Akademik Veri Yönetim Sistemi
JOURNAL OF FAILURE ANALYSIS AND PREVENTION, cilt.18, sa.2, ss.356-363, 2018 (ESCI)
This paper presents a maintenance error detection algorithm. Proposed algorithm is used to determine failure analysis of a locomotive diesel-electric engine. Although the inspected engines had been performing normally up to the maintenance sequence, the problem occurred after the maintenance and resulted in a complete stop of the engines with the high losses on-site. In failure cases, before focusing on technical problem narrowing down possibilities were required. After initial analysis, many possibilities were eliminated and the problem was determined with less effort on shorter time. Engine bearings were investigated to diagnose the problem. The origin of the problem was diagnosed and determined using SEM techniques and on-site inspections. The results show that the shot peening technique used in engine block cleaning operations caused the deterioration of the engine. Oil filters were damaged and could not hold shot peen particles. The oil filter and engine bearing have been examined with SEM and EDS analyses to determine the source of the particles. Some of the found ferrous particles had a spherical shape of 300-1000 mu m. These particles and the high pressure created by the engine's oil pump used to cool the system caused severe abrasive wear.