Abstract

Sugarcane, as an important industrial crop, is always considered as one of the strategic commodity and supported by governments. One of the most important repairable systems in agro-industrial companies is a sugarcane harvester machine. The failures of this machine cause a delay in operations and reduce product yield and quality. This machine has a key role in sugarcane harvesting operations of the agro-industries. Availability of sugarcane harvester machine was determined by using the Markov chain method which is a robust probabilistic method according to the actual conditions of the sugarcane harvesting system in the agro-industries. The methodology outlined in this study has been utilized to 12 sugarcane harvester machines, namely CASE IH Austoft 7000. According to the results, harvesting system availability was calculated as 87.5%, 86.4%, 95.3%, and 90.4% for the first, second, third, and fourth harvesting groups, respectively. For these groups, the down probability of the system is evaluated to be 12.5%, 13.6%, 4.7%, and 9.6%, respectively. On average, the down probability was 10.1%, meaning that the machine will not be available at 10.1% of days at harvesting season. Due to the high sensitivity of the crop that delayed harvesting, agro-industry managers should try to reduce this amount by increasing system reliability and optimizing planned maintenance activities to decrease scheduled downs that have a direct effect on harvest time.

Full Text
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