Optimization of an Industrial Recycling Line: The Effect of Processing Parameters on Mechanical Properties of Recycled Polyethylene (PE) Blends

: This study concerns the optimization of an industrial recycling line; in other terms, this paper aims to find the optimal processing parameters that allow for a decrease in the loss of stress crack resistance (SCR) using a notched crack ligament stress (NCLS) test and an increase in the gain of the elongation at break, flexural modulus, and Izod impact strength of a polyethylene (PE) blend before and after recycling. The recycling line is composed mainly of a mono-and twin-screw extruder and a filtration system. Hence, the research question is as follows: How can we optimize the recycling process, without compromising the mechanical properties of recycled polyethylene (PE) blends? To answer the research question, Taguchi’s design of experiment and grey relational analysis (GRA) for multiobjective optimization was applied. Experiments were performed according to L 16 standard orthogonal array based on five process parameters: mono-screw design, screw speed of the mono-and twin-screw extruder, melt pump pressure, and filter mesh size. Based on grey relational analysis (GRA), the optimal setting of process parameters was identified, and a barrier screw and a higher screw speed for both extruders were allowed to have optimal mechanical properties. Furthermore, the analysis of variance (ANOVA) indicated that the mono-screw design and screw speed of the mono-and twin-screw extruder significantly impact the mechanical properties of recycled polyethylene (PE) blends.


Introduction
The growth of populations and incomes have increased global plastics production; it has doubled, reaching 460 million tons (Mt) in 2019 [1].This rapid growth is due to the good properties and low cost of plastic.Thanks to its versatility, this material is used in several fields such as packaging, textile, transport, and construction [2].Global annual plastic waste increased by more than double between 2000 and 2019.Most of the plastic waste comes from applications with lifespans of less than five years: packaging (40%), consumer products (12%), and textiles (11%) [1].Indeed, only 9% of plastic waste was recycled, while 19% was incinerated and almost 50% was landfilled.The remaining 22% was burned or leaked in the environment [1].The proliferation of plastics negatively impacts the environment because of the emission of greenhouse gas emissions, since the production of virgin plastics requires the transformation of petroleum into monomers, which is an energy-intensive mechanism.This process generated more than 400 million tons (Mt) of greenhouse gas emissions in 2012 [3].Protecting the environment involves reducing plastic footprints and enhancing recycling.Basically, recycling techniques can be classified in three categories: physical recycling (primary and secondary recycling), chemical recycling, and energy recovery (incineration) [4][5][6].Physical recycling, also called mechanical recycling, is the most used technique, consisting of several operations (collecting, separating, washing, drying, and extrusion) that aim to obtain a recycled polymer with higher mechanical properties [7].
Mixing polymers during extrusion is one of the most important factors that influences recycled blend properties [8,9].Some qualitative visualization techniques had demonstrated that the mixing quality of polymer is affected by the design of the mixing element.The capability to create a high shear rate was an essential property that enhanced mixing.It was found that the best emplacement of the mixing element is just after the melting zone.Moreover, screw speed was also an important factor that influenced mixing quality, and among all the mixing elements tested, the pineapple screw offered the best mechanism for polymer mixing [8].The recycling line under study is equipped with a mono-and twinscrew extruder and a filtration system.Each piece of equipment has several parameters.To optimize the process's parameter, a design of experiment was completed based on Taguchi coupled with grey relational analysis (GRA).
The Taguchi method helps to design and analyze experiments [10].It has proved its efficiency to significantly reduce the number of trials without compromising the quality of products.However, this method has been developed to optimize a few performance characteristics.Studying multiple performance characteristics requires using the Taguchi method combined with other methods [11].Some researchers have highlighted Taguchi's quality loss function to determine optimum conditions during the parameter design stage for optimizing multiple quality characteristics in manufacturing processes [12,13].The fuzzy logic Taguchi method was used by several researchers to optimize processes with multiple performance characteristics [14,15].Some researchers used the Taguchi coupled with grey relational analysis (GRA) to optimize process parameters; Huang and Lin applied the grey relational analysis for the optimization of machining parameters of wire EDM [16].Fung and al. studied the grey relational analysis to obtain the optimal parameters of the injection molding process for mechanical properties of yield stress and elongation in polycarbonate/acrylonitrile-butadiene-styrene (PC/ABS) composites [17].C. L. Lin used the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics [18].
As mentioned before, this paper focuses on the optimization of the industrial recycling line composed of several pieces of equipment such as extruders and filtration systems.This industrial line is dedicated to recycling polyethylene (PE) blends, which will be used to produce corrugated pipes.The main objective of this study is to investigate the effect of process parameter (RPM, filter mesh size, melt pump pressure, and mixing element) on the mechanical properties of (PE) a polyethylene (PE) blend, such as elongation at break, flexural modulus, Izod, and stress crack resistance (SCR).

