# Material Flow Optimization as a Tool for Improving Logistics Processes in the Company
## 6 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**From** & **To** & **Ton/Year** & **Frequency/Year** & **Distance** & **Performance** & **m/Year** & **Handling Costs** \\ \hline Recipid of primary packaging & Primary packaging & & & & & & & \\ materials (PM) & warehouse (PM) & 504 & 2016 & 40 & 20,160 & 80,640 & 755.19 \\ Recipot of secondary packaging & Secondary packaging materials & & 4719 & 7080 & 20 & 94,380 & 141,600 & 1326.13 \\  & warehouse (PM) & & & & & & & \\ Receipt of raw materials (RM) & Raw materials warehouse (RM) & 47,634 & 127,024 & 10 & 476,340 & 1,270,240 & 11,896.02 \\ Raw materials warehouse (RM) & section 1 & 47,634 & 127,024 & 20 & 952,680 & 2,540,480 & 23,792.09 \\  & section 1 & Production lines & 47,634 & 63,512 & 20 & 952,680 & 1,270,200 & 11,896.02 \\ Primary packaging materials & & Production lines & 476 & 1904 & 20 & 9520 & 38,080 & 356.64 \\  & & Output from lines & 48,110 & 347 & 100 & 4,811,000 & 24,700 & 324.97 \\ Output from lines & Semi-finished goods & & 48,110 & 962,220 & 5 & 240,550 & 481,100 & 4505.60 \\ Semi-finished goods & & warehouse (SF) & & & & & & \\  & & Fruta & 48,110 & 3123 & 2000 & 96,220,000 & 6,246,000 & 58,494.95 \\  & Fruta & Packaging & 48,110 & 3470 & 2000 & 96,220,000 & 6,940,000 & 64,994.38 \\ Secondary packaging materials & & Packaging & 4461 & 2230 & 50 & 223,050 & 111,500 & 1044.23 \\  & Packaging & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & \\  & & & & & & & & \\  & & & & & &The savings per transport to Tabor amount to 8.06 EUR, while for Lasek, they amount to EUR 1.12. This results in potential annual savings of EUR 17,547.40. Despite the relatively low annual savings, variable material flow costs were reduced by EUR 150,916.84. However, due to the high investment costs and low operational profit, ROI was calculated at \(-91\%\), with a payback period of 11.5 years. From this perspective, this variant is deemed unfeasible, as it does not meet the required investment return conditions. While both optimization variants present potential cost savings, their implementation faces several practical challenges. One of the main obstacles in Variant 2 is the high initial investment required to acquire an internal fleet, along with its ongoing operational and maintenance costs. Additionally, the risk of investment return remains a key concern, as the calculations indicate that while Variant 1 meets the expected payback period, Variant 2 significantly exceeds it, making it financially unviable. A critical challenge is the organizational transition from an externally managed transport system to an in-house model. This shift would require substantial logistical adjustments, including personnel training, maintenance planning, and fleet management. Moreover, internal transport dependence introduces new operational risks, such as vehicle downtime or scheduling conflicts, which must be mitigated through efficient fleet utilization strategies. To address these issues, a phased implementation approach could distribute investment costs over time while allowing performance evaluation before full-scale adoption. Alternatively, a hybrid transport model, combining both internal and external logistics services, may offer a balanced solution between cost control and operational flexibility. Implementing real-time monitoring technologies, such as IoT-based fleet tracking and route optimization algorithms, could further enhance transport efficiency and reduce unnecessary costs. From an environmental sustainability perspective, optimizing material flows contributes to lower emissions and reduced energy consumption. By minimizing transport distances and adopting fuel-efficient transport methods, Variant 1 aligns better with sustainable logistics principles. If internal transport units were powered by alternative energy sources, such as electric or hybrid vehicles, the overall carbon footprint of logistics operations could be further minimized.