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Key research themes
1. How can Overall Equipment Effectiveness (OEE) be modeled and optimized to improve machinery operational efficiency?
This research area focuses on the use, enhancement, and optimization of Overall Equipment Effectiveness (OEE) models to assess and improve the operational efficiency of machines and production systems in industrial settings. It investigates both theoretical and applied aspects, including modeling approaches, vector calculus applications, genetic algorithm optimizations, and practical assessments in manufacturing environments. OEE remains a key metric aggregating availability, performance, and quality to identify losses and guide maintenance and productivity improvements.
Key finding: Introduces a novel geometric and vectored approach to model OEE by representing the three component measures (availability, performance, quality) as interrelated vectors, allowing calculation of tensor and gradient measures.... Read more
Key finding: Demonstrates that among OEE parameters, performance rate has the largest impact on overall effectiveness in a manufacturing system. Using genetic algorithms to optimize availability, performance, and quality rates, the study... Read more
Key finding: Empirically shows that average machine effectiveness in tool and die shops does not reach the ideal >85% OEE benchmark due to excessive downtime and speed losses. It recommends maintaining constant operational speed and... Read more
Key finding: Applies Total Productive Maintenance (TPM) pillars such as Kaizen to improve OEE in a spinning mill’s ring frame section. The study identifies machine downtime and quality losses as key detractors from OEE and demonstrates... Read more
Key finding: Investigates OEE components (availability, performance, quality) in a packaging manufacturing context, observing that machine availability improved by 5% over world standard, while performance and quality rates decreased by... Read more
2. How can motor efficiency be accurately modeled and assessed under variable speed and partial load conditions?
Accurate estimation and modeling of motor efficiency during variable speed and partial load operations is crucial due to the widespread use of motors in industrial settings with variable frequency drives. Research in this theme addresses the challenges in capturing efficiency variations as functions of load ratio, speed ratio, and loss components while considering limitations of traditional nameplate data. Methodological contributions include load ratio concepts, experimental validations, and efficiency mapping for design and operational optimization.
Key finding: Proposes a gray-box model utilizing load and speed ratios to estimate motor efficiency accurately under variable speed and partial load conditions, achieving relative errors within ±5% for full-speed partial load and within... Read more
Key finding: Develops a theoretical and practical framework to compute and model efficiency maps of electric machines based on torque and speed, employing finite-element analysis of losses and representing power losses as terms of torque... Read more
Key finding: Demonstrates that feasibility assessments of replacing standard efficiency motors with high-efficiency ones must incorporate actual operating conditions including measured load factors and operating times. Scenarios assuming... Read more
Key finding: Analyzes motor efficiency variability, emphasizing that nominal efficiency values have defined tolerances influenced by motor design, manufacturing, testing, and operational factors such as winding losses, core losses,... Read more
Key finding: Presents a mathematical control optimization approach based on Euler-Lagrange methods to minimize energy consumption in electro-mechanical drive systems, such as electric motors under load. The study formulates and solves... Read more
3. How is machinery efficiency quantified and optimized in agricultural operations considering energy, economic, and environmental factors?
This theme investigates the quantification and optimization of machinery efficiency in agriculture by integrating energy consumption metrics, operational productivity, equipment sizing, and environmental impacts such as soil compaction. It uses mathematical modeling, system analysis, and computational experiments to assess tractor and implement parameters, determine optimal fleet size to minimize energy and crop loss, and evaluate sustainability through life cycle and energy efficiency considerations.
Key finding: Develops mathematical models based on system analysis identifying optimal tractor weight and engine power ratios for varying technological operations grouped by energy consumption intensity. The study shows that distinct... Read more
Key finding: Utilizes energy mathematical models to determine an optimal number of tractors required for field operations over 1000 hectares to minimize total energy costs, including manufacturing, operation, maintenance energy, and yield... Read more
Key finding: Presents methodologies for quantifying agricultural machine efficiency focusing on thermodynamic efficiency as the ratio of output to input energy. Discusses measurement systems for motor efficiency via mechanical... Read more
Key finding: Introduces comprehensive life cycle efficiency models integrating energy, economic, and ecological benefits and costs for machinery such as wind farms, emphasizing construction, operation, and maintenance. The models assess... Read more
Key finding: Through experimental and regression modeling of cutting forces in turning operations under eco-friendly minimum quantity cooling lubrication (MQCL), identifies strong relationships between machining parameters, energy... Read more