Recycling Line and Materials
The recycling line consists of several components, which can be divided into two sections: the first (single-screw extruder + filtration system) for decontamination, and the second (twin-screw extruder) for homogenization (Figure 1).tons (Mt) of greenhouse gas emissions in 2012 [3].Protecting the environment involves reducing plastic footprints and enhancing recycling.Basically, recycling techniques can be classified in three categories: physical recycling (primary and secondary recycling), chemical recycling, and energy recovery (incineration) [4][5][6].Physical recycling, also called mechanical recycling, is the most used technique, consisting of several operations (collecting, separating, washing, drying, and extrusion) that aim to obtain a recycled polymer with higher mechanical properties [7].
Mixing polymers during extrusion is one of the most important factors that influences recycled blend properties [8,9].Some qualitative visualization techniques had demonstrated that the mixing quality of polymer is affected by the design of the mixing element.The capability to create a high shear rate was an essential property that enhanced mixing.It was found that the best emplacement of the mixing element is just after the melting zone.Moreover, screw speed was also an important factor that influenced mixing quality, and among all the mixing elements tested, the pineapple screw offered the best mechanism for polymer mixing [8].The recycling line under study is equipped with a mono-and twin-screw extruder and a filtration system.Each piece of equipment has several parameters.To optimize the process's parameter, a design of experiment was completed based on Taguchi coupled with grey relational analysis (GRA).
The Taguchi method helps to design and analyze experiments [10].It has proved its efficiency to significantly reduce the number of trials without compromising the quality of products.However, this method has been developed to optimize a few performance characteristics.Studying multiple performance characteristics requires using the Taguchi method combined with other methods [11].Some researchers have highlighted Taguchi's quality loss function to determine optimum conditions during the parameter design stage for optimizing multiple quality characteristics in manufacturing processes [12,13].The fuzzy logic Taguchi method was used by several researchers to optimize processes with multiple performance characteristics [14,15].Some researchers used the Taguchi coupled with grey relational analysis (GRA) to optimize process parameters; Huang and Lin applied the grey relational analysis for the optimization of machining parameters of wire EDM [16].Fung and al. studied the grey relational analysis to obtain the optimal parameters of the injection molding process for mechanical properties of yield stress and elongation in polycarbonate/acrylonitrile-butadiene-styrene (PC/ABS) composites [17].C. L. Lin used the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics [18].
As mentioned before, this paper focuses on the optimization of the industrial recycling line composed of several pieces of equipment such as extruders and filtration systems.This industrial line is dedicated to recycling polyethylene (PE) blends, which will be used to produce corrugated pipes.The main objective of this study is to investigate the effect of process parameter (RPM, filter mesh size, melt pump pressure, and mixing element) on the mechanical properties of (PE) a polyethylene (PE) blend, such as elongation at break, flexural modulus, Izod, and stress crack resistance (SCR).

Recycling Line and Materials
The recycling line consists of several components, which can be divided into two sections: the first (single-screw extruder + filtration system) for decontamination, and the second (twin-screw extruder) for homogenization (Figure 1).

Mono-screw extruder
Filtration system Twin-screw extruder The reference blend tested was composed of recycled high molecular weight polyethylene (rHMW) and recycled high-density polyethylene (rHDPE) (Table 1).Two screw designs were tested in the mono-screw extruder: a barrier screw and a screw equipped with Maddock and pineapple mixer (Figure 2).The reference blend tested was composed of recycled high molecular weight polyethylene (rHMW) and recycled high-density polyethylene (rHDPE) (Table 1).

Composition
Rate (%) rHMW 62.5 rHDPE 37.5 Two screw designs were tested in the mono-screw extruder: a barrier screw and a screw equipped with Maddock and pineapple mixer (Figure 2) The temperatures of the mono-and twin-screw extruder were chosen depending on the polymer blend composition (Tables 2 and 3).Tensile tests were performed in accordance with ASTM D638-14, on five dog-boneshaped specimens (specimen type IV) cut from a 3.2 mm thick molded plate (Figure 3).Tensile tests were carried out on a lab integration machine with a crosshead speed of 50 mm/min at room temperature 23 °C.Elongation at break was determined from stressstrain curves [19].The temperatures of the mono-and twin-screw extruder were chosen depending on the polymer blend composition (Tables 2 and 3).Tensile tests were performed in accordance with ASTM D638-14, on five dog-boneshaped specimens (specimen type IV) cut from a 3.2 mm thick molded plate (Figure 3).Tensile tests were carried out on a lab integration machine with a crosshead speed of 50 mm/min at room temperature 23  The reference blend tested was composed of recycled high molecular weight polyethylene (rHMW) and recycled high-density polyethylene (rHDPE) (Table 1).

