A Novel Approach to Identify Industrial Logistics Decarbonization Opportunities: Method Development and Preliminary Validation
Abstract
:Featured Application
Abstract
1. Introduction
2. Research Methodology
3. Theory Development
3.1. Selection of Decarbonization Measures
3.2. Inventory Management
3.3. The Developed Theory
4. The Methodology for the Proposition Validation
4.1. The Selection of Combined Road–Rail Transport as an Exemplary Decarbonization Measure
4.2. The Use of Discrete Event Simulation as the Evaluation Method
4.3. The Case Studies Investigated for the Theory Validation
- For competitive CRRT, the maximum number of transshipment operations during the main rail leg is set to one, i.e., no more than two rail services included in the main leg are allowed. The maximum allowed time for intermodal transportation is two days. To select the possible CRRT services, we search for the origin-destination pair on Routescanner.com (accessed on 11 September 2023) for each weekday and select the quickest connection that fulfils the requirements just mentioned. If there is no viable connection, we exclude the respective origin–destination pair from all scenarios. The rail services used are presented in the supplementary material.
- For pre- and post-haulage, we used the shortest possible routes from the suppliers to the origin terminal as well as from the destination terminal to the consignee. The distance and duration of these road haulages were acquired through the Openrouteservice.org (accessed on 11 September 2023) Distance API. We abstain from mentioning the precise addresses and distances due to confidentiality, but we can share that the average distances were 139 km and 169.5 km in the pre- and post-run for the first case, respectively, and 109.23 km and 193.82 km in the second case, respectively.
- The replenishment times differ between shipments from X, Y, and Z suppliers: X suppliers are given 7 calendar days replenishment time, Y shipments 5 days, and Z shipments 3 days. This reflects the predictability that is related to the different XYZ clusters. The replenishment time thereby determines how long before the planned arrival date the shipment is released by the supplier. For example, X suppliers are notified 7 calendar days in advance to send the shipment, either directly to the plant via road or to the first transshipment hub for intermediate storage.
- No further consolidation was considered. Shipment volumes and weights for intermodal shipments need to match the volumes and weights for the respective direct shipments that are given in the input data. It stands to reason that this is not the case with a real shift to rail as consolidation effects strengthen the business case for CRRT. However, we could not make any meaningful assumptions and would mix the evaluation with a second measure, which is why we decided against making any further assumptions on consolidation given the overall objective of the evaluation.
- To minimize cost, we aim to use 40-foot ISO containers. If the utilization of the 40-foot container is lower than 80% in terms of loading length, volume, or weight, we use 20-foot ISO containers instead. For competitive CRRT, each ILU utilization needs to be larger than or equal to 80%.
- Combining the former two assumptions led us to discuss how to handle shipments that have . Therefore, we introduced two dispatching modes for those shipments:
- In the first mode, we dispatch the whole shipment size to CRRT. This option constitutes the first shifting scenario, called “All ILUs on Rail” (ARA). In this scenario, the whole shipment, regardless of the shipment size, is dispatched to CRRT, meaning that one ILU is less utilized than 80%. This implies that some ILUs on rail are not well utilized, and the costs for renting, shipping, and handling the goods in this ILU are higher than for the better-utilized ones, but costs for direct road transport are obeyed. Before dispatching the ILUs via intermodal transportation, it is checked whether the ILU can reach the consignee on time with the available rail services. If this is not possible, the ILU is shipped directly by road transportation.
- This implies more cost for a low-utilized road transport. In this scenario, a minimum utilization of 80% is necessary for each load unit to be shipped via CRRT. If this utilization is not reached, the ILU is scheduled for direct road transportation. We call this scenario “Highly utilized ILUs on Rail” (URA).
4.4. Total Logistics Cost of Combined Road–Rail Transportation
- : The input data from case study 1 were used to consider costs for direct truck transport. As a result, we developed a regressive function that depends on the truck utilization to determine the freight charges per tonne-kilometre . Specifically,
- : To obtain pricing information for the main leg, we consulted the sales team at a railway operator for data related to a sample CRRT service. They provided us with a cost of 800 EUR for a single 60-foot wagon travelling an on-rail distance of 822 km and having a capacity of three 20-foot containers, which are commonly referred to as 20-foot equivalent units (TEU). Based on this information, we estimate the cost of transporting one 20-foot ILU per kilometre as:
- : Since actual road freight costs are included in the input data, the road is already included in the road freight charges.
- : As no data was available to us on the production delay, we initialized the simulation with:
- : In the first case, we cannot integrate in our evaluation due to the abundance of the shipment monetary values. For the second case, we compute the costs of capital by utilizing a literature-based interest of 12% from [62].
