4.2.3. Implementation

In this study, the desired expert system was designed using three principal modules. The first module is related to knowledge base development, the second module is relevant to interface design and required questions to reach the answer, and the third module is associated with system run and dialogue to the user. Figure 10 shows a schematic of the proposed neural expert system and its components. Below is a brief description of each system component.

	- o "Facts" refers to a set of facts relating to the current process state extracted by a knowledge engineer (KE) from the records of the quality managemen<sup>t</sup> system, preventive maintenance, calibration, brainstorming sessions, and interviews with experts.

o "Procedures" focuses on manuals, standards, and procedures. Some examples include technical operation instructions, plaster production standards, and intelligent statistical process control (ISPC) tutorials.

**Figure 10.** The proposed hybrid fault diagnosis system scheme or ISPC.

"Rules" relate to production rules that represent inferential knowledge learned from experts. In the knowledge base of the proposed model, 60 rules were employed that were extracted from interview with the experts, documents including "*Western Electric*" tests (general knowledge of the process), and the NN's response (case-specific data) extracted by KE and presented in the form if–then. Below is an example of a typical rule, based on specific knowledge of a process.

IF "diagnosis" is "upward trend",

AND "failure mode" is "increase of crystal water",

AND "process index" is "decrease of kiln's temperature",

THEN "specific cause" can be "clogged fuel nozzle",

AND "corrective actions" can be either "cleaning the fuel nozzle, the establishment of preventive maintenance (PM) for the burner, or installing fuel filter".


#### **5. Comparative Analysis and Case Study**
