Use of StanForD2010 data for determination of effect of harvester operator periodic training on productivity and fuel economy
2021
Strubergs, A., Latvia Univ. of Life Sciences and Technologies, Jelgava (Latvia) | Lazdins, A., Latvian State Forest Research Inst. Silava, Salaspils (Latvia) | Sisenis, L., Latvia Univ. of Life Sciences and Technologies, Jelgava (Latvia)
The aim of the study is to clarify the effectiveness of operator qualification improvement courses through the analysis of harvester production data acquired according to the StanForD2010 standard. The study demonstrated that regular training of operators is used by AS “Latvian State Forests” (LSF) logging service providers; in turn, companies providing harvesting services in private forests pay much less attention to the periodic training of operators. The study uses automatically harvester production data acquired according to StanForD 2010 standard by LSF service providers. The study found that the most of the companies do not use the automatically acquired data of the harvester information system and their in-depth analysis capabilities through the grouping and analysis of each work cycle operation for evaluation of operators’ productivity and for identification of operations where a particular operator should improve his skills. Second, the analysis of automatically acquired data enabled accurate detection of operations that significantly affected the changes in harvester fuel consumption before and after the qualification improvement courses. The study analyses data from two operators over a two months period prior to training and within a period of two months after training. The study approved that the harvester production files can be used for detailed evaluation of the training impact and demonstrated that after training both operators decreased the time consumed for stem gripping and processing on average by 5% and 16%, specifically demonstrating those operations where productivity increased. The harvester production data also can be used to demonstrate the impact of fuel consumption, in this case training led to decrease fuel consumption per produced unit by 8% and 4%. TimberOffice software was used for data grouping, while Microsoft Excel was used for data analysis.
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