run, it generates event log. One type of event log is double timestamp event log. Double timestamp has the start and complete time of each activity executed in the business process and has a close relationship with temporal pattern. In this paper, seven types of temporal pattern between activities were presented as extended version of relations used in the double timestamp event log. Since the event log was not always executed in sequential way, therefore using temporal pattern, event log was divided into several small groups to mine the business process both sequential and parallel. Both temporal pattern and Time-based α+ Miner algorithm were used to mine process model, determined sequential and parallel relations and then evaluated the process model using fitness value. This paper was focused on the advantages of temporal pattern implemented in Time-based α+ Miner algorithm to mine business process. The results also clearly stated that the proposed method could present better result rather than that of original α+ Miner algorithm.