Recycling Of Waste Products Research Articles

Analysis of Green Closed-Loop Supply Chain Efficiency under Generalized Stochastic Petri Nets

In this paper, we aim to explore the operational performance of a green closed-loop supply chain under random events. A green closed-loop supply chain model based on generalized stochastic Petri nets (GSPN) is built using the Petri nets theory. According to the isomorphic relationship between GSPN and continuous-time Markov chains, the relevant Markov model is converted from GSPN, and the steady-state probability of the model is then calculated. Finally, the model is analyzed from the aspects of time performance and operation efficiency of each link. Compared to previous studies, this paper finds that: when the whole green closed-loop supply chain system reaches a dynamic equilibrium state, the product has a steady-state probability at all stages, and thus the overall operational performance of the system can be obtained; compared with the recycling of waste products, the green product takes a longer time in the production and distribution stages; since marketing, packaging processing, market feedback, and market demand formulation account for a high level of utilization throughout the life cycle of green products, decision makers need to focus on the supervision and management of these links. Managers of green closed-loop supply chain systems need to adjust their decision-making strategies in a timely manner according to the performance level of the system in the steady state to realize the efficient operation of the system. This paper not only provides theoretical support for the improvement of the operational efficiency of green closed-loop supply chain system, but also provides new ideas for the research of green closed-loop supply chain operation mode.

Integrating distributed disassembly line balancing and vehicle routing problem in supply chain: Integer programming, constraint programming, and heuristic algorithms

Today, the fast-changing demands of customers force manufacturers to adapt their systems to the variability. As a result of the recent advances in technology and transport systems, most manufacturers have begun to employ more than one distributed facility to respond rapidly to the demands of their customers. In addition, with the emergence of Industry 4.0, information exchange between systems at the same and different levels has become relatively easy. Therefore, effective management of distributed facilities by integrating processes at different levels in the supply chain can provide a significant advantage in adapting the system to customer demand dynamics. Furthermore, recycling waste products and using them in new products have become essential for environmentally friendly production. Therefore, this paper introduces integrated distributed disassembly line balancing and vehicle routing problem first time in the literature. Since the distributed disassembly centers with routing decisions of the vehicles from these centers to the factories have not been considered before, the proposed integrated study will contribute to both industry and the literature. The contribution is not only limited to the proposed integrated problem. Also, novel solution methodologies, mixed-integer linear programming, mixed-integer non-linear programming, and constraint programming models are developed to solve the problem. Besides the mathematical models, a multi-start simulated annealing algorithm is also proposed to overcome the large-size instances due to the complexity of the proposed integrated problem. The comprehensive computational analysis demonstrates that the proposed methods are very competitive in providing good-quality solutions for the problem.

Metabolic partitioning in the brain and its hijacking by glioblastoma.

The different cell types in the brain have highly specialized roles with unique metabolic requirements. Normal brain function requires the coordinated partitioning of metabolic pathways between these cells, such as in the neuron-astrocyte glutamate-glutamine cycle. An emerging theme in glioblastoma (GBM) biology is that malignant cells integrate into or "hijack" brain metabolism, co-opting neurons and glia for the supply of nutrients and recycling of waste products. Moreover, GBM cells communicate via signaling metabolites in the tumor microenvironment to promote tumor growth and induce immune suppression. Recent findings in this field point toward new therapeutic strategies to target the metabolic exchange processes that fuel tumorigenesis and suppress the anticancer immune response in GBM. Here, we provide an overview of the intercellular division of metabolic labor that occurs in both the normal brain and the GBM tumor microenvironment and then discuss the implications of these interactions for GBM therapy.

