Maintenance & Reliability
Imagine having the ability to tell if a motor or a bearing were about to fail just by looking at it. Over the past 5 years, a thermography program has proven to be a cost-effective means to inspect electrical and mechanical equipment to do just that. The hot mill at ArcelorMittal Burns Harbor has continued the use and expansion of thermography throughout the mill with great success. Several findings have led to significant savings in both downtime and equipment damage, and have proven that just one person with the right equipment and training can make a big difference.
In blast furnace operation, the blowpipe that delivers hot blast air is constantly operated and undergoes wear in a high-temperature and high-pressure environment. Computational fluid dynamics (CFD) is used to simulate the flow pattern of hot blast air and heat transfer in a blowpipe. The information generated from CFD simulation is used to provide input conditions for mechanical simulation of thermal stress. Areas of failure corresponding to high stresses and plastic strain are identified. In this investigation, a parametric study is carried out to help optimize blowpipe design. The study findings can be used as guidelines for new blowpipe design, with reduced failure and better reliability.
The main reduction gears at the hot strip mill have been damaged after long operation. At times the fatigue safety factor of the tooth surface at peak torque is less than 1.0, and damage of the tooth surface such as gear pitting and spalling progresses. In this paper, a new residual bending fatigue life evaluation considering the effect of a valid gear’s tooth width reduced by the damage is proposed. By this method, the estimated fatigue life is much less than that of a general method, resulting in the damaged gears being able to be replaced before a serious accident could occur.
Level 2 automation systems play a critical role in almost all process industries. Traditional methods for maintaining level 2 systems are human-centric operations. Such methods increase the possibility of human mistakes as a result of routine actions that may lead to plant downtime. This paper introduces a new approach for automatic monitoring and proactive maintenance of level 2 automation systems based on the e-Maintenance ontology. A prototype is presented such that many components of level 2 systems can be monitored against pre-defined thresholds. The prototype can be dynamically customized to fit the needs for maintenance to be used either only for warning or for taking certain corrective actions. As a proof of concept, the approach is supported by an empirical evaluation after applying it in EZDK plants in Egypt.
Traditional methods of determining fluid health under operating conditions involve sample collection and laboratory analysis, a time-consuming process. Further, contamination introduced during fluid sampling can erroneously raise alarms or mask underlying issues. A robust fluid and filter monitoring platform utilizing the latest in sensor and electronics technology can be harnessed to overcome these limitations. Further, sensor data can be relayed wirelessly to a secure cloud-based location, allowing dynamic algorithms to predict key properties. An in-line monitoring technology coupled with cloud-based architecture is a powerful tool that will allow predictive decisions to be made in a timely manner.
A mathematical model has been developed to investigate fluid flow and heat transfer phenomena in the ladle shroud during transfer of molten steel from the ladle to the tundish. The model embodies finite thermal contact resistance between the liquid steel and the shroud refractory, which has been deduced directly from plant-scale measurements of the shroud surface temperature, embodying relevant heat flow theory. It is shown that thermal contact resistance between the melt and refractory is appreciable, is dependent on grade of steel and is significantly higher than the combined resistances offered by shroud refractory and the thermal boundary layer. In this work, plant-scale operating data were incorporated to formulate appropriate thermal and velocity boundary conditions. Embodying such in a coupled, turbulent fluid flow and heat transfer model, thermal fields in the conjugate domain (i.e., melt + shroud) have been numerically predicted via the ANSYS-CFX commercial software. Numerical predictions indicate a ~2°C drop in melt temperature between the ladle and tundish during continuous bloom casting, as molten steel is transferred through a 1,200-mm-long immersed shroud. To validate such findings, shroud wall temperatures during continuous bloom casting were measured in two different special steel plants and compared directly with corresponding numerical predictions. Close agreement between the two is demonstrated.