Composition
Rate (%) rHMW 62.5 rHDPE 37.5 Two screw designs were tested in the mono-screw extruder: a barrier screw and a screw equipped with Maddock and pineapple mixer (Figure 2) The temperatures of the mono-and twin-screw extruder were chosen depending on the polymer blend composition (Tables 2 and 3).Tensile tests were performed in accordance with ASTM D638-14, on five dog-boneshaped specimens (specimen type IV) cut from a 3.2 mm thick molded plate (Figure 3).Tensile tests were carried out on a lab integration machine with a crosshead speed of 50 mm/min at room temperature 23 °C.Elongation at break was determined from stressstrain curves [19].

Bending Test
Bending tests were performed in three-point bending mode with a crosshead speed of 10 mm/min according to ASTM D790 on five test rectangular specimens (Figure 4) [20].The flexural modulus was determined from stress-strain curves.

Bending Test
Bending tests were performed in three-point bending mode with a crosshead speed of 10 mm/min according to ASTM D790 on five test rectangular specimens (Figure 4) [20].The flexural modulus was determined from stress-strain curves.

Impact Test Izod
An Izod test is a standardized impact test used to measure the energy absorbed by a material when a notched specimen is subjected to a sudden impact load.This test was performed on an Izod impact tester according to the ASTM D256-10 [21].
The 8 notched specimens with a V-shape notch, with dimensions that are illustrated in Figure 5, were tested using a pendulum.The energy absorbed by the specimen during the test indicates the material's toughness and its impact resistance.

Impact Test Izod
An Izod test is a standardized impact test used to measure the energy absorbed by a material when a notched specimen is subjected to a sudden impact load.This test was performed on an Izod impact tester according to the ASTM D256-10 [21].
The 8 notched specimens with a V-shape notch, with dimensions that are illustrated in Figure 5, were tested using a pendulum.The energy absorbed by the specimen during the test indicates the material's toughness and its impact resistance.Bending tests were performed in three-point bending mode with a crosshead speed of 10 mm/min according to ASTM D790 on five test rectangular specimens (Figure 4) [20].The flexural modulus was determined from stress-strain curves.

Impact Test Izod
An Izod test is a standardized impact test used to measure the energy absorbed by a material when a notched specimen is subjected to a sudden impact load.This test was performed on an Izod impact tester according to the ASTM D256-10 [21].
The 8 notched specimens with a V-shape notch, with dimensions that are illustrated in Figure 5, were tested using a pendulum.The energy absorbed by the specimen during the test indicates the material's toughness and its impact resistance.Based on ASTM F2136, this test method is intended to assess slow crack growth (SCG) for polyethylene (PE) resin.In other terms, this test is used to control the tenacity of materials.The test specimen (Figure 6), which is obtained from compression-molded plaques, is notched and immersed in a solution composed of distilled water and 10% Igepal, at a temperature of 50 • C. Five specimens were placed at a single ligament stress level in a bath maintained at 50 • C, the weight tube was attached to the lever arm of each specimen, and the time to failure of all specimens was recorded [22].

Notched Crack Ligament Stress (NCLS)
Based on ASTM F2136, this test method is intended to asses (SCG) for polyethylene (PE) resin.In other terms, this test is used to of materials.The test specimen (Figure 6), which is obtained from plaques, is notched and immersed in a solution composed of distille pal, at a temperature of 50 °C.Five specimens were placed at a single in a bath maintained at 50 °C, the weight tube was attached to the le imen, and the time to failure of all specimens was recorded [22].

Line's Parameters
The design of experiments (DOE) approach based on the Tagu applied in several studies related to composite and polymer process By using strategically this method, it is possible to study the effe at one time, and to study inter-relationships and interactions [26][27][28] The objective of this paper is to study the effect of recycling li mechanical properties of recycled polyethylene (PE) blends and to d parameters configuration of the line.
The parameters considered were as follows: the screw design o truder, the screw speed of the mono-and twin-screw extruder, the m and the pressure of the melt pump.Taguchi orthogonal arrays (OA

