Efficiency of combine usage: a study of combine data comparing operators and combines to maximize efficiency

Abstract

Farming is an important industry in the United States. The custom harvesting industry plays a major role in feeding the world. Schemper Harvesting is a family-owned and operated custom harvesting service that employs 20-25 seasonal workers and understanding how to manage a custom harvesting business professionally and efficiently is the key for its success. Today, there is data available through JDLink on John Deere combine performance beginning in year 2012. The purpose of this study is to examine the usefulness of this JDLink data to assess the efficiency of each of Schemper Harvesting’s seven combines, including machine efficiency and different combine operators. The goal is to determine how the data can improve Schemper Harvesting’s overall performance. Statistical methods were used to analyze Schemper Harvesting’s performance. The analysis indicated that fuel is a major expense and there are ways Schemper Harvesting can conserve fuel. This information may prove valuable in being able to operate a combine more efficiently and save money on expenses. Overall, the objective is to improve Schemper Harvesting’s performance, which results in higher profit without sacrificing quality. Precision technology is an added expense to the business. Being able to justify this expense with profit is the answer. Fuel, labor and machinery are the biggest inputs in the custom harvesting business. These costs related to production agriculture have increased the demand for precision agriculture to increase efficiency and profitability. In order to compensate for the investment in technology, it has been demonstrated that it pays for itself. Making correct use of precision technology adds to productivity. With experience, operators improve increasing their overall efficiency. Incentive plans can be utilized through this data. With the availability of data, the costs and benefits of precision technology can be further evaluated. Five of the seven combines are operated by family members and the other two by non-family employees. This study shows that the performance of the non-family employees was below that of family members. The initial assessment for this difference may be attributed to experience because all the family members have been operating combines for most of their lives. This implies that employing people with excellent performance experience records and/or a need to train non-family employees to help them understand the performance expectations at Schemper Harvesting. The results indicate that tracking operational output performance indicators, such as acreage and volume harvest should be completed so that they may be assessed in concert with the technical indicators such as time and fuel use. The study provides the potential benefits of using John Deere’s JDLink data service providing telematics information for its customers with the latest precision agriculture technologies.