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Evaluation of Disturbances in Mechanized Tunneling Using Process Simulation
Author(s) -
Rahm Tobias,
Scheffer Markus,
Thewes Markus,
König Markus,
Duhme Ruben
Publication year - 2016
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12143
Subject(s) - process (computing) , computer science , systems modeling language , dimensioning , interdependence , production (economics) , supply chain , discrete event simulation , reliability engineering , systems engineering , risk analysis (engineering) , simulation , engineering , unified modeling language , medicine , software , law , political science , economics , macroeconomics , programming language , aerospace engineering , operating system
Abstract Production in mechanized tunneling frequently encounters disruptions due to sensitive process interdependencies. Reasons can be technical failures, insufficient capacity dimensioning, organizational deficiencies, or sensitive supply chains. These unproductive times could be reduced by an adequately designed project setup including logistical aspects. Therefore, possible disturbances must be identified and analyzed in detail. Based on this investigation, the machine and logistics setup can be changed to cope with unforeseen events. We present a modeling and simulation approach to analyze production and logistic processes of mechanized tunneling processes in a transparent and understandable way. The system is formalized in the modeling standard SysML. Thereby, we consider relevant system elements and process interdependencies to assess the effect of disturbances and to identify bottlenecks. We distinguish three kinds of disruptions: (i) technical failure of main elements related to the production processes, (ii) issues resulting from an insufficient supply chain, and (iii) cascading disturbances. The implementation in a simulation environment and the processing of relevant input data are presented hereupon. The presented approach is then illustrated by means of an application example based on a completed metro project. Three extending simulation studies quantify the impact of the identified disturbance categories.