Assessment of sludge application in maize (Zea mays L.): influence on crop biomass and heavy metals bioavailability

ABSTRACT Increasing population and subsequent increase in waste necessitate recycling of waste products to minimize the environmental burden. This study was conducted in semi-arid tropics of Punjab to evaluate different rates of sludge application as a supplementary source of nutrients to conventional fertilizers in maize. The grain yield was significantly higher with the application of 5 t ha−1 sludge over control and marginally lower than in 10 t ha−1. Cadmium (Cd), chromium (Cr), lead (Pb), and nickel (Ni) in grains were below international standards even after maximum dose of sludge treatment and can be declared as safe for consumption. The bioconcentration factor of Cd and Ni increased by 82% and 49% with 10 t ha−1 over control, respectively while it remained same for Cr and Pb. Significant increase in exchangeable Cd, Pb in carbonate, and easily reducible oxide, Ni and Cr in residual fraction with 10 t ha−1 sludge over control were found. Mobility of only Pb and Cd increased with increasing sludge treatment. Conclusively, sludge application can be beneficial in increasing plant biomass, however heavy metal accumulation in plants may limit its use. Long-term effect of sludge applications as nutrient sources must be evaluated to get more in-depth insights.

CLIMATE CHANGE AND ENVIRONMENTAL DEGRADATION: A SERIOUS THREAT TO GLOBAL SECURITY

Climate change and environmental degradation have been considered global issues apart from being graded as emerging issues. Climate change is a significant trend because of the adverse conditions witnessed already, and the implications likely to result when the situation is not addressed. The main causes of climate change and environmental degradation are human activities such as burning fossils, deforestation, and human settlement. The decline of the environment has led to national and international security risks as it is linked to food shortages, climate change calamities such as floods or famine, drought, loss of lives, soil erosion, and crop failure due to limited water resources. Countries have had to come together to find lasting solutions to climate change and the decline of the environment as it has raised concern across the world. Besides, there have been solutions that have been agreed by researchers that would minimize the risks of climate change and the decline of the environment, such as afforestation, avoiding the use of plastics, and recycling of waste products. Therefore, environmentally friendly activities have been encouraged in countries across the globe.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0015/a.php" alt="Hit counter" /></p>

Optimization of Polypropylene Waste Recycling Products as Alternative Fuels through Non-Catalytic Thermal and Catalytic Hydrocracking Using Fresh and Spent Pt/Al2O3 and NiMo/Al2O3 Catalysts

In this work, the conversion of waste polypropylene to alternative fuels (liquid and gas) was performed through non-catalytic thermal and catalytic hydrocracking over NiMo/Al2O3 and Pt/Al2O3 catalysts. The process was carried out in an autoclave batch reactor at a temperature of 450 °C and a pressure of 20 bar, which were selected based on experimental optimization. The spent catalyst was also successfully regenerated at 700 °C under a hot airflow. Experiments were conducted to determine the optimum conditions to completely separate the deactivated catalyst from the solid residue easily. The regenerated catalyst was reused to facilitate the economic cost reduction of the process. The reactivated catalysts have almost the same catalytic properties as the fresh catalysts; this was confirmed by several characterization techniques, such as TGA, XRD, SEM, EDX, BET and FTIR. The produced liquids/gases were quantified and classified into their fractions by the number of carbon atoms and gasoline to diesel ratio using GC/MS. The viscosity, density, API gravity, pour point and flash point of oil cuts were also investigated to evaluate the quality of the resulting liquid from the reactions. The NiMo/Al2O3 catalyst gave the highest liquid hydrocarbons yield of 86 wt%, while the highest weight products of gasoline range hydrocarbon fractions of 49.85 wt% were found over the Pt/Al2O3 catalyst. Almost the same catalytic behavior was found with the regenerated catalysts compared to the fresh catalysts. However, the highest gaseous products at 20.8 wt% were found in the non-catalytic thermal products with an increase in the diesel fuel range of 80.83 wt%. The kinetic model was implemented using six lumps and fifteen reactions, and the apparent activation energies for the gasoline and diesel fractions were calculated. In general, all primary and secondary reactions show greater activation energy values on the Pt/Al2O3 catalyst than on the NiMo/Al2O3 catalyst.

