This case is about a century-old integrated steel plant combined with mines, having more than 0.42 million capitalintensive assets, ages ranging from 0 to 100 years and spreads across 700+ hectares as shown in Figure 1. Assets having varied levels of automation maturity with different maintenance methodologies. It’s about shifting the whole maintenance paradigm from Time-based & Condition-based to Predictive. Through digital initiatives & optimum maintenance cost, we are trying to develop a Maintenance Transformation Roadmap (MTR) to ensure maximum machine availability/ reliability. For this paradigm shift from conventional to predictive maintenance, critical assets were identified through a systematic approach. Under this MTR Journey, to bridge the sensor gap, SMART Sensor (3 axis vibration & Temperature) was identified as the appropriate solution. Customizable In-house SMART Sensor applicable in Mining & Steel industry application and low-cost solution helped in cross locational horizontal. Presently early warning alerts saved 1000+ potential breakdowns on 1200nos critical assets. The Predictive Maintenance Framework has both tangible and intangible benefits. While safety is the most important intangible benefit of this technology, tangible benefits include approved savings of $20 Million. Further, we expect to save $12.5 Million by deploying our Sensor and $35 Million via prevention of breakdowns
{"title":"IoT Enabled Condition Monitoring Under Predictive Maintenance Framework of Mines and Steel Plant","authors":"Dr. Prabal Patra","doi":"10.54026/jmms/1087","DOIUrl":"https://doi.org/10.54026/jmms/1087","url":null,"abstract":"This case is about a century-old integrated steel plant combined with mines, having more than 0.42 million capitalintensive assets, ages ranging from 0 to 100 years and spreads across 700+ hectares as shown in Figure 1. Assets having varied levels of automation maturity with different maintenance methodologies. It’s about shifting the whole maintenance paradigm from Time-based & Condition-based to Predictive. Through digital initiatives & optimum maintenance cost, we are trying to develop a Maintenance Transformation Roadmap (MTR) to ensure maximum machine availability/ reliability. For this paradigm shift from conventional to predictive maintenance, critical assets were identified through a systematic approach. Under this MTR Journey, to bridge the sensor gap, SMART Sensor (3 axis vibration & Temperature) was identified as the appropriate solution. Customizable In-house SMART Sensor applicable in Mining & Steel industry application and low-cost solution helped in cross locational horizontal. Presently early warning alerts saved 1000+ potential breakdowns on 1200nos critical assets. The Predictive Maintenance Framework has both tangible and intangible benefits. While safety is the most important intangible benefit of this technology, tangible benefits include approved savings of $20 Million. Further, we expect to save $12.5 Million by deploying our Sensor and $35 Million via prevention of breakdowns","PeriodicalId":503317,"journal":{"name":"Journal of Mineral and Material Science (JMMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141837828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work explores the impact of fly ash and nanoparticle reinforcements (TiO2 , hBN, B4 C) on the mechanical and tribological properties of magnesium nanocomposites produced via mechanical alloying. The investigation revealed that incorporating these reinforcements increased the compressive strength and microhardness of the composites compared to pure Mg. Notably, the Mg-fly ash + B4 C composite exhibited the highest microhardness (50.74 HV), representing a 71.3% increase. Tribological analysis demonstrated that the Mg-fly ash composite and Mg-fly ash + TiO2 composite displayed slightly lower friction coefficients than pure Mg. The Mg-fly ash + hBN composite exhibited the lowest friction coefficient due to the lubricating nature of hBN. In contrast, the Mg-fly ash + B4 C composite showed the highest friction coefficient due to its inherently rough surface. These findings suggest that the developed hybrid magnesium nanocomposites offer a compelling combination of enhanced mechanical properties and tunable tribological behavior, making them suitable for applications demanding both wear resistance and reduced friction.
