*Article* **An Integrative Simulation for Mixing Different Polycarbonate Grades with the Same Color: Experimental Analysis and Evaluations**

**Jamal Alsadi \*, Rabah Ismail and Issam Trrad**

Engineering College, University of Jadara, Irbid 21110, Jordan; r.ismail@jadara.edu.jo (R.I.); i.trrad@jadara.edu.jo (I.T.)

**\*** Correspondence: jamal.alsadi@ontariotechu.net

**Abstract:** The processing parameters' impact such as temperature (Temp.), feed rate (F.R.), and speed (S.) at three distinct grades of the same color was explored in this study. To investigate the effect of the characteristics on color formulations, they were each adjusted to five different levels. For these grades, which were all associated with the same color, an intermeshing twin-screw extruder (TSE) was used. The compounded materials were molded into flat coupons then evaluated with a spectrophotometer for their CIE (L\*, a\*, b\*, and dE\*) values. A spectrophotometer was used to determine the color of a compounded plastic batch, which measured three numbers indicating the tristimulus values (CIE L\*a\*b\*). The lightness axis, which ranged from 0 (black) to 100 (white), is known as the L\*-axis (white). Redness-greenness and yellowness-blueness were represented by the other two coordinates, a\* and b\*, respectively. The color difference deviation (Delta E\*) from a target was dimensionless, when dE\* approached zero. However, the most excellent favorable color difference value occurred and different processing impact factors on polycarbonate grade were investigated. Using the response service design (RSD) software of Stat-Ease Design-Expert® (Minneapolis, MN, USA), historical data were gathered and evaluated. To reduce the value of dE\*, the impacts of these processing factors were investigated with the three processing parameters. The whole tristimulus color value could be simulated. Parameters were adjusted on 45 different treatments, using a five-level controlled response method to investigate their impact on color and detect non-optimal responses. The ANOVA for each grade was used to build the predicted regression models. The significant processing parameters were subjected to experimental running to simulate the regression models and achieve the best color, reducing waste.

**Keywords:** different grades; RSD; simulate r egression models; processing and parameters; analysis of variance; resin pigment blends
