Contingency Plans for the Wood Supply Chain Based on Bottleneck and Queuing Time Analyses of a Discrete Event Simulation

Abstract

Wood supply chain performance suffers from risks intensified by more frequent and extreme natural calamities such as windstorms, bark beetle infestations, and ice-break treetops. In order to limit further damage and wood value loss after natural calamities, high volumes of salvage wood have to be rapidly transported out of the forest. In these cases, robust decision support and coordinated management strategies based on advanced contingency planning are needed. Consequently, this study introduces a contingency planning toolbox consisting of a discrete event simulation model setup for analyses on an operational level, strategies to cope with challenging business cases, as well as transport templates to analyze outcomes of decisions before real, costly, and long-lasting changes are made. The toolbox enables wood supply managers to develop contingency plans to prepare for increasing risk events and more frequent natural disturbances due to climate change. Crucial key performance indicators including truck to wagon ratios, truck and wagon utilization, worktime coordination, truck queuing times, terminal transhipment volume, and required stockyard are presented for varying delivery time, transport tonnage, and train pick-up scenarios. The strategy BEST FIT was proven to provide robust solutions which saves truck and train resources, as well as keeps transhipment volume on a high level and stockyard and queuing time on a low level. Permission granted for increased truck transport tonnages was evaluated as a potential means to reduce truck trips, if working times and train pick-ups are coordinated. Furthermore, the practical applicability for contingency planning is demonstrated by highly relevant business cases such as limited wagon or truck availability, defined delivery quota, terminal selection, queuing time reduction, or scheduled stock accumulation. Further research should focus on the modeling and management of log quality deterioration and the resulting wood value loss caused by challenging transport and storage conditions.

Simulating Combined Self-Loading Truck and Semitrailer Truck Transport in the Wood Supply Chain

“…The efficient maximum utilization level of 92% of the maximum terminal transshipment capacity for truck terminals is close to the value of 90%, which was indicated by sensitivity analyses for train terminals (i.e., BEST FIT strategy in [11]). Increasing the legal gross vehicle weight for timber transport from 44 t up to 50 t reduces the number of self-loading trucks needed in the truck terminal concept by 20% to 38%, depending on the scenario setting.…”

“…Increasing the legal gross vehicle weight for timber transport from 44 t up to 50 t reduces the number of self-loading trucks needed in the truck terminal concept by 20% to 38%, depending on the scenario setting. For a comparable increase in legal gross vehicle weight in a multimodal wood supply chain, a reduction in truck trips of 17% was reported [11].…”

“…Additionally, first contributions for multimodal wood supply chains [6][7][8] were listed and analyzed in a literature review focusing on wood transport [9]. Recent works provide a detailed discrete event simulation (DES) model for small train terminals [10], enabling short-term contingency planning [11] as well as knowledge transfer in game-based workshop designs [12].…”

“…Parameters for process times, weights, costs and working times are based on literature [10,11], case studies, expert interviews as well as applicable European and Austrian laws. In order to focus on mountainous regions, where space is usually limited, a small terminal with four transshipping lots, but no stockyard area, was selected from both industry experts and scientists to study the design of an multi-echelon unimodal wood supply chain, find an optimal truck fleet configuration and observe its performance.…”

“…Based on data for an appropriate case study [11], three different triangular distributions for short, medium and long driving times of self-loading trucks from forest landings to the terminal were defined. Payload scenarios cover the most relevant transport weight limit for self-loading trucks in Austria (maximum weight: 44 t, tare weight 20 t, payload 24 t) as well as an exceptional weight limit (maximum weight 50 t, tare weight 20 t, payload 30 t) partly granted by local authorities as an exemption clause after, e.g., massive windthrow with bark beetle hazard (i.e., for 50 t the transshipping time at the terminal was proportionally adjusted).…”