Fault diagnosis of an industrial plant using a Monte Carlo analysis coupled with systematic troubleshooting

Efficiently troubleshooting a fortification issue at an industrial milk powder plant is a complex undertaking given the myriad of possible causes. Multiple causes, even when simple, are not easy to diagnose, however every single cause needs to be addressed in order to consistently meet product quality specifications. This paper uses statistical modelling in the form of Monte Carlo simulations to investigate the probable causes for unexpected excessive product variation. This approach alone, refines but does not completely solve, the production issues, so a systematic approach was required to definitively solve other root causes. This two-step fault diagnosis approach ensured that all of the differing causes proposed by plant personnel could be addressed, and sound recommendations for good manufacturing operations could be made and adopted.