This EEWC 2020 keynote presentation is available from

https://dpmn.info/reading/EEWC2020.

https://dpmn.info/reading/EEWC2020.

- Setting the Scene
- Part I: Discrete Dynamic Systems
- Part II: Object-Event Modeling and Simulation (OEM&S)
- Part III: Outlook

- First things first:
**objects**and**events**before**agents**and**actions** - A
**Business Process Modeling (BPM)**language is only meaningful if it allows making**Business Process Simulation (BPS)**models - The
**Business Process Modeling Notation (BPMN)**does not allow making BPS models

**Discrete Event Simulation (DES)**frameworks for BPS use proprietary modeling languages based on the 70-years old**Processing Networks (PN)**paradigm- BPMN-based BPS is
**incompatible**with DES-based BPS - The
**Discrete Event Process Modeling Notation (DPMN)**combines BPMN with DES-based BPS

- A
**limited**concept of "business process" (e.g., only human resources) - Overloading/
**ambiguity**of*sequence flow arrows* **Insufficient**integration of the**objects**that participate in a process**Insufficient**support of**resource management****No**support of**processing activities****No**convincing**formal semantics**

Which resources are there?

- When a BPM language allows simulation, it does have an
**execution semantics** - There are various proposals how to extend BPMN for BPS: Signavio, BIMP (Univ. Tartu), etc.)
- All of them result in quite limited forms of BPS:
- no conditional branching
- only human, but no other, resources
- lack of support for important resource management features (alternative resources, pre-emption)

- In DES, there are many paradigms (and a lot of conceptual confusion)
- The two main paradigms are
**Event-Based Simulation**and (higher-level)**Processing Network (PN) Simulation** - There are 10+ commercial DES tools, all of them focusing on PN Simulation, but with different (proprietary) terminologies and diagram languages
- PN Simulation is a form of BPS, but it is incompatible with BPMN

A real world system consisting of **objects** and a discrete flow of **events**
such that at any moment in time, the system's past is a sequence of situations each characterized by

- a time point
*t*(the situation time) - the system's object states
*O*at*t*, and - a set of
**imminent events**, to occur at times greater than*t*.

and each situation *S _{t+1}* is created from

An event *[email protected]* causes:

**state changes***Δ*of affected objects, and**follow-up events***e*_{1}@t_{1}, e_{2}@t_{2},...

according to the **dispositions** of affected objects, which can be generalized as **causal regularities**
of the form

with *O* being the set of the system's object states at time *t*, such that

is the resulting changed system state.

Computationally, a DDS can be represented by an *Object Event Model (OEM)* consisting of:

*object types**OT*, e.g., in the form of*classes*of an object-oriented language;*event types**ET*, e.g., in the form of*classes*of an object-oriented language;*event rules**R*representing*causal regularities*, e.g., in the form of`onEvent`

methods of the class that implements the triggering event type.

While *OT* and *ET* can be defined by a UML Class Diagram, the set of event rules *R* can be defined by a DPMN Process Diagram.

- Discrete processes are governed by
**causal regularities**, which relate events with (1)**state changes**of affected objects and (2)**follow-up events**. - A
**discrete process**consists of a partially ordered set of events that happen in a spatio-temporal region determined by the events' participants and the causal regularities involved. - A
**business process**is a discrete process that "happens in the context of an organization".

- Since events depend on objects, we first need to model object types and then event types.
- A process model is based on an underlying information model defining the types of its objects and events.
- A
*conceptual process model*describes the causal regularities of a real world process.

- A
*simulation design model*consists of an*information design model*and a*process design model*. - An
*information design model*defines*object types*and*event types*(e.g., in the form of classes in a UML Class Diagram). - A
*process design model*defines**event rules**that represent causal regularities (e.g., in a DPMN Process Diagram).

Event Graphs (EGs) have been proposed for DES modeling by Schruben in 1983.

**Strengths**:

- EGs provide an intuitive visual modeling language.
- EGs capture the fundamental
*event scheduling*paradigm.

**Weaknesses**:

- EGs lack a visual notation for (conditional and parallel) branching.
- EGs do not support OO state structure modeling (with objects/classes and attributes).
- EGs do not support activities.

The integer variable *L* denotes the length of the input buffer.

The Boolean variable *B* denotes the busy/available status of the service desk or machine.

...is the *Discrete Event Process Modeling Notation*, which extends *Event Graphs* by adding:

*Exclusive/Inclusive/Parallel*for conditional/parallel branching**Gateways**for replacing "state variables" (like**Data Objects***L*) with attributes (like*WorkStation::inputBufferLength*)**Activities**

A *DPMN Process Model* is composed of **Event Rule Models**.

- OEM&S is a new modeling and simulation paradigm with a
*formal*semantics and an*ontological*foundation. - The preferred modeling languages for OEM&S are
*UML Class Diagrams*and*DPMN Process Diagrams*. - OES has been implemented in
*JavaScript*, a*Python*implementation will follow. - DPMN allows modeling of message-based communication (with
*out-message*and*in-message*events). - OEM&S can be extended by adding
*Agents*with*Beliefs*about, and*Perceptions*of, their environment - How to model (DEMO)
*transactions*in DPMN still has to be investigated.

- Gerd Wagner: An Abstract State Machine Semantics For Discrete Event Simulation,
*Proc. of the 2017 Winter Simulation Conference*. - Gerd Wagner: Information and Process Modeling for Simulation – Part I: Objects and Events.
*Journal of Simulation Engineering*1:1, 2018. - Gerd Wagner: Information and Process Modeling for Simulation – Part II: Activities and Processing Networks. 2019.
- Available on
`dpmn.info`