A Discrete-Event Simulation Metamodel for Obtaining Simulation Models from Business Process Models

Information System is one of the key domain in which lot of research has been done in the past few years. Applying Information systems to heterogeneous and distributed environments is one of the current research areas. Business Process Management Systems is the information systems which deal with the administration of tasks in the business processes, organizational structures, or in the related context. The Workflow Management system, the early idea of BPM, controls the workflow in an organization, data transfer, and integration of legacy information systems with existing programs and program modules, delegation of business tasks. Offering task management services especially modeling of business processes and underlying organizations, BPM serves it meaning and incorporates the WFM system. BPM supporting the use of knowledge concerning the awareness/unawareness of integrated software, and analysis of processes and organizational structure in terms of verification, modification, evaluation are key management in BPM system I.INTRODUCTION TO BPM: Combination of corporate restructuring and mergers urged the department and processes to be automated and linked together. Unfortunately it created largely disconnected spaghetti of systems and applications. Business Process Management (BPM) was born from a strong need to streamline internal processes and connections between both internal and external functions. It provides ability to model, monitor, manage and manipulate processes quickly in response to changes in strategy and market forces. BPM is an extension of classical Work Flow Management (WFM) systems and approaches. BPM delivers the maximum utility of legacy system. It is a method for revolutionizing the way the work moves throughout an organization. II.COMPONENTS OF BPM: The four key elements in Business Process Management are: Process modeling, Process rule, Process management, and Process performance analytics. Process modeling: Process modeling describes the flow of information (business process).It helps in building a model of process and mapping into an implementation frame work. Modeling requires a consistent analysis and representation of the processes. It forms the basis for the userspecific process environment. Process Rule: Process Rule is a heart of the BPM. It involves execution of discrete steps & integration of information. A process rules engine is used for this purpose. The engine is to monitor and manage the given steps by providing a flow control over the business process. If a process fails or delayed, a compensated action can be done to rectify. Process Management: Process Management is to correlate business/application events to fundamental business metrics .It enables the organization to monitor and optimize the business process. Once the process has been analyzed, modeled and the associated rules are formed. The next stage involves the visualization and management. Visualization means transaction data ranging from holistic to process-state or client state specific rules. Process Performance Analytics: Process Performance Analytics is a transition data source available for sophisticated management analytics .This data should be available on a retrospective or real-time basis. It should answer to one of the most difficult question like “how much does it cost to process a specific transaction?” By this way BPM mainly addresses four components. They are Work Flow Management, Content and records management Enterprise Application Integration (EAI) and Business Activity monitoring (BAM). III.RELEVENCE TO SYSTEM INTEGRATION: BPM can be fitted easily on the top of existing IT system. It is the Process rules that governs all the happenings and optimizes the process. BPM will not be able to work without the connectivity provided by the EAI layer. EAI layer provides BPM to gain and measure the value from the investment. On the other hand, BPM provides value to the EAI technology layer of Information technology. BPM layer offers business management the view of the message processing layer. It is used to unlock the value of the information held in the integration layer. It is also used to gather data of every transaction in the lifecycle. IV.APPLICATION OF BPM: BPM can be applied to any application which needs these advantages. BPM reduces unnecessary high losses in time critical transactions, helps to provide any critical information, practical application yield fast ROI ,better control over the information, identifying and maximizing the benefits faster, better analysis and tracking, provides enterprise-wide visibility of business processes, improve the effectiveness of the core operations, provides ability to coordinate interactions between information systems, business process and the people, flexible and easily changed by non-technical business people.

