Sustainable MachinesTM by Conservation Labs
Condition Monitoring & Predictive Maintenance
Smart Equipment Monitoring for the Built Environment
Using Sound to Determine Machine Function and Malfunction
Introducing Sustainable MachinesTM by Conservation Labs, an edge-to-cloud platform that quantifies and classifies the audio profile of a machine, creating high-resolution and actionable data about machine function and malfunction. With Sustainable MachinesTM, OEMs and large service providers can develop a low-cost approach to developing an effective proactive and predictive maintenance program.
Solution Levels
Implementing condition monitoring and predictive maintenance for equipment can yield substantial cost savings, enhance customer satisfaction, and drive revenue growth for commercial properties and businesses that rely on appliances and equipment to ensure product or service continuity, customer safety, and comfort. We work with OEMs and large service providers to configure our edge-to-cloud platform to monitor any type of equipment. We provide solution levels with increasing levels of data resolution and value creation depending on the objectives.
Operational Insights
Basic insights about the machine such as periods of operation, runtime, and intensity of use.
Condition Monitoring
In addition to Operational Insights, identify when the machine deviates from normal use, indicating a potential malfunction.
Predictive Maintenance
In addition to Condition Monitoring, delivers high-resolution insights including overall health, factors contributing to the malfunction, component failure indications, and time to failure.
Save Money & Reduce Environmental Impact
Proactive and predictive maintenance can help companies reduce their environmental impact by increasing machine efficiency, minimizing maintenance, extending machine life, and lowering emissions.
Predictive maintenance allows machines to operate at optimal levels, which can result in reduced energy consumption. When machines are operating efficiently, they require less energy to perform their functions, resulting in reduced greenhouse gas emissions.
By detecting and addressing potential machine malfunctions before they cause significant damage, predictive maintenance can help reduce maintenance costs and environmental impact by scheduling maintenance instead of reacting to failure and by reducing truck rolls.
Predictive maintenance can help identify potential issues and address them before they cause irreversible damage to the machine. As a result, this approach can extend the life of machines and reduce the need for premature replacement, reducing the environmental impact of producing and disposing of new machines.
When machines are operating at peak efficiency, they produce fewer emissions and have a lower carbon footprint. Predictive maintenance can help ensure that machines operate at their optimal levels, reducing their impact on the environment.
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