Mechanized tunneling is one of the most common methods used for underground constructions for infrastructure systems. Since a tunnel boring machine (TBM) represents a non-redundant single machine system, the efficiency of maintenance work highly impacts the overall project performance. The wear and tear of cutting tools is a critical, but mostly unknown process. To plan the maintenance work of cutting tools efficiently, it is necessary to know the current tool conditions and adapt the planned maintenance strategies to the actual status accordingly. In this paper, an existing theoretical empiric surrogate model to describe cutting tool conditions will be used and implemented as a software component within a process simulation tool that manages TBM steering parameters. Further, different maintenance setups for TBM cutting tools are presented and evaluated. To prove the capability of the presented approach, a case study will show the effects that improved maintenance work can have on project performance.
To comply with the constantly increasing requirements on the performance of infrastructure systems in urban areas, mechanized tunneling is one of the most common construction techniques for underground structures. The main advantage of using tunnel boring machines (TBMs) in subsurface construction projects is a generally high production performance by simultaneously minimizing disruption of existing surface structures and infrastructure systems. However, tunneling projects must always deal with many individual project specifications (e.g., the tunnel diameter or the available storage space) and uncertain or varying boundary conditions (e.g., ground conditions or process durations). Thus, mechanized tunneling projects are characterized as highly complex systems with sensitive process interactions and process dependencies (Maidl et al. 2012).
Each project setup and TBM design is unique and must be adjusted to the special project demands. A prediction of the TBM performance is indispensable for the project planning but, due to unknown project conditions, still a challenging task. For this reason, in many projects the given project performance does not match the planned project performance (Osborne et al. 2013). The production performance rate depends highly on the actual machine condition and, thus, is related to the quality of the maintenance work. Due to the comparatively long duration of the maintenance processes, detailed knowledge of the current condition of the TBM cutting tools is of crucial importance to achieve a high performance rate. Poorly planned maintenance strategies of the TBM cutting tools can also lead to lower advance rates and a decreased project performance. However, in general the planning of maintenance work is currently based mainly on experience or simplified static dimensioning (Kohler, Maidl, and Martak 2011).
Wear and tear of the TBM cutting tools are highly related to the prevailing ground conditions (including earth pressure and abrasiveness) and machine steering parameters such as the face support pressure or the cutting wheel penetration rate. The wearing processes of cutting tools operating in hard rock conditions have been a strongly focused topic of researchers in the last few years (e.g., Wu et al. (2010); Schneider, Thuro, and Galler (2012); Wang et al. (2012)). Up to now, for soft ground conditions only few approaches predicting the wearing process of TBM cutting tools exist. As a consequence, for most projects in soft ground conditions periodic maintenance strategies based on pre-scheduled maintenance stops are applied. As a well-known fact, periodic maintenance ignores the current machine condition and can lead to undesirable and avoidable loss of production performance. A condition- based preventive maintenance strategy promises a greater efficiency of maintenance work and, consequently, a reduction of the project duration and potential costs for spare parts.
This paper shows the implementation of an empirical approach to forecast the condition of cutting tools of TBMs operating in soft ground conditions by creating a software component that is integrated within a simulation model. Varying ground conditions as well as different maintenance strategies are taken into account. The generated simulation model is used to optimize maintenance schedules for TBMs by varying maintenance parameters like the minimum average cutting tool condition. This generally leads to more efficient and robust maintenance schedules and can help improve the overall project performance.
A simulation model representing production processes of TBMs and concerning the continuous wear of the TBM cutting tools promises significant improvements in the planning of maintenance works (Mattern et al. 2016). Thus, a multi-method simulation model has been developed, combining both aspects and enabling the evaluation of different maintenance strategies under varying boundary condition.
Implemented Simulation Model in AnyLogic