Nowadays, the problem in business process management (BPM) is that BPM systems should both be easy to use for business process developers and be based on a sound formal method. Business process management systems are often based on semiformal modeling techniques such as event-driven process chains (EPC) or UML. Unlike semiformal modeling techniques, the process calculus CSP comes with mature verification sup- port. Surprisingly little work has been done on using CSP for business process modeling and management. In this paper, we present our approach to business process management, which is based on the observation that CSP is well suited not only for specifying business processes and verifying work???ows but also for executing work???ows using our CSP4J framework. We report on a work???ow server, which is specified in CSP and implemented using our CSP4J framework. The server accepts work???ows that are modeled in CSP and also implemented using CSP4J. This allows us to integrate the mature verification support of CSP into both the management system itself and the development process of the end users’ business process definitions.

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.

Business process modelling is an important part of system design. When designing or redesigning a business process, stakeholders specify, negotiate, and agree on business requirements to be satisfied, including non-functional requirements that concern the quality of the business process. This thesis addresses the question of how to specify and compute the quality of a business process, given the model that stakeholders use. The motivation for this thesis is the increasing importance of the quality of business processes. Knowing the quality of specific business processes enables stakeholders to judge if these processes need improvement. Knowing the quality of the constructs of those processes (viz., events, inputs, activities, and outputs) and the way they are structured enables a more detailed analysis of their shortcomings and provides a basis for the design of improvements. The research challenge of this thesis is grounded in the assumption that: “Organisations need an appropriate means to effectively compute achievement of their goals and objectives by their business processes.” Given this challenge, the main research question on which this thesis focuses is: “Can the quality of a business process be computed quantitatively at different levels of granularity?” The research objective is: “To develop frameworks, factors, and metrics for computing non-functional requirements (quality) of business processes quantitatively at different levels of granularity.” The outcomes of this thesis are: 1) BPIMM, a language-independent business process integrating meta-model, based on the concepts of seven mainstream business process modelling languages: BPMN, EPC, RAD, UML AD, SADT, IDEF0, and IDEF3. 2) BPC-QC (Business Process Concept - Quality Computation), an approach to quality computation at the lowest level of granularity of a business process. The approach consists of: i. BPC-QEF (Business Process Concept - Quality Evaluation Framework), a language-independent generic framework and algorithm to compute the quality of the constructs of a business process: event, input, activity, and output. ii. A set of business process quality dimensions and factors. The following quality dimensions are distinguished: performance, efficiency, reliability, recoverability, permissibility, and availability. Each dimension categorises different quality aspects in terms of factors. A non-exhaustive set of sixteen quantitative factors is provided. iii. Quality metrics for each of the quality factors, to facilitate a quantitative computation of the quality of a specific construct of a business process. 3) BP-QC (Business Process - Quality Computation), an approach to compute the quality at the highest level of granularity of a business process. The approach consists of: i. BP-CQCF (Business Process - Compositional Quality Computation Framework), a language-independent generic framework and algorithm to compute the quality of a business process as a whole, given the quality of its constructs. ii. A set of generic business process modelling patterns to decompose a business process into more succinct parts, namely: sequential, parallel with synchronisation, exclusive, inclusive, simple loop, and complex loop. iii. A set of over one hundred computational formulae. For each combination of modelling pattern and a quality factor, there is a formula to compute the quality. 4) AAV (Approach to Application and Validation), an evaluation plan to evaluate BPIMM, BPC-QC and BP-QC in practice, together with expert stakeholders. The plan consists of the units of measure, a measurement model, and a case study procedure. To evaluate the applicability of the contributions of this thesis to real world business needs, four case studies have been conducted in different environments: a Dutch educational institution, a global financial institution, an international financial service provider, and a Dutch research project on crisis management. Each of these case studies concerns a different, single business process. This thesis shows that: 1) A quality computation approach can be adopted independent of a business process modelling language. 2) Quantitative quality factors can be introduced specifically for the constructs of a business process. 3) Quantitative metrics and computational formulae can be developed for specific quality factors, allowing the computation of different aspects of the quality of a business process quantitatively at different levels of granularity. 4) An evaluation plan can be developed to evaluate the applicability of the contributions of this thesis (viz., BPIMM, BPC-QC, and BP-QC). The contributions of this thesis are designed to be beneficial to the areas of business and management, requirements engineering, software engineering, and business process modelling. In the areas of requirements engineering and software engineering, these contributions are intended to help practitioners to consider non-functional requirements at the earliest stage. In the area of business process modelling, information systems, service computing, and cloud computing, the contributions can be used for quality-driven modelling, design, and redesign. To conclude, knowing the quality value of a business process at different levels of granularity provides a basis for its improvement.