这项研究探讨了粉煤灰和纳米粒子增强材料（TiO2、hBN、B4 C）对通过机械合金化生产的镁纳米复合材料的机械和摩擦学性能的影响。研究表明，与纯镁相比，加入这些增强材料可提高复合材料的抗压强度和显微硬度。值得注意的是，镁-粉煤灰 + B4 C 复合材料的显微硬度最高（50.74 HV），提高了 71.3%。摩擦学分析表明，粉煤灰镁复合材料和粉煤灰镁 + TiO2 复合材料的摩擦系数略低于纯镁。由于 hBN 的润滑性，粉煤灰镁 + hBN 复合材料的摩擦系数最低。相反，镁-粉煤灰 + B4 C 复合材料因其固有的粗糙表面而表现出最高的摩擦系数。这些发现表明，所开发的杂化镁纳米复合材料将增强的机械性能和可调整的摩擦学行为完美地结合在一起，使其适用于既要求耐磨性又要求减少摩擦的应用领域。
{"title":"An Investigation of the Tribological and Mechanical Properties of the Hybrid Mg Nanocomposites Manufactured by Mechanical Alloy","authors":"Essam B Moustafa","doi":"10.54026/jmms/1084","DOIUrl":"https://doi.org/10.54026/jmms/1084","url":null,"abstract":"This work explores the impact of fly ash and nanoparticle reinforcements (TiO2 , hBN, B4 C) on the mechanical and tribological properties of magnesium nanocomposites produced via mechanical alloying. The investigation revealed that incorporating these reinforcements increased the compressive strength and microhardness of the composites compared to pure Mg. Notably, the Mg-fly ash + B4 C composite exhibited the highest microhardness (50.74 HV), representing a 71.3% increase. Tribological analysis demonstrated that the Mg-fly ash composite and Mg-fly ash + TiO2 composite displayed slightly lower friction coefficients than pure Mg. The Mg-fly ash + hBN composite exhibited the lowest friction coefficient due to the lubricating nature of hBN. In contrast, the Mg-fly ash + B4 C composite showed the highest friction coefficient due to its inherently rough surface. These findings suggest that the developed hybrid magnesium nanocomposites offer a compelling combination of enhanced mechanical properties and tunable tribological behavior, making them suitable for applications demanding both wear resistance and reduced friction.","PeriodicalId":503317,"journal":{"name":"Journal of Mineral and Material Science (JMMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140716141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A mathematical programming framework based on Mixed Integer Linear Programming (MILP) model for surfaceunderground mining options and transition optimization for resource extraction is presented in this paper. Existing models are mainly based on a stepwise optimization approach with limited constraints which produces localized optimal solutions and are often impractical. For mineral deposits amenable to both surface and underground mining options, the MILP framework determines the most suitable mining option and associated schedule to exploit the orebody. The MILP formulation is tested and implemented on a gold deposit case study. The NPV of the optimal mining option ($ 2.515 billion) is sensitive to the gold price, ore quantity delivered from the underground mine, and delay factor associated in supporting the operational development and stopes. Positive changes in the delay factors associated with operational development support and mining stope support have more impact on the NPV than negative changes. However, the NPV is highly sensitive to the mining stope support delay than the operational development support delay
{"title":"Resource Extraction Evaluation Using a Mathematical Programming Framework for Surface-Underground Mining Options and Transitions Optimization","authors":"B. O. Afum","doi":"10.54026/jmms/1083","DOIUrl":"https://doi.org/10.54026/jmms/1083","url":null,"abstract":"A mathematical programming framework based on Mixed Integer Linear Programming (MILP) model for surfaceunderground mining options and transition optimization for resource extraction is presented in this paper. Existing models are mainly based on a stepwise optimization approach with limited constraints which produces localized optimal solutions and are often impractical. For mineral deposits amenable to both surface and underground mining options, the MILP framework determines the most suitable mining option and associated schedule to exploit the orebody. The MILP formulation is tested and implemented on a gold deposit case study. The NPV of the optimal mining option ($ 2.515 billion) is sensitive to the gold price, ore quantity delivered from the underground mine, and delay factor associated in supporting the operational development and stopes. Positive changes in the delay factors associated with operational development support and mining stope support have more impact on the NPV than negative changes. However, the NPV is highly sensitive to the mining stope support delay than the operational development support delay","PeriodicalId":503317,"journal":{"name":"Journal of Mineral and Material Science (JMMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140731128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the IR spectra of nominally pure and doped MgO crystals after irradiation, an intense absorption band appears at 1600 cm-1. This message discusses the model of the corresponding absorption center.
{"title":"Absorption Band at 1600 cm-1 in the IR Spectra of Irradiated MgO Crystals","authors":"Kvatchadze V","doi":"10.54026/jmms/1082","DOIUrl":"https://doi.org/10.54026/jmms/1082","url":null,"abstract":"In the IR spectra of nominally pure and doped MgO crystals after irradiation, an intense absorption band appears at 1600 cm-1. This message discusses the model of the corresponding absorption center.","PeriodicalId":503317,"journal":{"name":"Journal of Mineral and Material Science (JMMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140756846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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