Preprocessing Support for Large Scale Process Mining of SAP Transactions

Ingvaldsen, Jon Espen; Gulla, Jon Atle

doi:10.1007/978-3-540-78238-4_5

Cited by 58 publications

(46 citation statements)

References 6 publications

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“…Different techniques related with process mining [1] attempt to solve the issues related with data collection [7,8] and its conversion [9,10]. Similarly in [11], author proposes a data format for recording business events.…”

Section: Framework For Improvementmentioning

confidence: 99%

Business Process Improvement Framework and Representational Support

Lodhi

Köppen

Saake

2012

Advances in Intelligent Systems and Computing

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Abstract. Business process management and improvement are vital for enterprises in competitive environments. Understanding of a process is a pre-requisite and important step for improvement. Interaction between humans, computers, and business objects provide excellent opportunities for knowledge extraction. However, the specification of a framework is required for business process improvement, which extends from data collection, analytical methods, storage, and representation of knowledge. The process models conceived for information system development are not sufficient for post execution analysis and improvement. In this paper, we specify such a framework briefly and focus on providing representational support for business process improvement. The main objective is to improve the overall improvement process by providing enriched graphical process models. Furthermore, we use a case study to explain the proposed usage and extensions of an existing modeling language for business process improvement.

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Section: Framework For Improvementmentioning

confidence: 99%

Business Process Improvement Framework and Representational Support

Lodhi

Köppen

Saake

2012

Advances in Intelligent Systems and Computing

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“…The input for process mining is a set of event logs, which all can be related to different instances of a process. These event logs typically stem from processaware information systems such as workflow applications or ERP systems [10]. Using mining algorithms, it is possible to automatically construct process models from the event logs [8], [22].…”

Section: B Challenges Of Mining Supply Chainsmentioning

confidence: 99%

“…A particular problem relates to the reformatting and enrichment of log data that stems from information systems that are not directly process-aware, e.g. SAP log data [10]. Our work is unique in this context, as it identifies how RFID events (available in EPCglobal format) can be used to construct cases such that process mining can be applied.…”

Section: Related Workmentioning

confidence: 99%

Process Mining of RFID-Based Supply Chains

Gerke

Claus

Mendling

2009

2009 IEEE Conference on Commerce and Enterprise Computing

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Abstract-Process mining facilitates the analysis of business processes by extracting a process model from event logs. Most mining algorithms perform well on single-system event logs that explicitly refer to a process instance or case. However, in many operational environments such case identifiers are not directly recorded. In supply chain processes there are even further challenges, since different identification numbers and numerous aggregation steps prevent individual work items to become traceable as a case. In this paper, we investigate how the EPCglobal standard for processing Radio Frequency Identification (RFID) events can make supply chain data accessible for process mining. Our contribution is an algorithm that is able to deal with challenges of case identification and focus shifts. We present a prototypical implementation and use a process based on the Supply Chain Operations Reference (SCOR) Model to evaluate our implementation.

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“…RapidProM is an extension that adds process mining plugins from ProM to the well-known data mining workflow tool RapidMiner 7 . For our task, an OpenSLEX meta model population operator has been implemented in a development branch 8 of RapidProM. This operator, together with the data handling operators of RapidMiner (including database connectors), lets us extract, transform and query our populated meta model automatically in a single execution of the workflow.…”

Section: Methodsmentioning

confidence: 99%

“…Some work has been done in this field to assist in the extraction and log generation task [2]. Also, studies have been performed on how to extract events in specific environments like SAP [8,10,18] or other ERP systems [12]. In [5], we presented a more general solution to extract events from databases, regardless of the application under study.…”

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confidence: 99%

Connecting databases with process mining: a meta model and toolset

2018

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Process mining techniques require event logs which, in many cases, are obtained from databases. Obtaining these event logs is not a trivial task and requires substantial domain knowledge. In addition, an extracted event log provides only a single view on the database. To change our view, e.g., to focus on another business process and generate another event log, it is necessary to go back to the source of data. This paper proposes a meta model to integrate both process and data perspectives, relating one to the other. It can be used to generate different views from the database at any moment in a highly flexible way. This approach decouples the data extraction from the application of analysis techniques, enabling the application of process mining in different contexts.

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Preprocessing Support for Large Scale Process Mining of SAP Transactions

Cited by 58 publications

References 6 publications

Business Process Improvement Framework and Representational Support

Business Process Improvement Framework and Representational Support

Process Mining of RFID-Based Supply Chains

Connecting databases with process mining: a meta model and toolset

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