Semantic Business Process Mining of SAP Transactions

2010 ◽  
pp. 416-429
Author(s):  
Jon Espen Ingvaldsen ◽  
Jon Atle Gulla
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Process Mining ◽  
Structured Data ◽  
The Core ◽  
Management Perspective ◽  
System Logs ◽  
Business Process Mining ◽  
Semantic Process

This chapter introduces semantic business process mining of SAP transaction logs. SAP systems are promising domains for semantic process mining as they contain transaction logs that are linked to large amounts of structured data. A challenge with process mining these transaction logs is that the core of SAP systems was not originally designed from the business process management perspective. The business process layer was added later without full rearrangement of the system. As a result, system logs produced by SAP are not process-based, but transaction-based. This means that the system does not produce traces of process instances that are needed for process mining. In this chapter, we show how data available in SAP systems can enrich process instance logs with ontologically structured concepts, and evaluate techniques for mapping executed transaction sequences with predefined process hierarchies.

Semantic Business Process Mining of SAP Transactions

2011 ◽  
pp. 866-878 ◽  
Author(s):  
Jon Espen Ingvaldsen ◽  
Jon Atle Gulla
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Process Mining ◽  
Structured Data ◽  
The Core ◽  
Management Perspective ◽  
System Logs ◽  
Business Process Mining ◽  
Semantic Process

This chapter introduces semantic business process mining of SAP transaction logs. SAP systems are promising domains for semantic process mining as they contain transaction logs that are linked to large amounts of structured data. A challenge with process mining these transaction logs is that the core of SAP systems was not originally designed from the business process management perspective. The business process layer was added later without full rearrangement of the system. As a result, system logs produced by SAP are not process-based, but transaction-based. This means that the system does not produce traces of process instances that are needed for process mining. In this chapter, we show how data available in SAP systems can enrich process instance logs with ontologically structured concepts, and evaluate techniques for mapping executed transaction sequences with predefined process hierarchies.

Business process management for Industry 4.0 – Three application cases in the DFKI-Smart-Lego-Factory

2018 ◽  
Vol 60 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Jana-Rebecca Rehse ◽  
Sharam Dadashnia ◽  
Peter Fettke
Keyword(s):  
Business Process ◽  
Industry 4.0 ◽  
Business Process Management ◽  
Manufacturing Industry ◽  
Process Management ◽  
Process Mining ◽  
Smart Factory ◽  
Manufacturing Processes ◽  
Planning And Control ◽  
And Control

Abstract The advent of Industry 4.0 is expected to dramatically change the manufacturing industry as we know it today. Highly standardized, rigid manufacturing processes need to become self-organizing and decentralized. This flexibility leads to new challenges to the management of smart factories in general and production planning and control in particular. In this contribution, we illustrate how established techniques from Business Process Management (BPM) hold great potential to conquer challenges in Industry 4.0. Therefore, we show three application cases based on the DFKI-Smart-Lego-Factory, a fully automated “smart factory” built out of LEGO® bricks, which demonstrates the potentials of BPM methodology for Industry 4.0 in an innovative, yet easily accessible way. For each application case (model-based management, process mining, prediction of manufacturing processes) in a smart factory, we describe the specific challenges of Industry 4.0, how BPM can be used to address these challenges, and, their realization within the DFKI-Smart-Lego-Factory.

GOAL-ORIENTED PROCESSES WITH GPMN

2011 ◽  
Vol 20 (06) ◽  
pp. 1021-1041 ◽  
Author(s):  
KAI JANDER ◽  
LARS BRAUBACH ◽  
ALEXANDER POKAHR ◽  
WINFRIED LAMERSDORF ◽  
KARL-JOSEF WACK
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Workflow Execution ◽  
Business People ◽  
The Core ◽  
Working Together ◽  
Important Means ◽  
Core Idea

Business process management is a challenging task that requires business processes being described, executed, monitored and continuously enhanced. This process management lifecycle requires business as well as IT people working together, whereby the view on business process is quite different on both sides. One important means for bridging the gap between both consists in having a modeling notation that can be easily understood but also has a precise semantics and can be used as a basis for workflow execution. Although existing approaches like BPMN and EPCs aim at being such as notation they are already very activity oriented and do not consider the underlying motivations of processes. Introducing the goal oriented process modeling notation (GPMN) a new language is presented that has the objective of bringing together both sides by establishing higher-level modeling concepts for workflows. This results in an increased intelligibility of workflow descriptions for business people and greater consideration for the way processes are described on the business side. The core idea of the approach consists in introducing different kinds of goals and goal relationships in addition to the established activity-centered behavior model. The applicability of the approach is further illustrated with an example workflow from Daimler AG.

