Modelling of material handling operations using controlled traffic

Controlled-traffic farming (CTF) is a management system that can eliminate soil compaction by wheels within the cropped area. According to the principles of CTF, permanent parallel wheel tracks are created within the field area. The benefits of CTF, in terms of productivity and sustainability, have been the subject of intensive research for a number of decades. This has led to the establishment of CTF in various regions around the world. CTF also has drawbacks that include the need to purchase specialised machinery, the loss of cropped area due to dedicated wheel tracks and the cost of creating and maintaining permanent traffic lanes within the fields. Furthermore, field efficiency is affected by CTF due to significant increases in idle time of in-field transport and the way the fields are traversed in material handling operations. During fertilisation, when tramline length and the driving distance needed to apply one tanker load of fertiliser are not coordinated, CTF does not allow for random turns and requires the tanker to drive empty along the traffic path. The inherent characteristics of the CTF system, as well as the fact that cooperatively owned machines are used to carry out the operations, makes existing models inadequate for evaluating field efficiency. In this paper, the development of a discrete-event model for the prediction of travelled distances of a machine operating in material handling operations using the concept of CTF is presented. The model is based on the mathematical formulation of the discrete events regarding the motion of the machine when performing the fieldwork pattern. To evaluate the model two slurry application experiments were designed. The experiments involved registering the position and monitoring the application status of the slurry applicator. Validation showed that the model could adequately predict the motion pattern of machinery operating in CTF. Prediction errors of total distance travelled, were 0.24% and 1.41% for the 2 experimental setups. The current model structure captures the interrelationships between the mutual influencing parameters of motion sequence and configurations of the CTF layout. This model has the potential to be used for autonomous vehicles.