Friday, April 5, 2013

Prognostics & Diagnostics with Big Data



Prognostics & Diagnostics with Big Data




                Damage prognostic’s is the future of structural health monitoring. Damage prognosis (DP) attempts to forecast system performance by assessing the current damage state of the system, which looks at the future loading environments for that system, and predicting through simulation and past experience the remaining useful life of the system according to the Philosophical Transactions of The Royal Society (http://rsta.royalsocietypublishing.org/content/365/1851/623.full).  To fully maximize the potential, damage prognostics model will require further development and the integration of measurement/processing/telemetry hardware with deterministic and probabilistic predictive models. While DP is in its infancy there is tremendous potential for life-safety and economic benefits. 

                DP has applications that could be used in most engineered structures and mechanical systems including civil infrastructure, civil defense hardware, and commercial aerospace systems.  Airframe and jet engine manufacturers are using a business model to allow the customer to assess damage and predict when the damage will reach some critical level that will require corrective action. The owners can better plan scheduled maintenance tasks.  Within Civil infrastructure, there is a great need for prognosis of large building and bridges after a large-scale event such as an earthquake, flood, or tornado. The structural condition assessments will help confidently predict how these structures can be repaired and offer a safe condition for public use. The helicopter industry has used vibration testing and data trending for predictive maintenance for several years and has been proven to increase the rotor component life up to 15%. One factor that allows for rotor blades to be accurately tested is that the rotor speed is typically held at a nominal speed. Other prognostic examples in aircraft include the T55 engine in the CH-45 helicopter. This paper (http://www.impact-tek.com/Resources/TechnicalPublicationPDFs/MaintenanceManagement/Impact_MM_MR_ADEPTFinal_color.pdf) identifies innovative diagnostic, prognostic and maintenance reasoning technologies focused on significantly reducing operational and support requirements. 

                Another avenue for prognostics and diagnostics can be found with Condition Based Maintenance (http://www.arl.army.mil/www/default.cfm?page=980) (CBM). CBM is increasing the Army’s weapon system readiness and is resulting in huge maintenance costs savings for the Army. The Army can save millions in eliminating maintenance test flights and corrective maintenance tasks. Reliability Web.com expounds on how cloud technology can be used for Condition-Based Monitoring (http://reliabilityweb.com/index.php/articles/cloud-technology_condition_based_monitoring/). Condition Based Monitoring is the core of how you can perform condition-based maintenance. Vibration analysis, motor current signature, ultrasound and oil analysis, can be used to help assess the help of machinery and predict future failures. Some advantages of condition-based monitoring include improved system reliability, increased production, decreased maintenance costs, and less human intervention with less human error influence. Using cloud technology with condition based monitoring will allow anyone with approved access rights to the data from anywhere in the world, without having to add additional expensive infrastructure. It also makes it easier to monitor remote installations – pipelines, offshore drilling rigs, small facilities with limited resources. Types of cloud services include: Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (IaaS). Each form of cloud services are different based on the support requirements. 


                As the Army and private sector businesses with large machines expound the technology of Condition-Based Maintenance, this will allow smaller businesses to reap the benefits as well. The future is bright when it comes to automobile maintenance, lawn-mower, and other small machine preventative maintenance. Hopefully big businesses and the automatic preventative maintenance tasks that the automobile industry mandates will stand in the way. There is a lot of money to be saved by the consumer without having to risk the reliability of the vehicle when implementing Condition-Based Maintenance. 


Other Condition Based Maintenance articles - http://alvarestech.com/temp/milton2012/rcm.pdf




4 comments:

  1. Thank you for sharing. Condition Based Maintenance is a major component of Predictive Maintenance (PdM) and asset health

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