Process Mining of RFID-Based Supply Chains

Gerke, Kerstin; Claus, Alexander; Mendling, Jan

doi:10.1109/cec.2009.72

Cited by 23 publications

(15 citation statements)

References 19 publications

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“…Furthermore, scalability also has to be provided on the analytical and the conceptual side. For instance, mining large-scale process-related event data requires dedicated approaches [35].…”

Section: Scalabilitymentioning

confidence: 99%

Towards Living Inter-organizational Processes

Breu

Dustdar

Eder

et al. 2013

2013 IEEE 15th Conference on Business Informatics

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Abstract-Business Process Management (BPM) has gained significant adoption in practice for enabling organizations to increase their effectiveness, efficiency, and flexibility. This broad adoption has not only been fostered by a rich and wellestablished theory to model, analyze, simulate, and enact business processes, but also by internationally accepted standards and mature technologies. Caused by the ever increasing speed and volatility of markets and the dynamics of new technologies, such as cloud infrastructures and mobile communications, we face a new generation of business processes, which we refer to as living inter-organizational processes. Such processes are not in control of one single organization; instead, they are enacted by multiple organizations, where no participating party possesses full control over the entire process. Such processes often involve a high number of actors that might even be unknown in advance. These actors require various degrees in participation, they are acting in heterogeneous environments. Moreover, such processes are often weakly structured or designed in an ad-hoc manner, and have to be continuously subject to evolution. Unfortunately, existing theories, methodologies, and technologies cannot cope with this challenging combination of aspects, which all have to be considered when dealing with living inter-organizational processes. The state of the art typically addresses singular aspects in isolation. However, a holistic approach to these challenges bears a tremendous potential. This paper aims to contribute towards a holistic approach to living inter-organizational processes. To this end, we describe different perspectives on inter-organizational processes and identify challenges for making them living processes.

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“…Furthermore, scalability also has to be provided on the analytical and the conceptual side. For instance, mining large-scale process-related event data requires dedicated approaches [35].…”

Section: Scalabilitymentioning

confidence: 99%

Towards Living Inter-organizational Processes

Breu

Dustdar

Eder

et al. 2013

2013 IEEE 15th Conference on Business Informatics

Self Cite

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“…This problem is known in process mining for a while, e.g. [7]. It has been tackled more generally in database research in [2] and adapted to event logs in [4].…”

Section: Related Workmentioning

confidence: 99%

Mining processes with multi-instantiation

Weber

Farshchi

Mendling

et al. 2015

Proceedings of the 30th Annual ACM Symposium on Applied Computing

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Process mining, in particular discovering process models by mining event traces, is becoming a widely adopted practice. However, when the underlying process contains subprocesses which are instantiated multiple times in parallel, classical process mining techniques that assume a flat process are not directly applicable. Their application can cause one of two problems: either the mined model is overly general, allowing arbitrary order and execution frequency of activities in the sub-process, or it lacks fitness by capturing only single instantiation of sub-processes. For conformance checking, this results in a too high rate of either false positives or false negatives, respectively. In this paper, we propose an extension to well-known process mining techniques, adding the capability of handling multi-instantiated sub-processes to discovery and conformance checking. We evaluate the approach with a real-world data set.

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“…Therefore, process mining provides a promising way to acquire insights into the real dynamics in logistics by discovering knowledge from the logistics processes (Chun et al, 2011;van Dongen & van der Aalst, 2004). While existing research has been carried out on the application of process mining in logistics for discovering knowledge in the supply chain network (Gerke, Claus, & Mendling, 2009;Lau, Ho, Zhao, & Chung, 2009) and for constructing compressed workflows to capture the general trends of the logistics processes (Gonzalez, Han, & Li, 2006), study of contemporary research publications indicates that there is a lack of articles related to a comprehensive methodology for process mining in logistics to provide intelligence support for logisticians.…”

Section: Logistics Intelligence and Process Mining Techniquesmentioning

confidence: 99%