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Importance of Overall Vibration Measurements in Predictive Maintenance
Overall measurements can be used for identifying a developing fault in a piece of equipment. Overall measurements can be trended over time to make out the trend in machine health.
Total Productive Maintenance
Total Productive Maintenance (TPM) is a way to keep equipment running smoothly without any problems. The goal is to have no breakdowns, no slowdowns, no defects, and no accidents. TPM tries to make equipment work as well as possible by taking care of it before problems happen. Principles of TPM TPM aims to create a…
Improving Pump Reliability and Efficiency with IoT and AI – Using Electrical, Vibration and Ultrasound based condition monitoring data.
Centrifugal pumps are widely used in the Industry. Pumps are one of the major contributors to energy consumption and plant breakdown occurrences. Pump operators usually face the following two challenges with centrifugal pumps: The solution to the above two problems is simple – Operate the pumps at or near their best efficiency point. Even though…
AI Driven Cost Effective Maintenance Strategy for Steel Industry
predictive maintenance case study 0% Downtime due to lack of spares 28% Reduction in inspection of the gear boxes Early detection and prediction of gear box failure in sinter machines. These gearbox spares have long lead time. Early detection allows Tata Metaliks to take corrective action and also order gearbox spares in time. Challenges Detecting…
Electric Submersible Pump (ESP): Improving Reliability and Fault Prediction with Motor Current Signature Data and AI
ESP, is an efficient and reliable artificial-lift method for lifting moderate to high volumes of fluids from wellbores. ESPs are widely used in the oil and gas industry to lift fluids from the reservoir to the surface. ESPs are also used in water applications, such as irrigation, municipal water supply, and groundwater remediation. ESPs offer…
Decoding Reliability : Exploring Predictive Maintenance through Electrical Signature Analysis
ESA can identify subtle changes in electrical signatures that may indicate early signs of equipment degradation or impending failure, allowing for proactive maintenance intervention before a breakdown occurs.
Textile Industry Case Study for AI Driven Predictive Maintenance
19% Overall reliability improvement based on increased in MTBF & Uptime Jaya Shree is the largest linen integrated facility in India. It has more than 42000 spindles and hundreds of machines – Hackling, Sliver Blending, Spinning, Power Looms (Weaving & Knitting), Dyeing and other balance of plant equipment. Jay Shree monitors conditions of bearings, gearboxes, fans…
Predictive Maintenance of cranes Red Sea Gateway Terminal
Red Sea Gateway Terminal improved reliability of their wheeled gantry cranes with ML, AI, IoT vibration, ultrasound and temperature sensors. This case study if for maintenance managers and CIOs that want to digitize reliability to improve crane maintenance in port of industrial installations.
Yamama Cement – Journey to Operational Excellence
15 days Fast Implementation due to wireless sensors and SaaS 48% More assets under digital predictive maintenance 3x Improvement in accuracy and timely prediction of faults. 15 % reduction in unplanned downtime Reduced inspection possible for machineries installed in difficult to reach locations. Increased asset life due to reduced ware leading to capex savings Production…
Essel Mining improves reliability across its mining assets
36% Overall reliability improvement based on increased in MTBF & Uptime 5 Large Critical assets monitored 7 Faults Predicted 21% reduction in unplanned downtime Challenges Outcomes Solving Machinery Huddles with AI The 72+year-old company “Essel Mining & Industries Limited” was founded in 1950, it holds a legacy of innovation and growth. EMIL has expanded its…
Pidilite – Innovating with Precision and Reliability
6 weeks to full implementation 58 assets monitored 22 faults predicted 32% reduction in unplanned downtime Reduced inspection possible for machineries installed in difficult to reach locations. Increased asset life due to reduced ware leading to capex savings Production loss prevented due to reduced unplanned downtimes Reduced overall maintenance cost Reduced inspection possible for machineries…