“Accident brings tears, safety brings cheers.” is true for manufacturers and every driving-force associated with a shop floor. Unfortunately, the statistical analysis of the International Labour Organization, states for every minute, 612 workers have a work-related accident, which could have been avoided.
A competent prognostic maintenance policy leverages innovations and analytical information to facilitate streamlined operations in a plant with minimized maintenance tasks. The objective of Predictive Maintenance programs is to increase asset uptime., avoid erratic failures, boost productivity and enhance the protection of technical staff. Providing a hazard-free workspace is the essential conduct of every manufacturer; not only to generate smart business but also to establish a caring relationship with its workforce.
Predictive Maintenance tool (PdM) comprises a sensor to collect data from the equipment, trend and scrutinize it to anticipate any issues or failures before they occur. This data may be obtained by monitoring the vibrations, oil levels, oil splashes, oil whirls, ultrasound, and infrared thermography, etc. Further, as a vital component of PdM, the organisational ecosystem should have a technology to collect, process, prepare and structure massive amounts of equipment data. These tools apply algorithms to the data seized, trends the key indicators, such as vibrations, temperature, acoustics, etc. to envisage when a failure is likely to trigger. With efficient workflows in place, for every actionable insight provided the Maintenance team can perform to improve and refine processes, enhance the reliability of the equipment, maximize uptime and minimize servicing costs.
Predictive Maintenance empowers the stakeholders to understand exactly when and how an asset needs to be serviced for optimal performance. Manufacturers across the globe who rely on Preventive Maintenance are affected by an estimated loss of $13 trillion in production due to equipment downtime. 25 to 30% of workplace deaths in the chemical industry are due to shocks, burns, and injury from moving parts, which could have been prevented with Predictive Maintenance policies. 50% of the machines in a Cement plant run roughly in two years due to harsh environmental conditions; affecting 80% of the operators commanding additional safety measures. A PdM that involves the installation of a sensor to examine the performance of the equipment can substantially track its running for the next decade. 80% of the maintenance time spent in reaching and reacting to the broken parts invokes extra precautionary measures to be taken by the Maintenance team in the automotive industry. Overhauling the equipment on the verge of failure ensures 44% of the unscheduled downtime due to the aging of the equipment in a steel plant.
Thus, Predictive Maintenance programs directly influence the safety of the plant. Servicing the equipment only when it is needed reduces injuries during overhauling, especially in the power plant. The dairy industry which employees 71% of the women employees prioritizes Predictive Maintenance as a benchmark of safety. Defence industries comply with the norm of implementing PdM for the safety and security of every aircraft with more than 9 defence personnel.
Infinite Uptime’s Industrial Data Enabler (IDE) a sensor catering predictive maintenance approach provides instantaneous information on the dashboard and seeks to decrease or eliminate unexpected machine breakdowns. Moreover, 80% of the faults of the rotating equipment viz motors, pumps, fans, blowers, spindle and gearboxes can be predicted with 20% of the costs. A plug and play, real-time triaxial vibration monitoring system that builds a foresighted trend and evaluates the captured data ensures the safety and security of the equipment and may determine its expected life span.