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Fuzzy Expert System for Melamine Moulding Compound Dye Feasibility Identification: A Case study on Plastic Industry Jansen Wiratama; Santo Fernandi Wijaya; Samuel Ady Sanjaya; Florentina Kurniasari; Hendro Budiyanto; Ala Al Kafri; Nuttaphat Sukchitt
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1498

Abstract

This study addresses a practical decision problem within the melamine industry. Production managers are tasked with determining whether a new Melamine Moulding Compound (MMC) dye is suitable for use, based on testing parameters such as boiling point, processing time, and pressure. Given that these values frequently fall between established expert categories, manual decision-making can be challenging to justify and replicate. Accordingly, this research develops a web-based Fuzzy Sugeno expert system to assess the feasibility of MMC dye. The model incorporates three input variables, each characterized by low, medium, and high fuzzy sets. Expert knowledge is formalized into 27 rules employing zero-order Sugeno consequents for three classes: not feasible, conditionally feasible, and feasible. The system has been implemented as a PHP and MySQL application and is accessible via a publicly available login page. An illustrative example involving MMC103—boiling point of 165 °C, processing time of 65 seconds, and pressure of 55 bar—indicated medium and high membership values across all three parameters, activating eight rules. The aggregate firing strength was calculated as 3.00, the weighted consequent sum amounted to 80.00, and the final Sugeno score was 26.67. This score categorizes MMC103 as feasible. The results demonstrate that the model not only provides a classification label but also displays memberships, active rules, rule consequents, and the final computation, thereby enabling verification by the production manager. Furthermore, the study includes an English version of the application interface with privacy masking features for user data.
Fuzzy Expert System for Melamine Moulding Compound Dye Feasibility Identification: A Case study on Plastic Industry Jansen Wiratama; Santo Fernandi Wijaya; Samuel Ady Sanjaya; Florentina Kurniasari; Hendro Budiyanto; Ala Al Kafri; Nuttaphat Sukchitt
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1498

Abstract

This study develops and evaluates an explainable zero order Fuzzy Sugeno expert system for assessing the feasibility of Melamine Moulding Compound (MMC) dyes in the melamine industry. The objective is to support consistent dye assessment by converting expert knowledge of boiling point, processing time, and injection pressure into a structured decision model. Each input variable is represented by low, medium, and high fuzzy sets, while four domain experts contributed to the definition and review of the membership ranges, rule base, and feasibility outcomes. The model contains 27 rules with singleton consequents of 10, 20, and 30 for not feasible, conditionally feasible, and feasible decisions, respectively, with midpoint decision boundaries of 15 and 25. The model was evaluated using 23 historical process profiles and classified 10 samples as not feasible (43.48%), 8 as conditionally feasible (34.78%), and 5 as feasible (21.74%). MMC103, with a boiling point of 165 °C, processing time of 65 seconds, and pressure of 55 bar, activated eight rules and produced a Sugeno score of 26.67, resulting in a feasible classification. A ±5% sensitivity analysis with 10,000 random perturbations produced MMC103 scores from 25.86 to 27.29 and retained its feasible classification in all runs, while overall class stability across the 23 profiles reached 98.86%. Sugeno classifications agreed with Mamdani inference for 20 of 23 profiles and with a crisp rule baseline for 18 profiles. By combining expert knowledge formalization, sensitivity evaluation, comparative analysis, and web implementation, this study provides an explainable and traceable decision support approach for MMC dye feasibility assessment in melamine production.