Global Journal of Computer Science and Technology, C: Software & Data Engineering, Volume 22 Issue 2

Figure 13: Feed Water Quality Display Panel i. Dynamic Simulation for Worst-Case and Best-Case Test Values on Iron Fe (Ppm) The iron (Fe) as a default parameter with range of 0.0- 0.025ppm was simulated, and the feed water erratically displays worst-case of 2ppm a higher value of Fe, this turns the indicator paramter red. The erractic value was remove as a user clicking and system requesting right value to be entered. the user enterd a test value best- case of 0.010 Fe (ppm), which is within the parameter setpoint range, and the paramter bar turns green, validating that the boiler device enable and working effeciently. Figure 14: Fe (iron) Simulation Result ii. Dynamic Simulation for Worst-case and Best-case values on pH value at 25DegC The dynamic simulation results of the feed water quality for pH value at 25 DegC displaying pH value parameters of test value worst-case of 8.2-9.5 is shown below. The boiler system displaying a test value worst-case pH value of 8.2, less than the designed setpoint, turns indicator panel red, a user then clicked on the indicator bar and entered the right value range of pH value of say 8.9 to validate the system. The best- case value simulation which is a pH value of 8.9 @25DegC, turns indicator green, meaning value entered is within the boiler system designed specification. Figure 15: Ph Value at 25degc Simulation Result iii. Dynamic Simulation for Worst-Case and Best-Case Values for Feed Water Quality on (TDS) In Ppm Finally, a dynamic simulation for total dissolved solid (TDS) parameter was carried out with worst-case value of 1.80ppm and best-case value of 1.20ppm TDS. The feed water TDS panel indicator bar turns red at 1.80ppm which is erratic. A user is requested to entered correct value of the feed water quality at 1.20ppm which turns the TDS bar indicator green, this keeps boiler device in healthy operation. Figure16: TDS Simulation Result c) Analysis for Mean, Mean Absolute Deviation and Standard Deviation System Errors The researcher computes the mean, mean absolute deviation (MAD) and the standard deviation errors (SDE) of both manual and auto running with different time intervals to evaluate and verify which mode of the boiler system was preferable and the number of errors generated. The action research method deployed with quantitative observation of ten (10) consecutives run times of the boiler system on Table8, comprising system error time (minutes), system running in manual and auto run. Each time corresponds with the number of errors generated. Steam Package Boiler Expert System for Control and Maintenance of Fertilizer Plants Using Rule-Base Fuzzy Logic Global Journal of Computer Science and Technology Volume XXII Issue II Version I 36 Year 2022 ( ) C © 2022 Global Journals