Multimodal strategies for greener and more resilient wood supply

The objective of MultiStrat was to establish an integrated framework for testing multimodal strategies for greener and more resilient wood supply, delivered as supply chain simulation models enabling participatory evaluation and implementation of results. The work was structured in 3 work packages: WP1 Supply chain mapping, WP2 Supply operations analysis and WP3 Supply chain modeling and evaluation. The project spanned 3 climate zones; continental (Austria with rail transport), sub-arctic (Sweden with rail transport) and oceanic (Norway with sea transport). WP1 Supply chain mapping. In a supply chain context, resilience represents the ability to sustain supply in the face of disruptions. This work package started therefore with mapping of disruptions for all three regional cases as well as the management processes which respond to these. The agility required of the organization to meet these disruptions typical was generally reflected by the frequency of management control and planning cycles and their time horizons. WP2 Supply operations analysis. Given the variation in conditions between regions, this work package started with developing a common framework for analysis of organization-level variation in harvesting production and transport. The final framework enabled presentation of multi-year time series with relative weekly production and transport pace (% of annual average) with the corresponding weekly temperature, precipitation and snowdepth. The differences between production and transport pace determine the time spent in roadside stocks before and the typical lead times for the respective regions varied accordingly. In the Austrian case, direct loading from truck to block-train solutions caused a maximum 5 day prolongation of the lead time between harvesting and mill. In the Norwegian case, the time for vessel cargo accumulation) caused an 2,5 weeks prolongation of lead time, on average. WP3 Supply chain modeling and evaluation. This work package focused on developing supply chain simulation models. The Austrian work continued with a simulation study for quantifying the effect of fixed levels of multimodal transport on system KPIs. The Swedish work focused on further simulation studies of lead times for direct and multimodal transport (system-train solution). The Norwegian work focused on development of demonstration modules for testing management alternatives over the whole supply geography. The first (supply chain demo I) provides weekly visualization of the geographical distribution of production and transport. The second (supply chain demo II) provided an optimization tool based on the same graphical interface, used for testing and visualizing the effect of vessel strategies within the seasonal trends mapped in WP2. Compared to truck transport alone, the Austrian results showed a 6 % reduction of C02 emissions and 29 % reduction of lead times from forest to mill for the current block-train solution. The reduction of lead times for multimodal solutions increased to 54 % for the increased wood flows after wind storms. The Swedish results show that the simulated lead times for truck transport varied between 11-43 days. These increased to 50 days from forest to pulpmill via the system-train solution. Regarding tools for working at the organization-level, the Norwegian results provided optimal truck/vessel solutions for pulpwood deliveries throughout the yearly cycle. The optimal proportion of vessel use followed the same seasonal pattern as provided by transport statistics in WP2, but with a slightly lower overall level. The optimal solutions enabled access to a wide variety of geographies with minimal variation in sum transport system costs. Synthesis. In all three regions, multimodal systems provide a robust base level of transport capacity ensuring stable deliveries from terminal stocks regardless of varying operating conditions. However, given that variation in production pace was greater than for transport pace, the bottleneck for improved supply chain performance was therefore production strategy. The simulated re-scheduling of production based on weather-based modeling of weekly bearing capacity presented a plausible alternative for reducing variation from the head of the value chain. The experiment provided a simple demonstration of the potential for improved resilience through an adaptive management response. Following this direction of development enables further exploitation of the structural flexibility inherent to multimodal solutions. Improved supply chain coordination between production and transport provides better control over lead times and freshness. This translates directly to lower costs and higher product value; with direct impacts for competitive advantage.

The Norwegian host organization was a well functioning multimodal system, as shown in the results. The bottleneck for further development of the supply chain, however, is identified as planning horizon for harvesting production planning. Continuation of this work has been initiated in a coming proposal (via ARENA-Skog). For the Austrian host organization, a bottleneck for further development is identified as terminal layout and transhipment practices, and new strategies are under development. For all three regions (Austria, Sweden, Norway) seasonal variations were tracked and consequences for roundwood lead-times mapped. Continuation of this work has been initiated in a coming proposal (via Era-Net Forest Value).

While seasonal mill consumption is often constant, seasonal irregularities and risks in wood harvest and transport are significant challenges for wood supply management in many regions of Europe. Given the wide variety of market, infrastructure, and climate conditions between regions, there is a need for an integrated framework for modeling and analysis of efficiency and resilience to supply chain risks. At the same time, increasing occurrences of natural disturbances such as windstorms require an increased buffer capacity. In this context, innovative multimodal systems via rail and sea terminals offer the potential to increase buffer capacity and reduce fossil fuel emissions. The research approach starts with a broad initial mapping to establish common frameworks for regional analyses of supply operations which then quantify parameters for the integrated supply chain simulation model. The project has three work packages. These include: WP1. Supply chain mapping; focusing on mapping typical supply chain disruption patterns, system elements and management processes for multimodal roundwood transport. WP2. Supply operations analysis; focusing on developing a common framework for analysis of organization-level irregularities in harvesting production and multimodal transport, as well as the driving factors behind these irregularities. WP3. Supply chain modeling and participatory evaluation; focusing on developing a supply chain simulation model for testing multimodal innovations with a participatory evaluation of strategies to cope with supply chain risks. In addition to a comprehensive cataloging of regional challenges and multimodal system capacities and management processes, the key deliverable from the project is a new virtual environment enabling manager involvement in testing, analysis and evaluation of relatively complex multimodal systems.