Design of Experiments 2.3.1. Line's Parameters
The design of experiments (DOE) approach based on the Taguchi method has been applied in several studies related to composite and polymer processes [23][24][25].
By using strategically this method, it is possible to study the effect of several variables at one time, and to study inter-relationships and interactions [26][27][28].
The objective of this paper is to study the effect of recycling line parameter on the mechanical properties of recycled polyethylene (PE) blends and to determine the optimal parameters configuration of the line.
The parameters considered were as follows: the screw design of the mono-screw extruder, the screw speed of the mono-and twin-screw extruder, the mesh size of the filter, and the pressure of the melt pump.Taguchi orthogonal arrays (OA) were used to build the experimental matrix.Table 4 shows the parameters and their levels in the experiments.The Taguchi experimental design, called orthogonal arrays (OAs), consists of a set of fractional factorial designs which ignore interactions and concentrate on main effect estimation.Orthogonal arrays can be viewed as plans of multifactor experiments where the columns correspond to the factors, the entries in the columns correspond to the test levels of the factors, and the rows correspond to the tests (Table 5).

Results of Experiments
After setting the experimental parameters for each experiment, 16 experiments were conducted using Taguchi orthogonal arrays (Table 5).Four characterization tests were carried out on the recycled materials.In other terms, the response features were elongation at break, flexural modulus, Izod impact strength, and stress crack resistance (SCR).
Since the study concerns an industrial line that recycles post-consumer and postindustrial plastics from all sources, the physicochemical properties of its materials change depending on the batch.To overcome this complexity, for each test, three samples were characterized before and after they had been recycled, and the gain of each property was calculated for all the tests (Table 6).To investigate which processing parameters significantly affect the mechanical properties of the recycled blends, graphics were drawn using Minitab to shows the effect of each parameter on each recycled blend's property (Figures 7-10).To investigate which processing parameters significantly affect the mechanical properties of the recycled blends, graphics were drawn using Minitab to shows the effect of each parameter on each recycled blend's property (Figures 7-10).The graphics show that the design of the mono-screw extruder significantly influences the gain of elongation at break and the loss of SCR (stress crack resistance), while the pressure of the melt pump and the screw speed of the twin-screw extruder impact the gain of Izod impact strength and flexural modulus, respectively.
Since the process has 4 response features, and each parameter has a significative impact on only one property, the Taguchi method should be coupled with grey relational analysis (GRA) to figure out the optimal parameters configuration that improve the mechanical properties under study of the recycled blend.

Grey Relational Analysis
Grey relational analysis (GRA) is a method that combines all the considered performance characteristics into a single value that can be used as the single characteristic in optimization problems.This approach is based on the normalizing of data, and the calculation of grey relational grade (GRG) using grey relational coefficient (GRC) [29].

Normalization of Responses Values
Normalization of response values are completed to transfer the original sequence to a comparable sequence.Numerical results are normalized between 0 and 1.The normalization can be divided to two types depending on the expected nature of the response.
The first normalization is 'the smaller the better' values, where the lowest values of the function are expected.The second one is 'the higher the better', where the highest values of the results are expected.
Since the objective of the study is to find the parameters that allow for the production of a recycled material with optimal properties, accordingly, 'the higher the better' is the normalization criteria that is considered.
The formula for 'the higher the better' normalization criteria considered is as follows: where The graphics show that the design of the mono-screw extruder significantly influences the gain of elongation at break and the loss of SCR (stress crack resistance), while the pressure of the melt pump and the screw speed of the twin-screw extruder impact the gain of Izod impact strength and flexural modulus, respectively.
Since the process has 4 response features, and each parameter has a significative impact on only one property, the Taguchi method should be coupled with grey relational analysis (GRA) to figure out the optimal parameters configuration that improve the mechanical properties under study of the recycled blend.

Grey Relational Analysis
Grey relational analysis (GRA) is a method that combines all the considered performance characteristics into a single value that can be used as the single characteristic in optimization problems.This approach is based on the normalizing of data, and the calculation of grey relational grade (GRG) using grey relational coefficient (GRC) [29].

Normalization of Responses Values
Normalization of response values are completed to transfer the original sequence to a comparable sequence.Numerical results are normalized between 0 and 1.The normalization can be divided to two types depending on the expected nature of the response.
The first normalization is 'the smaller the better' values, where the lowest values of the function are expected.The second one is 'the higher the better', where the highest values of the results are expected.
Since the objective of the study is to find the parameters that allow for the production of a recycled material with optimal properties, accordingly, 'the higher the better' is the normalization criteria that is considered.
The formula for 'the higher the better' normalization criteria considered is as follows: where -X i (k): value after the grey relational generation.
Hence, the normalized values of the responses are calculated and presented in Table 7.

