Effektivisering av interna transporter

Sammanfattning

Cramo Region Mitt operates three tour trucks to transport machines between depots. This helps balance the machine stock and meet customer demand, but it also involves high costs and challenges. One particular challenge is that customers can return machines to any depot, which creates imbalances and increases the need for internal transportation. At the same time, the third truck is only used twice a week to cover hard-to-reach areas, raising questions about its cost-effectiveness. The objective of this study is to analyze and evaluate Cramo's internal transport flows within the Central Region, aiming to propose measures that minimize unnecessary transport and optimize resource usage. By analyzing the transport data for 2024, the most frequently moved machines have been identified and used as a basis for an ABC classification. The findings indicate that certain machine types represent a significant portion of transportation, thereby greatly influencing costs and logistics. Primary data was collected through surveys and semi-structured interviews with depot staff, managers, and suppliers, providing insights into practical challenges such as a lack of coordination, imbalances between depots, and unclear planning. The survey responses confirm that unnecessary transportation occurs, partly due to a lack of oversight and internal communication. A digital transport management system (TMS), improved machine distribution, investment in more machines, and the introduction of clear procedures were identified as potential solutions. The study indicates that by concentrating on high-frequency transport machines and implementing more advanced planning tools, Cramo can decrease costs and environmental impact while also enhancing the availability of the right machine in the right place at the right time. Further implementation necessitates collaboration from Cramo's internal logistics and operations teams, particularly in areas such as machine coordination and the establishment of routines for measuring and monitoring key metrics, including transport frequency and the number of transports involving A-rated machines.