Performance comparison between workshop-based and laboratory-based condition monitoring systems for operational and economic performances of sugarcane harvesting

• Workshop-based monitoring showed significantly higher machinery uptime and efficiency. • The cost per sample in the workshop-based system ($1.52) was approximately 25.98 times lower than in the laboratory-based system ($39.45). • The response time in the workshop-based system (90–120 min) was significantly shorter than in the laboratory-based system (1–8 weeks). • Laboratory-based monitoring provided more detailed and standardized analyses but at a higher cost and longer processing time. • The study highlights the trade-offs between cost-effectiveness and analytical accuracy in condition monitoring of sugarcane harvesting machinery. Effective management of machinery operation, maintenance, and condition monitoring is essential for optimizing performance and minimizing costs. This study compares different Oil Condition Monitoring (OCM) methods in sugarcane harvesting machinery using analysis of variance (ANOVA) to assess technical performance and operational costs. Focusing on Khuzestan Province, Iran's primary sugarcane cultivation hub, a comparative analysis was conducted in the "Dehkhoda" and "Debel Khazai" agro-industrial complexes. Analysis of variance (ANOVA) revealed highly statistically significant differences in the performance (annual effective operating hours) of sugarcane harvesting machines across different years ( p < 0.01). The annual effective operating hours in the third year were significantly higher than in the preceding two years. Notably, in 2023, the highest recorded operational hours (1290 h) were achieved under the workshop-based monitoring system, demonstrating marked improvement. This finding indicates that the workshop-based system significantly outperformed the laboratory-based system in enhancing machinery uptime and efficiency. The cost per sample in the workshop-based system was $1.52, whereas in the laboratory-based system, it was significantly higher at $39.45, making it 25.98 times more expensive. Additionally, the laboratory-based system's feedback time ranged from one to eight weeks, while the workshop-based system provided results within 90 to 120 min. Although the laboratory-based system ensured higher accuracy and adherence to scientific standards, the workshop-based system demonstrated notable economic and operational advantages. These findings highlight the trade-off between rapid, cost-effective monitoring and comprehensive, standardized analysis. The integration of workshop efficiency with laboratory accuracy can optimize machine performance in future harvesting seasons, especially under constrained conditions.

Authors

Publication Details

Journal
Results in Engineering
Published
2025-04-14
DOI
https://doi.org/10.1016/j.rineng.2025.104937
Citations
1
Primary Topic
Sugarcane Cultivation and Processing
Type
article
Field-Weighted Citation Impact
1.75
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article

Performance comparison between workshop-based and laboratory-based condition monitoring systems for operational and economic performances of sugarcane harvesting

Mahmoud Ghasemi-Nejad-Raeini, Afshin Marzban, Majid Rahnama, Rasol Abedini
1 citations
Results in Engineering
Sugarcane Cultivation and Processing
1.75
article

Performance comparison between workshop-based and laboratory-based condition monitoring systems for operational and economic performances of sugarcane harvesting

Mahmoud Ghasemi-Nejad-Raeini, Afshin Marzban, Majid Rahnama, Rasol Abedini
article en
1 citations

Abstract

• Workshop-based monitoring showed significantly higher machinery uptime and efficiency. • The cost per sample in the workshop-based system ($1.52) was approximately 25.98 times lower than in the laboratory-based system ($39.45). • The response time in the workshop-based system (90–120 min) was significantly shorter than in the laboratory-based system (1–8 weeks). • Laboratory-based monitoring provided more detailed and standardized analyses but at a higher cost and longer processing time. • The study highlights the trade-offs between cost-effectiveness and analytical accuracy in condition monitoring of sugarcane harvesting machinery. Effective management of machinery operation, maintenance, and condition monitoring is essential for optimizing performance and minimizing costs. This study compares different Oil Condition Monitoring (OCM) methods in sugarcane harvesting machinery using analysis of variance (ANOVA) to assess technical performance and operational costs. Focusing on Khuzestan Province, Iran's primary sugarcane cultivation hub, a comparative analysis was conducted in the "Dehkhoda" and "Debel Khazai" agro-industrial complexes. Analysis of variance (ANOVA) revealed highly statistically significant differences in the performance (annual effective operating hours) of sugarcane harvesting machines across different years ( p < 0.01). The annual effective operating hours in the third year were significantly higher than in the preceding two years. Notably, in 2023, the highest recorded operational hours (1290 h) were achieved under the workshop-based monitoring system, demonstrating marked improvement. This finding indicates that the workshop-based system significantly outperformed the laboratory-based system in enhancing machinery uptime and efficiency. The cost per sample in the workshop-based system was $1.52, whereas in the laboratory-based system, it was significantly higher at $39.45, making it 25.98 times more expensive. Additionally, the laboratory-based system's feedback time ranged from one to eight weeks, while the workshop-based system provided results within 90 to 120 min. Although the laboratory-based system ensured higher accuracy and adherence to scientific standards, the workshop-based system demonstrated notable economic and operational advantages. These findings highlight the trade-off between rapid, cost-effective monitoring and comprehensive, standardized analysis. The integration of workshop efficiency with laboratory accuracy can optimize machine performance in future harvesting seasons, especially under constrained conditions.

Results in EngineeringVol. 26
Zero hunger
Openalex Percentile: Top 16%
Sugarcane Cultivation and Processing
1.75
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