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Predictive Maintenance: A Paradigm Shift
Minding your own business is wisdom, but it might not pay in the brave new world of condition monitoring, where equipment from numerous OEMs run side-by-side in highly integrated industrial production environments. How much should OEMs concern themselves with the performance of their equipment whose failure could cast them in poor light? Should they care that their machines be under the watchful eye of third parties, especially if those third parties are competitors?
Early predictions on equipment malfunctions and service maintenance can be automatically scheduled ahead of an actual part failure by installing IoT devices inside equipment continuously transmit information about the equipment’s status and condition to software platforms that analyze the data to determine the condition of the machine with the intent to forecast mechanical wear and failure. In recent years, a few OEMs developed homegrown remote monitoring solutions. The few notable exceptions that survived came from OEMs that recognized the potential of knowing everybody’s business and possessed the scale to do it. It’s for this reason that the question is becoming less about whether to monitor and more about how far and wide an OEM’s predictive maintenance program should extend.
One of the keys to the cost-effective and efficient operations for any business with a significant number of mechanical systems is its maintenance program. Many OEMs are embracing the Internet of Things (IoT) by connecting their products. The marriage of these closely connected data sources, characterization of the host device, and analytics predicting operational behavior has moved maintenance to a new level.
Predictive maintenance has gained importance in line with increased company focus on productivity and asset utilization. The need for eliminating unnecessary maintenance costs and catastrophic breakdowns in production processes is expected to continue to drive the adoption of predictive maintenance solutions. Global machine condition monitoring market in the pharmaceutical industry alone was valued at $118.7 million in 2015 and is expected to reach $159 million by 2020, growing at a CAGR of 6.02%.
Advantages of Predictive Maintenance Solutions
- Wind Energy- To be competitive in the energy market, wind turbines must operate as cheaply as possible. Maintenance costs due to their remote locations are typically high, so routine maintenance or portable diagnostic systems often don't make sense.
- Oil and Gas- As the cost of reaching oil and gas reserves increases, reducing the operating and maintenance costs of oil and gas assets grows increasingly important. Pumps and drills are often in remote locations where technician expenses are high.
- Aviation- Predictive maintenance is heavily used in the aviation sector. It allows airlines to monitor and control the status of the onboard systems and equipment, as well as variations in the flight conditions and to the operation of the aircraft.
- Food and beverage industry- Food and beverage companies have started adopting machine condition monitoring and predictive maintenance solutions to optimize plant operations and reduce equipment breakdown and downtime.
- Automotive industry- The automotive industry's plant equipment and machinery are dependent on predictive maintenance solutions to prevent machinery breakdown and downtime, increase productivity, and uphold safety standards.
- Healthcare industry- Global machine condition monitoring market in the healthcare industry is helping improve patient care and patient outcomes.
- Insurance Industry – Insights from predictive maintenance analytics are helping insurance providers improve policies and claim reimbursements
The following are the advantages of predictive maintenance using analytics:
- Detects incipient failures and breakdowns in early stages and facilitates early repair
- Establishes shelf life of asset and assesses product warranty
- Maintains inventory and tabs on spare parts
- Explores hypothetical scenarios
- Early notification and alerts to field operators and improves safety standards
- Prevents unnecessary downtime in production processes
- Maximizes lifecycle of equipment
- Enables product innovation – new features, services and pricing models
Predictive maintenance solutions ensure smooth functioning and harmony of complex processes in plant equipment and machinery with minimum downtime and maintain the exact standards of the legislature for employees' safety. The adoption of IoT and advances in M2M communications have accelerated the use of such technologies in manufacturing across multiple industries. Listen to your inner geek and consider the potential impact of the Internet of Things on your business-
- For OEMs, consider the broader benefits of IoT to in optimization of inventory and depots for addition business improvements and, beyond revenue enhancement for services
- For end-users, include IoT, remote monitoring, and predictive maintenance in the selection criteria for new equipment to reduce total lifecycle cost
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