Maintenance 4.0

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Everyone consumes the same product or service differently. The response to each variable in the consumption cycle is different, the duration is different, and the intensity is different.  A driver who drives 200 KM daily on the highway is different from a driver driving 120 KM in traffic. Both are driving the same car but with different consumption patterns. We cannot treat the two cars with the same maintenance program in our attempt to maximize sustainable performance and avoid stops or malfunctions. 
Predictive maintenance refers to the use of data-driven, proactive maintenance methods that are designed to analyze the condition of equipment and help predict when maintenance should be performed. Using different machine-to-machine connectivity interfaces, Big Data Analytics, and Artificial Intelligence, manufacturers can develop flexible maintenance plans and programs putting into consideration several elements such as (1) the demand on each machine, (2) the expected load of work, (3) internal machine pieces components, (4) the entire schedule of production, …etc.

 

Predictive maintenance plays a critical role in improving overall efficiency and quality. Through predictive maintenance, manufacturers can decrease or eliminate equipment failures, increase asset lifetime, gather precise asset data, and improve workplace safety. 
The cost of maintenance will decrease dramatically as well as the holding stock of spare parts. Additionally, cut-off time can be much better planned in alignment with demand and production orders complexity. The flexibility of the maintenance plan complements the ever-changing production demands and plans giving the organization well-needed production flexibility.  

 

The result of such benefits is reflected in higher ROI, increased production volume and speed (hence improved responsiveness to market demands), and a decrease in manufacturing cost.

 

 

 

 

 

 

 

As per the above diagram showing the different types of maintenance programs and the effect on the OEE (Overall Equipment Efficiency), Predictive Maintenance has the largest impact on OEE achieving high levels of efficiency and utilization. In a supply-driven industry, such as the soft drinks industry, maximizing output is key to company profitability. 


Predictive Analytics solutions provide early warning notification and diagnosis of equipment issues days, weeks, or months before failure. This helps asset-intensive organizations, such as automobile manufacturing, oil production, refining, steel production, telecommunications, and transportation sectors, reduce equipment downtime, increase reliability, and improve performance while reducing operations and maintenance expenditures. An organization can decrease its maintenance costs by up to 30% and 25% of its downtime using predictive maintenance. 
 

Predictive Analytics Software integrates with a wide variety of control and monitoring systems and can be deployed on-premise or in the cloud giving a further higher level of flexibility for improving the speed of decision making.  
Predictive maintenance programs suit large organizations with hundreds of remote assets across multiple sites and small organizations with one single asset or site. Additionally, it is easy to integrate the predictive maintenance systems with the entire system of asset management such as ERP.

 

Finally, the predictive maintenance system can leverage several benefits to the organization such as (1) Alerts and Notifications: organizations can set a wide variety of alert thresholds with underlying predictions and automated response if needed. Relevant users and groups can be notified in real-time. 


(2) Data Analysis: includes a variety of advanced statistical and model-based comparison applications and business intelligence tools that enable organizations to spend less time searching for potential problems. 


(3) Transient Module: provides the ability for online monitoring of abnormal conditions during a transient, such as startups and shutdowns. It is also able to automatically identify previous transient events from the historian, which is useful for comparisons.


(4) Monitoring and Diagnostics: Predictive maintenance programs deliver comprehensive monitoring and diagnostic services remotely or on-site. 


(5) Security: integrates with existing organizational security solutions to limit user access rights and editing privileges at a granular level adhering to your own security policy. 
 

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