Predictive Maintenance – Sustainable Solution for Energy Conservation in Manufacturing Plant

India is the fourth-largest producer as well as consumer of electricity. Approximately 45% of the energy produced in India is used by the industrial sector for its development and production. However, according to the government statistical data, though there is a growth of 4.26% in the manufacturing industry an outsized proportion of electrical energy is also consumed. Continue reading the article to know the proven way of Energy Conservation in manufacturing plant.

Overview of Energy Consumption in Manufacturing Industry:

The Indian manufacturing industry can be broadly classified into the processing and automobile industry. Whilst the progress in the automobile sector is already on the decline, the processing industry strives to limit energy usage. The processing industries like food, pulp and paper, basic chemicals, refining, iron and steel, nonferrous metals and non-metallic minerals are considered to be energy-intensive.  The energy consumption in any manufacturing industry today forms an indispensable persona which collects large amounts of real-time data from equipment through sensors, network communication, wireless transmission, and cloud computing technologies.

The main rationale that results in high power consumption is the challenges faced in resource sharing, operation and maintenance management, asset retirement monitoring, inventory management, and procurement monitoring. The need to run the assembly to process only a certain component or process extracts additional power, poor productive management strategies also affect the power consumption adversely.

energy conservation

What leads to more Power Consumption? 

Misalignment of any mechanical equipment impacts a rise in vibrations or noise. According to the law of conservation of energy, this impact is transformed into heat (power loss). Improper lubrication can  trigger friction in bearing causing the motor to ingest excessive electrical energy. Further, the misalignment in any of the axis of the equipment implies additional effort to drive it and absorbs high power. In a normal pump & motor assembly, the outcome of the throttled valves of the pump affects the flow of the pump. Generally, 45% jamming of these valves influences dynamic vibrations reflecting more power utilization. Uneven distribution of mass on an impeller of fan faces an unbalance due to the accumulation of invisible dust particles and contributes to unnecessary power intake. A peak of 1X in radial speed can be observed as a diagnostic feature that indicates pure unbalance. The vibration spectrum has higher noise levels and increased shock pulses due to bearing overload and the characteristic bearing frequencies can be easily identified in the trend analysis. The rise in temperature due to poor lubrication also needs online monitoring. Harmonic filters used to eliminate harmonic distortion can yield high excitation frequency subsequently causing an increase in vibration levels, acceleration as well as the temperature of the equipment. This rise in temperature symbolizes wastage of heat energy. The natural tendency to over-utilize equipment to achieve the production target is a common attribute to excessive power consumption.

Appreciative measures to track the vibration patterns, noise levels, changes in temperature and similar parameters that provide an insight into the operating condition of the equipment can ensure economized energy utilization. Indicatively, the steel plant uses 20% of the energy for its manufacturing, while 18% of the energy used in an automotive facility is consumed by equipment.

Predictive Maintenance – Sustainable Solution for Energy Conservation:

The adoption of Predictive maintenance techniques targeting energy efficiency can result in up to 20% savings annually. Besides, this prognostic management provides an early warning  for replacement or repairs of malfunctioning equipment. Instead of ignoring malfunctions and running equipment to failure, the diagnostics deliver a comprehensive analysis of the equipment.

The achievement of Predictive Maintenance is a sustainable approach to energy optimization, detection, and exploration of opportunities to fix energy leaks and minimize energy costs. With improvements in informatics and analytics, energy usage can even be planned which successively can predict customer’s energy savings. Nonetheless, the implementation of predictive analytics,  equipment history, reduced maintenance costs, revitalised business policies, targeted production figures, streamlined asset operations when integrated prove to be a sustainable solution to manage the energy demand for future generations.

Role of Infinite Uptime’s IDE vEdge

Infinite Uptime’s Industrial Data Enabler (IDE) vEdge, a wireless Predictive Maintenance Solution captures vibrations, acoustics, and temperature in real-time. The plug and play sensor with edge-computing technology provides insights on the dashboard as well as the Android app. IDE vEdge  forecasts the failure of any rotating equipment thus potentially ensuring optimized energy usage for processes run by the equipment.  The vibrational analysis detects cavitation and turbulence issues in pumps, the rotor issues caused due to the vibrations of the electromagnetic forces in an electric motor, shaft or coupling misalignment, etc. With the deployment of vEdge, a traditional manufacturing unit may now be transformed  and termed as a low-power DIGITAL factory. The end-to-end industrial solution with hardware, cloud analytics and control software to monitor equipment matches the energy supply and product-demand.  The easy-to analyze impressions of the equipment captured in real-time empower the Maintenance team to take SMART decisions and harness the full potential of predictive analytics.

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