10 Benefits of Predictive Maintenance with IoT Projects
Manufacturing equipment fails in hot and cold environments. With the increasing demand for efficiency and quality in production and manufacturing, these unplanned downtimes can cause delays to production schedules and even lost customers. Therefore, it is essential to limit the possibility of unplanned downtime as much as possible to improve the bottom line and gain a competitive advantage.
IoT predictive maintenance with IoT refers to predictive analytics used to predict when equipment requires maintenance and to prevent failures before they occur. It improves the performance, lifetime and reliability of assets by monitoring their health and scheduling maintenance activities accordingly. IoT Predictive maintenance identifies the root cause of failures and takes remedial measures based on this information
Enhanced Production
When equipment breaks down unexpectedly, the production capacity of a manufacturing plant can be reduced during downtime. Predictive Maintenance With IoT uses machine sensors to monitor machines in real-time, track their performance over time, and predict when they will fail. With this information, maintenance technicians can make pre-emptive repairs or replacements before failures occur, keeping production on schedule.
Improved Utilization of MachinesIoT Predictive maintenance extends the useful life of your assets. Unlike preventive maintenance, which fixes damage after it happens, the IoT technology monitors equipment components and replaces them before they break down completely. Using IoT Predictive maintenance, you can identify issues before they arise and extend the useful lifetime of your assets.Safer Work Environment
Predictive Maintenance With IoT allows you to forecast dangerous work conditions before they create any life-threatening risks. For example: by monitoring voltage and temperature levels on machines, you can predict surges before they occur and mitigate them to avoid fire hazards in the workplace.
Evaluation of RepairsWhen machines malfunction and repairs are made, IoT Predictive maintenance allows you to ensure that you have corrected the problem before restarting the machine. This prevents another malfunction and the need for more repairs. Predictive maintenance systems can also analyze several parameters using Internet of Things (IoT) sensors. For example, they can self-diagnose vibration, temperature, and fluid levels before the equipment are used again.Lower Risk for Machine Failures
A functional IoT Predictive maintenance system can eliminate the likelihood of equipment failure by as much as 55%. With regular and preemptive checkups, the equipment can remain operational throughout the production process.
Short Lasting Repairs
The time required for a repair can be reduced by 60% using a predictive maintenance program. In one survey of 500 plants, researchers found that the mean time to repair (MTTR) was reduced from 40 hours to 21 hours when a predictive maintenance program was implemented.
Increased Return on Investment (ROI)When mechanical failures are identified in time, manufacturers tend to spend less on maintenance and repair. They also see increased productivity as a result of line workers and managers focusing on core operations rather than troubleshooting breakdowns. This results in a higher return on investment for the company.Better Stock Management of Spare Parts
IoT Predictive maintenance can reduce the costs associated with stocking spare parts by 30%, including labour, hardware, and other overheads. During repair, there are costs associated with purchasing and stocking spare parts. Predictive maintenance ensures that you only stock replacement parts at the right time, which reduces the cost of stocking by 30%.
Increased Revenue
Production schedules are often compromised by the breakdown of machinery. By protecting your assets from undue wear and breakdowns, you will be able to fulfil production quotas and increase revenue streams.
Applying Predictive Maintenance With IoT
Before beginning a predictive Maintenance With IoT, you should start with a small-scale test. Try placing sensors on one asset to determine how the system fits into your business structure. Afterwards, you can decide the best approach for fully integrating your equipment with the technology. Once your software and IoT Predictive maintenance tools are merged and evaluated, you can begin collecting performance data through sensors and transmitting it wirelessly to a cloud-based centralized storage platform in real-time. Through machine learning and algorithms, your system will gather data about your asset’s condition while also predicting when a failure might occur.
Predictive Maintenance with IoT at Nanoprecise
Nanoprecise is an Industrial Predictive Maintenance With IoT solution provider that offers real-time predictive information about the genuine health and performance of industrial assets. Nanoprecise's 6-in-1 wireless sensor and AI-based analytics platform enable seamless monitoring, prescriptive diagnostics, and scalable Industrial IoT solutions for various sectors.
