Grey Relational Grade
The grey relational grade (GRG) is used to measure the correlation between the measurement spaces factor and the target sequence after a grey relational generation of the discrete sequence.The GRG depends on grey relation coefficient γ i (k), which can be calculated using the following equation: where -∆ 0i =||X 0 (k) − X i (k) || : which is the difference of the absolute value between the target sequence X 0 (k) and the comparison sequence After the calculation of the GRA coefficient, the grey relational grade can be calculated by the following equation: Waste 2024, 2

196
Table 8 shows the grey relational coefficients and grades for each experiment.The higher grey relational grade (GRG) corresponds to the optimal parameter combination.Experiment 16 has the highest value of grey relational grade, and the factors set up for this experiment are listed in Table 9.The means of the grey relational grade for each level of the five parameters are calculated in Table 8 and summarized in Table 10. Figure 11 shows the process parameter in relation with the grey relational grade.Based on Figure 11 and Table 10, the mono-screw design and the RPM of the two extruders significantly influence the grey relational grade and, consequently, impact the mechanical properties of the recycled blends.

ANOVA Analysis
The analysis of variance (ANOVA) is a method used in this study to find which controllable parameter significantly affects the feature responses of this process.The main objective of ANOVA is to extract from the results how much variation each factor causes to the total variation observed in the results [30].The ANOVA indicates the percentage and the degree of influence of each factor on the results obtained (Table 11).Based on Figure 11 and Table 10, the mono-screw design and the RPM of the two extruders significantly influence the grey relational grade and, consequently, impact the mechanical properties of the recycled blends.

ANOVA Analysis
The analysis of variance (ANOVA) is a method used in this study to find which controllable parameter significantly affects the feature responses of this process.The main objective of ANOVA is to extract from the results how much variation each factor causes to the total variation observed in the results [30].The ANOVA indicates the percentage and the degree of influence of each factor on the results obtained (Table 11).
The results of the ANOVA indicate that the percentage of contribution of the monoscrew design, screw speed of the mono-and twin-screw extruder, and mesh size of the filter are 45.47%, 5.7%, 5.86%, and 4.3%, respectively (Table 11).
Figure 12 shows the contribution of the five parameters on the mechanical properties of recycled blends.The mono-screw design is the most significant parameter for multiple performance characteristics, while the melt pump pressure does not have a significant impact on the process's response.

Conclusions
In this paper, the controllable parameters influencing the multiple performance characteristics of recycled polyethylene (PE) blend were studied based on Taguchi's experimental design method.The optimal configuration of the recycling line was determined for the improvement in the following mechanical properties: elongation at break, flexural modulus, Izod impact strength, and stress crack resistance (SCR).
This research proposed the orthogonal array combined with the grey relational analysis (GRA) to optimize multiple performances of recycling of PE blends when 5 parameters where modified: mono-screw design, speed screw of the mono-and twin-screw extruder, the pressure of the melt pump, and the mesh size of the filter.
The conclusions were summarized as follows: 1.It can be concluded from the grey relational grade and the response table for the grey relational grade that the optimal levels of recycling process parameters for the desired mechanical properties is the combination labelled as A2B2C2D2E1.In other terms, the optimal parameter settings are as follows:

Conclusions
In this paper, the controllable parameters influencing the multiple performance characteristics of recycled polyethylene (PE) blend were studied based on Taguchi's experimental design method.The optimal configuration of the recycling line was determined for the improvement in the following mechanical properties: elongation at break, flexural modulus, Izod impact strength, and stress crack resistance (SCR).
This research proposed the orthogonal array combined with the grey relational analysis (GRA) to optimize multiple performances of recycling of PE blends when 5 parameters where modified: mono-screw design, speed screw of the mono-and twin-screw extruder, the pressure of the melt pump, and the mesh size of the filter.
The conclusions were summarized as follows: 1.It can be concluded from the grey relational grade and the response table for the grey relational grade that the optimal levels of recycling process parameters for the desired mechanical properties is the combination labelled as A2B2C2D2E1.In other terms, the optimal parameter settings are as follows: -Mono-screw design: Barrier screw -Screw speed (mono-screw extruder): 90 RPM -Pressure of the melt pump: 40 bar -Mesh size of the filter: 300 µm

Table 4 .
Experimental parameters and their levels.

Table 5 .
Experimental design based on experimental values.

Table 6 .
Data summary of experiments.

Table 8 .
Grey relational coefficients and grey relational grades.

Table 10 .
Mean value of the grey relational grade.

Table 11 .
ANOVA for multiple performance characteristics.

Table 11 .
ANOVA for multiple performance characteristics.