Business process management (BPM) based on the usage of simulation modelling allows organizations to sustain and improve their operational performance. Discrete event simulation (DES) can help identify resource's bottlenecks, such as staffing, estimate process execution or delay times, test improvement suggestions in the process design phase, and overall assist in understanding how processes might impact performance in various scenarios. While many research papers report on the industry applications of BPM and DES, we focus to higher educational institutions (HEIS). Goals of the paper are: (1) to review the research of BPM and DES in HEIs, and (2) to discuss the impact of BPM and DES to process performance in one Croatian HEI. The case study methodology has been used in order to shed some light on the issue of applying discrete event simulation in BPM in the HEIs, especially for the purpose of collaboration improvement and impact assessment.

Business processes are essential components of all enterprises and the use of models, languages and execution engines as components of a Business Process Management (BPM) deployment are now commonplace. By definition, these processes describe an enterprise in terms of its organizational knowledge, structure and activities, and are often essential to realizing an organization's competitive advantage. It thus follows that the design, execution and, critically, responsiveness to change in the system or environment they are affecting, is of prime significance toward establishing and maintaining efficient business operation. Deploying a high quality and effective Business Process Management System (BPMS) is thus utterly essential to many modern enterprises. Yet current trends toward flexible methods of working, just-in-time organizational reaction times, distributed intra-organization and interorganization collaboration and constantly changing markets are creating new and complex business landscapes. This brings about increased complexity, further motivating the need for real-time dynamic change throughout an enterprise's business processes; ever more dynamic environments require key business processes to be more flexible and automated in both their design and behaviour. Yet many companies are now discovering that investments in conventional BPMS often suffers from poor return on investment due to a common inability to create business process models that are both meaningful to business people and capable of offering the real-time process flexibility and rapid process adaptation required to cope effectively with the fluid business conditions typifying many modern enterprises. As evidenced by our work with customers in the manufacturing domain, there is very often a need to alter executing process structures, sometimes in real-time, without perturbing the integrity of running process instances. If a BPMS is not built to innately support change in this manner the result can be reductions in both dependability and visibility, especially from a management perspective. Our observation is that many of the current procedural approaches to BPM are too inflexible and unresponsive to change, especially in any automated fashion. In fact many BPMS solutions provide only design-time modelling, with neither support for run-time determination of process structure, nor direct execution of industry standard Business Process Modeling Notation (BPMN) process models without the need for first translating BPMN into intermediary formats, such as the Business Process Execution Language (BPEL), in preparation for execution. In practice, these issues imply that process models can tend to become overly complex and brittle through the necessity of coding-in all O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

IoT-aware business processes are gaining momentum as part of an effort to exploit the potential of IoT technology in the business process management field. The conventional lifecycle of a business process (BP) consists of several phases, from modeling and analysis down to implementation, monitoring and optimization. The availability of widely used standard notations for BP modeling, such as BPMN, allows business analysts to specify their BPs and get the corresponding implementations in an effective and largely automated way. Introducing IoT technologies from the BP design phase proves to bring significant improvements in terms of BP efficiency but also difficulties, when it comes to deal with the complexity and heterogeneity of such technologies at BP modeling time. This paper proposes an approach, named Process over Things (PoT), that aims at overcoming such difficulties by using a standardized ontology to deal with IoT interaction at BP modeling and design time. The proposed approach introduces a BPMN extension to explicitly address the IoT ontology in the BPMN model, yet being independent of the specific ontology implementation. A technology named PoT Broker is also introduced to fill the gap between the BP execution platform and the IoT devices access layer. The PoT Broker also obtains a significant level of automation when implementing IoT-aware BPs making use of a specific IoT ontology. The paper describes the architecture of the PoT approach and illustrates its application to a case study dealing with a weather alert system.

