NEW HEAD OF SERVICE URGES ANAMBRA CIVIL SERVANTS TO EMBRACE EFFICIENCY AND ACCOUNTABILITY. (PHOTO). #PRESS RELEASE.

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 New Head of Service Urges Anambra Civil Servants to Embrace Efficiency and Accountability ‎ ‎By Chizoba Njaka  ‎ ‎The newly appointed Head of Service in Anambra State, Ngozi Anuli Iwouno, has called on civil servants to shift towards efficiency and accountability, promising improvements in welfare.  ‎ ‎Addressing staff at the Jerome Udoji Secretariat Complex in Awka, Iwouno outlined her vision for a professional, merit-based, and citizen-centered service that aligns with Governor Chukwuma Soludo's goals. ‎ ‎Iwouno emphasized that her mission is not just a statement, but a call to action, demanding sincerity and commitment from all workers. She expressed disappointment with the recent governor's visit, which revealed empty offices during working hours, and stressed that absenteeism, lateness, and poor attitudes are unacceptable. ‎ ‎The Head of Service pledged to improve welfare, including fixing ministry vehicles, and mandated that Wednesday 1st April , 2026 will be clean...

NAF ADOPTS PREDICTIVE MAINTENANCE CULTURE- CAS. (PHOTOS). #PRESS RELEASE.



 NAF ADOPTS PREDICTIVE MAINTENANCE CULTURE- CAS



The Chief of the Air Staff (CAS), Air Marshal Hasan Abubakar, has stated that the Nigerian Air Force (NAF) is currently adopting the predictive maintenance culture across all NAF Engineering and Maintenance units, designed to assist in determining the condition of in-service aircraft and other equipment in order to estimate, ahead of time, when maintenance should be performed. He stated this recently while addressing personnel of NAF Logistics Command, Lagos, during his operational tour of NAF units in the Lagos area. This approach, according to the CAS, will enable cost savings over routine or time-based proactive or preventive maintenance culture. Air Marshal Abubakar went on to state that the advantage of predictive maintenance is that it allows for convenient scheduling of corrective maintenance and prevents unexpected equipment failures. He also noted that with the right data of equipment lifetime, the tendency for increased plant safety, fewer accidents with negative impact on environment, and optimized spare parts handling is assured. According to him, “We have moved away from proactive maintenance culture to predictive maintenance. This has been possible because we have continued to keep up-to-date data about our spares and current maintenance status of all our platforms. With this, it will enable us to provide spares before they are due for maintenance. It will also reduce downtime while expediting aircraft serviceability.”


The CAS also spoke about the need to continually sustain and enhance NAF’s safety standards. While he reemphasized that safety training will henceforth be compulsory in all NAF training institutions, he also revealed that all NAF institutions have been directed to review their curriculums to include all aspects of safety training. 

  

Predictive maintenance differs from proactive maintenance because it relies on the actual condition of equipment, rather than average or expected life statistics, to predict when maintenance will be required. Some of the main components that are necessary for implementing predictive maintenance are data collection and preprocessing, early fault detection, fault detection, time to failure predictions, maintenance scheduling and resource optimization.


Predictive maintenance is well entrenched in advanced militaries worldwide. According to an article published on 19 January 2023 in defensenews.com, the US Army, for instance, first implemented predictive maintenance on it AH-64 helicopters in 2005. By 2012, the Service was using this approach with the UH-60 helicopter as well as some vehicle programs. By early 2022, it had installed predictive maintenance capability on 65% of its CH-47 Chinook cargo helicopter fleet.


Edward Gabkwet

Air Vice Marshal 

Director of Public Relations and Information

Nigerian Air Force


1 April 2024.

More photos below. 








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