• DocumentCode
    3063585
  • Title

    Process Mining of RFID-Based Supply Chains

  • Author

    Gerke, Kerstin ; Claus, Alexander ; Mendling, Jan

  • Author_Institution
    SAP Res., SAP AG, Dresden, Germany
  • fYear
    2009
  • fDate
    20-23 July 2009
  • Firstpage
    285
  • Lastpage
    292
  • 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.
  • Keywords
    business process re-engineering; data mining; radiofrequency identification; supply chains; EPCglobal standard; RFID; business processes; process mining; radio frequency identification; single-system event logs; supply chain operations reference model; supply chains; Business; Delay; Information processing; Logistics; Process planning; Prototypes; Radiofrequency identification; Supply and demand; Supply chains; Technological innovation; EPCglobal; RFID; process mining; supply chain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Commerce and Enterprise Computing, 2009. CEC '09. IEEE Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    978-0-7695-3755-9
  • Type

    conf

  • DOI
    10.1109/CEC.2009.72
  • Filename
    5210784