Background and Purpose: Agent-based modelling and simulation (ABS) is growing in many areas like, e.g., management, social and computer sciences. However, the similar trend does not seem to occur within the field of business process management (BPM), even though simulation approaches like discrete event simulation or system dynamics are well established and widely used. Thus, in our paper we investigate the advantages and disadvantages of agent-based modelling and simulation in the field of BPM in simulation experiments. Design/Methodology/Approach: In our research, we investigate if there is a necessity for ABS in the field of BPM with our own simulation experiments to compare traditional and ABS models. For this purpose, we use simulation framework MAREA, which is a simulation environment with integrated ERP system. Our model is a complex system of a trading company selling computer cables. For the verification of our model, we use automated process discovery techniques. Results: In our simulations, we investigated the impact of changes in resources’ behavior on the outcome of company’s order to cash process (O2C). Simulations experiments demonstrated that even small changes might have statistically significant effect on outcomes of the processes and decisions based on such outcomes. Simulation experiments also demonstrated that the impact of randomly distributed fluctuations of well-being have a diminishing tendency with the increasing number of sales representatives involved in the process. Conclusions: Our research revealed several advantages and disadvantages of using ABS in business process modelling. However, as we show, many of them were at least partially addressed in the recent years. Thus, we believe that ABS will get more attention in the field of BPM similarly to other fields like, e.g., social sciences. We suggested areas in BPM simulations, e.g., modelling of resources, be it human or technological resources, where there is a need for ABS.

Business Process Management (BPM) is the factual criteria for business process modeling. Although it is widely used in various fields, when required When using business processes to express big data business processes, the existing business process specifications do not support it. Big data business can only be simulated as multiple manual tasks before execution, which is not friendly to non-big data technology practitioners, and will The non-standardized business process and poor reusability lead to a reduction in the efficiency of business completion. On the other hand, while supporting big data technology brings flexibility to BPM, it consumes a lot of process engine resources when executing big data business processes, and the execution efficiency is low, which brings greater burden to the process engine. Aiming at the above deficiencies, this paper carries out the following work: (1) Extend the existing business process modeling, and define a new category of " Big Data Service Task" by extending the activity elements in BPMN2.0 (2) Propose a compatible big data technology The task scheduling strategy in the business process includes a single big data task scheduling decision and an intensive big data task scheduling decision.

Business processes (BPs) are nowadays essential elements and key assets in any commercial organization. Additionally, BP matters are important issues in the context of enterprise computing. Business process management (BPM) is the main research area for process-aware systems involving methodologies, models, and supporting tools for process design, execution, and monitoring. BPM offers many challenges for software developers, including process specification and documentation. This paper is about (operational) BPs (e.g., procurement, hiring a new employee, supply chain management, request for leave), with a focus on modeling BPs in which all sub-processes, activities, data flows, inputs, and outputs, together with their relationships with each other, are identified and described. Typically, the focus of traditional process modeling is persistently on diagrammatic tools to design process notations (e.g., UML and BPMN). In this paper, we adopt a diagrammatic modeling methodology called the Thinging Machine (TM) and use it as a base to promote understanding of notions of BPs by offering a new perspective that captures a system’s dynamic behavior based on its events. The TM emphasizes a single unifying ontological element: the thing/machine concept (thimac), in contrast to object- or process-oriented methodologies. TM-based modeling can be a valuable tool in the general area of BPM. We partially demonstrate that by applying it to document two actual administrative systems. The resultant conceptual descriptions reflect a well-defined approach to the notions of processes and events.