The Proposition of a Framework for Semantic Process Mining

2014 ◽  
Vol 1051 ◽  
pp. 995-999
Author(s):  
Yong Xin Liao ◽  
Eduardo Rocha Loures ◽  
Eduardo Alves Portela Santos ◽  
Osiris Canciglieri
Keyword(s):  
General Framework ◽  
Business Process Management ◽  
Process Management ◽  
Process Mining ◽  
Related Information ◽  
Event Logs ◽  
Semantic Mining ◽  
Semantic Models ◽  
Footprint Analysis ◽  
Semantic Process

As one of the hot topics in Business Process Management (BPM), process mining aims at constructing models to explain what is actually happening from different perspectives based on the process-related information that automatically extracted from event logs. Because the semantics of the data that recorded in event logs are not usually explicit, current mining approaches are somewhat limited. A number of studies have been carried out in the combination use of formalized semantic models and process mining technologies to obtain the semantic mining capability. However, among these researches, there is lack of a guideline that can clearly illustrate different stages during the semantic process mining. The objective of this study is to present a general framework, which unambiguously expresses the main stages of the semantic process mining. Based on this framework, an example about carbon footprint analysis is used to show the possibility of obtaining advantages from semantic process mining.

scholarly journals Industry 4.0 and business process management

2019 ◽  
Vol 13 (4) ◽  
pp. 349-355
Author(s):  
Jiri Tupa ◽  
Frantisek Steiner
Keyword(s):  
Process Improvement ◽  
Business Process ◽  
Industry 4.0 ◽  
Business Process Management ◽  
Process Management ◽  
New Technologies ◽  
The Core ◽  
New Methods ◽  
Theoretical Paper ◽  
The Cost

Production companies are adopting new methods for the improvement of their managing production processes. The cost, quality and time are still key important attributes for process improvement. This is reason why the Business Process Management (BPM) is the core of management in different areas, e.g., quality management, sustainability management. The new technologies based on Internet of Things and Services, SMART solutions, and the concept Industry 4.0 are opening new possibilities of BPM implementation. This theoretical paper deals with a review of new trends in BPM and a presentation of the possibilities of core technologies for Industry 4.0 in phases of BPM applications.

scholarly journals HyperLDLf: a Logic for Checking Properties of Finite Traces Process Logs

2021 ◽  
Author(s):  
Giuseppe De Giacomo ◽  
Paolo Felli ◽  
Marco Montali ◽  
Giuseppe Perelli
Keyword(s):  
Model Checking ◽  
Business Process ◽  
Finite Length ◽  
Regular Language ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Process Mining ◽  
Temporal Logics ◽  
Relevant Case

Temporal logics over finite traces, such as LTLf and its extension LDLf, have been adopted in several areas, including Business Process Management (BPM), to check properties of processes whose executions have an unbounded, but finite, length. These logics express properties of single traces in isolation, however, especially in BPM it is also of interest to express properties over the entire log, i.e., properties that relate multiple traces of the log at once. In the case of infinite-traces, HyperLTL has been proposed to express these ``hyper'' properties. In this paper, motivated by BPM, we introduce HyperLDLf, a logic that extends LDLf with the hyper features of HyperLTL. We provide a sound, complete and computationally optimal technique, based on DFAs manipulation, for the model checking problem in the relevant case where the set of traces (i.e., the log) is a regular language. We illustrate how this form of model checking can be used for verifying log of business processes and for advanced forms of process mining.

Building Semantic Business Process Space for Agile and Efficient Business Processes Management

2012 ◽  
pp. 51-73
Author(s):  
Gunwoo Kim ◽  
Yongmoo Suh
Keyword(s):  
Business Process ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Limited Area ◽  
Successful Implementation ◽  
Order Process ◽  
The Core ◽  
Automatic Discovery ◽  
Current Practices

Current practices of BPM suffer from the several fundamental problems, including difficulty with automatic discovery and the integration of business processes across organizations. Many studies uncovered that the main cause of these problems lies in insufficient semantics on business processes and suggested semantic business process management (SBPM) as a solution. Although building semantic business process space (SBPS) must be at the core of the SBPM approach to resolving the problems, most research on SBPM hardly deal with it seriously. Thus, this research shows how to build SBPS by incorporating semantics with business processes. The authors first illustrate the idea of building SBPS by defining a variety of generic and specific business process ontologies for the limited area of sales order process. They then explain how the SBPS satisfies the requirements for successful implementation of SBPM and demonstrate with a scenario how SBPM can be realized in the environment of SBPS for the agile and efficient BPM.

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