A study on factors affecting the wear of steel track undercarriage

Rich, Frederick A.; Shahhosseini, A. Mehran; Badar, M. Affan; Kluse, Christopher

doi:10.1108/jqme-10-2021-0081

Cited by 2 publications

(1 citation statement)

References 28 publications

(36 reference statements)

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“…Steel has an important position in the national economy [1] and is widely used in construction [2], machinery [3], railway tracks [4], ships [5], and other industries. However, ironmaking is one of the industries with high carbon emissions [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Distribution Behavior of Impurities during the Hydrogen Reduction Ironmaking Process

Wang,

Liu,

Zeng

et al. 2024

Metals

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The traditional blast furnace ironmaking process is the most widely used ironmaking process globally, yet it is associated with significant drawbacks, including high energy consumption and carbon emissions. To achieve low-carbon ironmaking, researchers have developed hydrogen ironmaking, which is capable of achieving lower CO2 emissions. Nevertheless, the distribution behavior of impurities has been less studied in the existing research on hydrogen ironmaking. Therefore, in this study, the factors affecting the slag properties and distribution of impurity elements during hydrogen ironmaking were investigated using FactSage, and smelting experiments were carried out. The results show that temperature has the greatest influence on the distribution behavior of the impurities, and excessively elevated temperatures result in the ingress of a significant quantity of impurities into the reduced iron. Reduced iron with a purity of 98.52% was obtained under the conditions of 10%, 10%, 2%, and 2% ratios of CaO, SiO2, MgO, and Al2O3, respectively, a hydrogen flow rate of 12 mL/min, and a temperature of 1400 °C; Lg L Mg, Lg L Al, Lg L Si, and Lg L Ca were 2.72, 2.41, 3.36, and 2.45, respectively (“L” stands for slag-to-metal ratio). The slag was mainly dominated by the silicate, and the iron was mainly lost in the form of mechanical inclusions in the slag. This study will enrich the basic theory of hydrogen ironmaking and is of great significance for the realization of carbon neutralization.

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Section: Introductionmentioning

confidence: 99%

Distribution Behavior of Impurities during the Hydrogen Reduction Ironmaking Process

Wang,

Liu,

Zeng

et al. 2024

Metals

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Operational excellence in total productive maintenance: statistical reliability as support for planned maintenance pillar

Mohad,

Gomes,

Tortorella

et al. 2024

IJQRM

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PurposeTotal productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.Design/methodology/approachIn this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.FindingsOur findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.Originality/valueIn terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.

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A study on factors affecting the wear of steel track undercarriage

Cited by 2 publications

References 28 publications

Distribution Behavior of Impurities during the Hydrogen Reduction Ironmaking Process

Distribution Behavior of Impurities during the Hydrogen Reduction Ironmaking Process

Operational excellence in total productive maintenance: statistical reliability as support for planned maintenance pillar

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