PurposeThe purpose of this paper is to address a theoretical gap in the business process management (BPM) literature on factors that influence the acceptance and use of business process modelling (PM) in organisations. The paper seeks to contribute to theory building and practice in BPM through better understanding of important determinants of PM adoption and use.Design/methodology/approachA combination of literature review and 34 interviews in context was used to develop a PM acceptance model that was subsequently empirically tested using survey data from 74 companies.FindingsThe paper provides empirical insights about how business PM can be influenced by many factors in the organisational context. It suggests that PM is a complex activity mandated by management, but influenced by individual and socio‐political factors.Research limitations/implicationsThere is a need for future research to focus on the many opposing forces that influence business PM in organisations. Future studies should analyse influence from different stakeholder groups separately to reveal their relative influence on PM activity and its outcomes.Practical implicationsThe paper identifies important forces in the organisational context that managers should focus on in their efforts to successfully implement business PM in their organisations.Originality/valueThis paper uses a triangulation of sources of information to better understand the less‐studied process of PM adoption and use in an organisational context. It contributes to theory building within BPM and to more successful BPM in organisations.

Business processes are designed to execute strategies that aim at achieving organisational goals. During the last decade, several methods have been proposed that prescribe the use of goal-oriented requirements engineering techniques for supporting different business process management activities, in particular business process modelling. The integration of goal modelling and business process modelling aims at increasing the alignment between business strategies and the processes with their supporting IT systems. This new research area, which the authors call Goal-Oriented Requirements Engineering for Business Processes (GORE-for-BP), is developing rapidly, but without a clear conceptualization of the focus and scope of the proposed GORE-for-BP methods. Furthermore, an overview is lacking of which methods exist and what their level of maturity is. This paper therefore presents a research review of the GORE-for-BP area, with the aim of identifying relevant methods and assessing their focus, scope, and maturity. This study used Systematic Literature Review and Method Meta-Modelling as research methods to identify and evaluate the state of the GORE-for-BP research area and to propose a research agenda for directing future research in the area. Nineteen methods were identified, which is an indication of an active research area. Although some similarities were found with respect to how goal models are transformed into business process models (or vice-versa), there is also considerable divergence in modelling languages used and the extent of coverage of typical requirements engineering and business process management lifecycle phases. Furthermore, the exploitation of requirements engineering techniques in the full business process management lifecycle is currently under researched. Also, the maturity of the methods found in terms of the formalisation of the transformation activity, the elaboration of method guidelines, and the extent to which methods are validated, can be further improved.

The constant change and rising complexity of organizations, mainly due to the transforming nature of their business processes, has driven the increase of interest in business process management by organizations. It is recognized that knowing business processes can help to ensure that the software under development will meet the business needs. Some of software development processes (like unified process) already refer to business process modeling as a first effort in the software development process. A business process model usually is created under the supervision, clarification, approval, and validation of the business stakeholders. Thus, a business process model is a proper representation of the reality (as is or to be), having lots of useful information that can be used in the development of the software system that will support the business. The chapter uses the information existing in business process models to derive software models specially focused in generating a data model.

A Multidimensional Knowledge Model for Business Process Modeling

Being a part of business process management (BPM) life cycle, business process modeling has found its place in information systems development (ISD) practices as well. At the same time, concepts of business vocabularies and rules are also the hot topics among BPM and ISD practitioners and academics. Nevertheless, in ISD, the integration of business process models with business vocabularies and rules is still not standardized and remains quite empiric. In this paper, basic aspects of the approach for business vocabularies’ extraction from business process models are presented. The approach is based on novel business level OMG standards “Business Process Model and Notation” (BPMN) and “Semantics for Business Vocabularies and Business Rules” (SBVR), thus contributing to OMG’s vision about Model-Driven Architecture (MDA) and to model-driven development in general.DOI: http://dx.doi.org/10.5755/j01.itc.42.2.2310