5 Reasons Why Predictive Machine Maintenance is a Critical Pillar of Success for Modern Manufacturers
Tags: api, aws, programming, opensource
Published: 2023-05-10 17:40:58

In the contemporary manufacturing industry, a multitude of processes necessitate swift, top-notch performance and productivity, which poses a formidable challenge for factory workers. Hence, machinery is one of the most essential foundations of the manufacturing sector, and its consistent and efficient operation plays a pivotal role in achieving success. However, even the slightest malfunction, breakdown, or minor issue can result in significant ramifications for the entire production process, ultimately affecting the company's profitability.
Predictive maintenance utilizes IoT-based resources to monitor equipment health and ensure production stays on track. It is an approach that leverages machine data and advanced analytics to predict and prevent potential equipment failures before they occur. This proactive maintenance approach can increase machine uptime, reduce maintenance costs, and optimize the use of maintenance resources.

By shifting from reactive maintenance to proactive maintenance, companies can achieve significant cost savings and improved equipment reliability. Predictive maintenance is becoming increasingly popular in the manufacturing industry, and with the growth of IoT, AI, ML, and other advanced technologies, it is likely to become even more widespread.

The following reasons emphasize the pivotal role of predictive machine maintenance in achieving success in the manufacturing industry:
● Minimized Downtime
● Maximized Efficiency
● Ensured Quality
● Increased Employee Safety
● Reduced Cost 
Examples of Major Disruptions in Manufacturing Due to Machine Failure:
Production delays: Any malfunctioning machine can lead to significant production delays, causing missed deadlines and resulting in lost revenue.
Downtime costs: Replacing faulty equipment can be time-consuming and may require additional costs such as overtime pay for workers or renting temporary machinery to continue production.
Quality issues: A machine breakdown can result in defective products that fail to meet quality standards, leading to customer complaints or reduced sales.
Safety concerns: Certain equipment failures can pose safety risks to employees or the environment, resulting in costly accidents or legal liabilities.
When unpredictable events such as machine failures halt manufacturing production, it leads to downtime, and the challenge for the industry is maintaining all types of equipment while keeping costs low. Predictive machine maintenance is a solution that addresses this issue.
Two Use Cases on Why Predictive Machine Maintenance is a Critical Pillar of Success for Modern Manufacturers
Predictive machine maintenance is a crucial factor for success in modern manufacturing, as highlighted by various studies. According to McKinsey, PdM software can reduce production equipment downtime by 30% to 50%, and extend machine life by 20% to 40%. The U.S. Department of Energy also estimates that preventive maintenance can result in significant benefits, such as up to a 30% reduction in energy and maintenance costs, 35% to 45% fewer breakdowns on machinery, and up to 75% reduction in downtime.
Rawcubes [iDataOps ](https://www.rawcubes.com/idataops.html)provides manufacturers with two use cases that demonstrate how predictive maintenance can be beneficial.
Machine Data Integration for Early Detection of Potential Failure: [iDataOps](https://www.rawcubes.com/idataops.html) enables you to connect and integrate data from all machines with predictive maintenance techniques, allowing you to monitor equipment performance in real time, identify issues, and make predictive decisions. With this tool, you can connect production across the shop floor for real-time visibility of key machine metrics, transfer data using different protocols, and align machine data and service providers with predictive asset maintenance.

Preventive Maintenance Management for Reduced Downtime: [iDataOps ](https://www.rawcubes.com/idataops.html)enables you to create proactive maintenance schedules as per each machine's specifications, helping to prevent future breakdowns or emergency maintenance issues. Predictive maintenance tools can minimize overall maintenance costs, optimize spare part inventory, and reduce downtime. This tool can notify production support and technician staff of scheduled physical check-ups, easily recognize local service technicians for more streamlined troubleshooting, and digitally maintain previous records aligned with the QR code to verify all details of services.
The Final Thought!
Accurate data is critical to the success of predictive maintenance in modern manufacturing. It improves the accuracy of forecasts, enhances decision-making, reduces errors, and boosts efficiency.
Rawcubes' [iDataOps ](https://www.rawcubes.com/idataops.html)offers machine monitoring software that enables manufacturers to harness accurate data from their machines for predictive analysis. The platform provides turn-key predictive equipment analytics services, eliminating the need for large data integrations.
With iDataOps, technicians, leaders, workers, and CEOs can leverage the predictive machine maintenance platform to increase efficiency and reduce operational downtime.
Empower your maintenance team with Rawcubes [iDataOps](https://www.rawcubes.com/idataops.html) by reserving a complimentary demo today!