Private grain storage technology considerations and location optimization

Abstract

Farming operations looking to invest in private grain storage as a long-term investment to increase potential profits often face difficulty when deciding the best location to fulfill current storage needs and future expansion options. This thesis aims to combine the knowledge and desires of current farm operations to create optimization models for the optimal location for a private storage facility. Combining the use of technology and storage data in the precision agriculture realm allows agriculturalists to manage farm efficiency to better plan storage construction. Interviews were conducted with various farmers across the Midwest. Data was then accumulated on what factors of storage decision processes are most important as well as different types of technologies used in the agriculture industry. The operations varied in size, storage capabilities, technology implementation and storage expertise. All interviewees stated that technology was imperative in data management and grain monitorization in their farming processes. A concept farm was created to protect interviewee’s confidentiality. This creation was attainable using base knowledge gained through the interview process. The concept farm consisted of multi-year yield data as well as satellite imagery to show acreages and field boundaries. A 90/10 storage percentage of corn to soybeans was realized as well as three potential storage location options. A transportation minimization model was then created and solved to find the least time required for hauling to a potential storage facility. Furthermore, a cost minimization model was created to find which location had the least cost associated with infrastructure requirement and freight costs. Results indicated that through both model processes, out of a selection of three feasible sites, Location 1 is the desired location.