Direct and general support maintenance manual : truck, lift, fork, gasoline, pneumatic tires, 4,000 pound capacity, Army model MHE 221, Baker model FJF-040, FSN 3930-151-4428.

"October 1971."

Operator's and organizational maintenance manual : truck, fork lift, 4000 lb capacity, 144 in. lift, gasoline engine driven (Baker model FJF-040, Army model MHE-211), FSN 3930-935-7963.

"March 1971."

Operator's manual : truck, lift, fork, electric, solid rubber tires, 4000 pound capacity, Army model MHE-196, Baker model FTD-040-EE, FSN 3930-709-6342, 100 in. lift ....

"February 1965."

Organizational maintenance manual : truck, lift, fork, electric, solid rubber tires, 4000 pound capacity, Army model MHE-196, Baker model FTD-040-EE, FSN 3930-709-6342 (100-in. lift), FSN 3930-709-6341 (130-in. lift), FSN 3930-709-6358 (144-in. lift).

"April 1965."

Organizational maintenance repair parts and special tools list for communications central AN/ASC-15A(V)1 (NSN 5895-01-040-9660) and AN/ASC-15A(V)2 (NSN 5895-01-040-9661).

"24 August 1983."

Resolución 040 del 18 de abril de 2013: Por la cual se acepta un desistimiento

Servicios registrales

Resolución 040 del 15 de abril de 2009: Por la cual se acepta un desistimiento de un recurso de reposición y en subsidio de apelación

Doctrina

A practical approach for reliability prediction of pipeline systems

Pipelines play an important role in the modern society. Failures of pipelines can have great impacts on economy, environment and community. Preventive maintenance (PM) is often conducted to improve the reliability of pipelines. Modern asset management practice requires accurate predictability of the reliability of pipelines with multiple PM actions, especially when these PM actions involve imperfect repairs. To address this issue, a split system approach (SSA) based model is developed in this paper through an industrial case study. This new model enables maintenance personnel to predict the reliability of pipelines with different PM strategies and hence effectively assists them in making optimal PM decisions.