Analysis of Internal Logistic Systems based on Event Logs

Transcription

1 ETFA 2010 Dresden University of Technology» Computer Science» Applied Computer Science Analysis of Internal ogistic Systems based on Event ogs Volodymyr Andre Gellrich Klaus Kabitzsch Chair of Technical Information Systems David Wustmann Chair of ogistics Engineering Dresden University of Technology, Germany

2 Outline Challenges in analysis of logistic systems Analysis workflow Extended state-transition model Example of analysis Conclusion and outlook Analysis of Internal ogistic Systems based on Event ogs 2/ 14

3 Use case: baggage transport in airports Typical requirement: max. transport time of one baggage of 30 min. Up to 200 km of conveyor bands, thousands of transport elements Extremely high data amounts Similar complexity in factories, storage depots etc. Incheon (Korea) Main Terminal Kuala umpur (Malaysia) Satellite Terminal Analysis of Internal ogistic Systems based on Event ogs 3/ 14

4 Analysis of logistic processes: challenges Challenges during design: High complexity and heterogeneity of systems High requirements on flexibility and scalability imited time and budget for design State-of-the-Art: Extensive simulations during design and operation ( virtual design ) Only key performance indicators are measured: throughput, transport time, But: only a general overview, not a deep insight Examples of possible questions: Is there a critical node? Is there any tailback? What is its cause? Deeper analysis using event data Analysis of Internal ogistic Systems based on Event ogs 4/ 14

5 Event data Analysis of Internal ogistic Systems based on Event ogs 5/ 14

6 Event data: challenges of analysis Challenges of analysis: Great amount of log data (up to several millions of event records per day) Different logging methods and data formats Different information sources Different viewpoints and purposes Analysis of Internal ogistic Systems based on Event ogs 6/ 14

7 Analysis workflow Simulation Real system Monitoring Import of system topology ogs og ogs parser og indexes og description Event interpretation Model identification Runtime parameters Module library Project manager Project settings Rule management Actions Optimization Fault recovery System model (topology) Runtime parameters Symptoms Visualization Tables, graphs Domain catalogs Rule base Symptom detection Cause effect rules Export / Import Topology models Parameters Expert system Symptom detection Fault diagnosis egend: Data streams Knowledge streams Analysis of Internal ogistic Systems based on Event ogs 7/ 14

8 Extended state-transition model (ESTM) Challenges» Analysis workflow» Extended state-transition model» Example» Conclusion A state may correspond to: - a conveyor transport element, - a machine - a human worker, - oad Path P Parameters of state: -Holding time -Min./Max. -Distribution -Time in system -Min./Max. -Distribution -oad counter -Performance index - State S T Transition Analysis of Internal ogistic Systems based on Event ogs 8/ 14

9 Construction of extended state transition models Challenges» Analysis workflow» Extended state-transition model» Example» Conclusion oad Section Timestamp 001 S01 01:14: S02 01:14: S02 01:14: S04 01:14: S03 01:14: S03 01:14:25 Event log ST S01 S01 S02 S02 S02 S04 Path (P) Not within P TR: Transition ST: State S03 TR S04 Analysis of Internal ogistic Systems based on Event ogs 9/ 14

10 Symptom detection and fault diagnosis Challenges» Analysis workflow» Extended state-transition model» Example» Conclusion An example of the analysis rule: IF TimeInSystem>30 Min THEN Alarm_Delay Types of rules Rules for detection of fault symptoms. Rules for diagnosis of fault causes Rules for countermeasures The rules can be created by: human experts using system models, e.g. topology Analysis of Internal ogistic Systems based on Event ogs 10 / 14

11 Analysis example: baggage transport (1) Calculate transport time of each load ID : TIS t( e( i )) t( e(0)) ID Apply rule A piece of baggage must not travel longer than 30 minutes from one gate to another : 30 TIS ID 10% of loads were too late. What is the cause? Calculate performance index: min( HT p( i) ) PI ID, p( i) HTp( i), ID where holding time of load ID in position p at time instant i: ID last HT t( e( i)) and min(ht p(i) ) is holding time of the most quick load on this segment ID s( i), t( e( i 1)) ID ID ID Analysis of Internal ogistic Systems based on Event ogs 11 / 14

12 Analysis example: baggage transport (2) Performance index: compares actual performance with the best achieved one PI 1 good performance, PI 0 bad performance Tailback analysis: calculate the length of queues in sections sec94 is a buffer for subsequent sections Analysis of Internal ogistic Systems based on Event ogs 12 / 14

13 Further applications Shop floor of a semiconductor factory Internal logistics of semiconductor equipment Assembly lines Business process mining Analysis of Internal ogistic Systems based on Event ogs 13 / 14

14 Conclusion Scope: analysis of logistic processes Contributions: Module-based analysis workflow Dedicated state-transition model A lot of pre-defined characteristic parameters Definition and application of diagnostic rules Advantages: Generic workflow and description model that are adaptable to different use cases (Semi)automatic model generation Successfully applied on several use cases Outlook: Online-analysis for real-time fault detection and optimization Analysis of the mutual influence of parallel processes Advanced rule management Analysis of Internal ogistic Systems based on Event ogs 14 / 14

15 Dresden University of Technology» Computer Science» Institute for Applied Computer Science Questions and comments? Analysis of Internal ogistic Systems based on Event ogs 15 / 14