A manufacturing company discovered that their raw material was losing weight while being transported. This raw material is the primary raw material used in the production of animal feed and is known as soybean meal (SBM). It was hypothesised that the weather and the length of the trip had an impact on the weight reduction. Time series clustering will be used to demonstrate this claim. Time series clustering will be used to create multiple distinc clusters, each with a unique pattern and value, using Euclidean distance as the distance measurement. The background of these clusters will then be investigated, taking weather and duration characteristics into account. Subsequently, it was shown that the high humidity and extended travel time were to blame for the weight loss that occured during the procses. Given that the port-to-factory duration is beyond the company's control, it should be able to expedite the scaling process.