4.5. Distribution of Train Delay Times
5. Validation Results
5.1. Results of the ABC/XYZ Analysis
5.2. Results of the Simulation Study
6. Discussion, Implications, and Limitations
6.1. Implications for Practitioners from Simulating Combined Road–Rail Transportation
6.2. Implications for Practitioners from the Validation of the Approach
6.3. Limitations and Further Research Directions
7. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Appendix B
Appendix C
Kolmogorov–Smirnov a | Shapiro–Wilk | |||||
---|---|---|---|---|---|---|
Statistics | df | Sig | Statistics | df | Sig | |
abatement_cost_ara | 0.209 | 55 | <0.001 | 0.866 | 55 | <0.001 |
abatement_cost_ura | 0.267 | 32 | <0.001 | 0.776 | 32 | <0.001 |
abatement_cost_total | 0.229 | 87 | <0.001 | 0.852 | 87 | <0.001 |
Kruskal–Wallis | ||||
---|---|---|---|---|
Chi-Square | df | Sig | H | |
ARA | 38.429 | 5 | <0.001 | reject |
URA | 19.176 | 2 | <0.001 | reject |
Total | 58.644 | 5 | <0.001 | reject |
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Statement | References |
---|---|
Inventory management and its ABC/XYZ analysis are frequently applied in practice and well-researched | [16,34,35,37,38,39,40,41] |
Inventory categories impact the selection of inventory strategies | [16,35] |
Inventory strategies impact inventory cost | [16,35,43] |
Inventory costs impact total logistics cost | [44,45] |
Inventory strategies impact emissions | [46,47] |
Implementing lower-carbon transportation technology, modes, or practices impacts total logistics cost | [13,14,15,20,33,48,49,50] |
Selecting transport decarbonization measures on the product level can optimize total abatement cost | [37] |
Transportation abatement costs differ across inventory categories | This study |
Case 1 | Case 2 | |||
---|---|---|---|---|
Total | Considered | Total | Considered | |
Number of suppliers | 36 | 21 | 75 | 8 |
Number of products | n.a. | n.a. | 359 | 10 |
Number of shipments | 1215 | 275 | 1706 | 98 |
Shipment date range | February–December 2021 | February–May 2021 | January–December 2022 | January–December 2022 |
Transport GHG emissions | 548.51 t | 247.25 t | 305.60 t | 153.01 t |
Case 1 | Case 2 | |||
---|---|---|---|---|
Total Logistics Cost EUR | GHG Emissions t CO2e | Total Logistics Cost EUR | GHG Emissions t CO2e | |
ARO | 321,698.21 | 247.25 | 176,436.29 | 153.01 |
ARA | 304,060.61 | 222.59 | 159,717.17 | 120.31 |
URA | 308,854.52 | 224.32 | 166,241.26 | 131.04 |
Case 1 | Case 2 | ||||||
---|---|---|---|---|---|---|---|
X | Y | Z | X | Y | Z | ||
ARA | A | −874.99 | 15.21 | −891.09 | |||
B | −989.48 | −1169.40 | −1251.47 | ||||
n.a. | −1510.92 | −552.97 | −1411.41 | ||||
URA | A | −849.64 | −63.24 | −892.56 | |||
B | |||||||
n.a. | −1514.00 | −513.90 | 123.79 |
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Miklautsch-Breznik, P.; Hoffelner, M.; Woschank, M. A Novel Approach to Identify Industrial Logistics Decarbonization Opportunities: Method Development and Preliminary Validation. Appl. Sci. 2023, 13, 12277. https://doi.org/10.3390/app132212277
Miklautsch-Breznik P, Hoffelner M, Woschank M. A Novel Approach to Identify Industrial Logistics Decarbonization Opportunities: Method Development and Preliminary Validation. Applied Sciences. 2023; 13(22):12277. https://doi.org/10.3390/app132212277
Chicago/Turabian StyleMiklautsch-Breznik, Philipp, Mario Hoffelner, and Manuel Woschank. 2023. "A Novel Approach to Identify Industrial Logistics Decarbonization Opportunities: Method Development and Preliminary Validation" Applied Sciences 13, no. 22: 12277. https://doi.org/10.3390/app132212277
APA StyleMiklautsch-Breznik, P., Hoffelner, M., & Woschank, M. (2023). A Novel Approach to Identify Industrial Logistics Decarbonization Opportunities: Method Development and Preliminary Validation. Applied Sciences, 13(22), 12277. https://doi.org/10.3390/app132212277