Analysis of field machinery performance based on daily soil workability status using discrete event simulation or on average workday probability

The objective of the study was to develop a simulation model for field machinery operations using a discrete event simulation technique in order to analyse machinery performance based on daily status of soil workability for a series of years (Daily Work. method), and to compare the results with those from a simpler method based on average probability values of available workdays for operations and seasons (Aver. Work. method). Timeliness costs with this latter method were estimated using the formula proposed by ASAE Standards, ASAE EP496.2 DEC99. Seven machinery sets were assessed on a 400 ha farm with both methods in terms of total costs (labour+specific machinery+timeliness costs) to find the effect of the methods on assessment of timeliness costs. The model for field machinery operations was developed in the Arena simulation language, allowing simulation of field operations on a real farm for a 20-year period. Completion dates of operations in individual fields were important outputs of the model, which enabled timeliness costs to be estimated in detail. Daily soil workability was inferred by means of moisture thresholds from simulated soil moisture contents from another model (the SOIL-model) and weather data from Uppsala, Sweden. The validity of the machinery model was tested with data from a farm, the daily results of the model had good agreement with the progress of the field operations at the real farm. The assessment of the seven machinery sets revealed that machinery costs were the main component of total costs and, as expected, they increased with machine size. Labour costs and timeliness costs decreased as machine size increased with both methods. The Aver. Work. method estimates resulted in lower timeliness costs for sowing operations than those determined with the Daily Work. method, which was attributed to the fact that former method did not take into account chain effects. Regarding timeliness costs for harvesting operations, the Aver. Work. method was considered inappropriate because of scattered field maturity times in the region of the study where single periods with their own optimum time are difficult to identify. In addition, the ASAE formula was very sensitive to the number of such periods. In contrast, timeliness costs with the Daily Work. method were estimated for sowing and harvesting operations taking into account some management criteria and chain effects were captured on a field basis. They were quantified for sowing and harvesting operations based on a long-term assessment (20 years) and their yearly variability was determined.