DEM/CFD Simulation in Process Engineering

Thermal and chemical treatment of bulk solids and particle systems is a basic unit operation in many industrial sectors. The purpose of the treatment can be either to achieve well-defined product properties or to use solids in gasification processes to produce syngas, synthetic fuels, or to recycle waste products. Typical examples are the calcination of minerals as dolomite or magnesite in the basic materials industry, the direct iron ore reduction with hydrogen in steel industry, coffee bean roasting in the food processing industry, or catalytic reactors and fluidized bed spray coating of tablets in the chemical and medical industries, respectively. Many of these processes are operated at high temperatures and are, therefore, energy-intensive and often associated with high CO2 emissions; a careful layout of the systems is needed. Furthermore, target properties of the solids must be achieved concerning reactivity, specific surface area, calcination or roasting degree, etc. To meet all these challenges and requirements, a detailed knowledge of the underlying physical and chemical processes is needed for predictive design. Fundamental studies are first necessary to understand the properties of particulate flows, e.g., regarding turbulence modulation, collisions between particles and/or with surfaces, and particle dispersion, before going toward practical applications. Typical systems are highly loaded with particles, often passed by a reactive gas flow, and are operated at high temperatures. Therefore, measurements are very challenging in such systems. Hence, appropriate simulation methods are needed to support system and reactor layout. Such a method combines the discrete element method (DEM) with computational fluid dynamics (CFD). DEM/CFD allows to track individual particles and their interactions with other particles, surrounding walls, and the gas phase in-between the particles. Conversion of the particles including intra-particle processes can be described as well as size change or development of adhesive forces associated with the thermal treatment. The current focus issue of Chemical Engineering & Technology entitled “DEM/CFD Simulation in Process Engineering” gives a status on the description of particulate flows with a focus on reactive particle-gas systems using DEM/CFD and presents illustrative examples of its application. A review article on DEM/CFD for reacting systems sets the frame for the further contributions that concentrate on fundamental aspects, specific examples, and important methodological developments. Examples presented are shaft kilns (production of quicklime/production of spinel), waste incineration, combustion of wood pellets, and carbonate looping processes. Novel trends as the usage of machine learning in combination with DEM/CFD, the combination of resolved and unresolved DEM/CFD in one simulation domain, and new approaches regarding the immersed boundary method to describe particle-gas systems are presented. The contributions do not claim to cover all relevant aspects needed for DEM/CFD simulations of reactive particle-gas systems but can be seen as a first overview and starting point for interested readers. This focus issue and the corresponding workshop at the Conference on Modelling Fluid Flow in Budapest 2022 have been organized by the Collaborative Research Centre BULK-REACTION financed by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project-ID 422037413 – TRR 287. Prof. Dr.-Ing. Viktor Scherer Ruhr-Universität Bochum, Faculty of Mechanical Engineering, Department of Energy Plant Technology Prof. Dr.-Ing. Dominique Thévenin Otto von Guericke University Magdeburg, The Laboratory of Fluid Dynamics and Technical Flows Viktor Scherer Dominique Thévenin

Designing a sustainable fish closed-loop supply chain network under uncertainty.

There is increasing attention to the sustainable development of supply chain (SC) and reverse logistics (RL) in the contemporary competitive economy, notably in the food sector, by scholars and stakeholders. This study investigates a sustainable closed-loop supply chain (CLSC) for fish due to its high value in the family food basket, its perishability, and the importance of waste product recycling. A multi-objective mathematical model is developed under uncertainty and sustainability criteria to optimize production rates with the aim of better distribution among different demand markets, total costs, social issues, and negative environmental effects (e.g., CO2 emissions and unused/waste products). A combination of exact, meta-heuristic, and hybrid meta-heuristic algorithms are used to solve the suggested model. Then, the optimal solutions are found using the Taguchi method by evaluating the best initial replies. The solutions are evaluated based on various performance metrics. The analysis of variance (ANOVA) and the "filtering/displaced ideal solution" methods determine the best solution approach. Moreover, a case study with a trout CLSC in Northern Iran is examined. In addition, the Lingo software utilizes the ε-constraint method to evaluate and check the performance of the algorithms under different levels of uncertainty. Finally, sensitivity analyses are carried out to confirm the efficacy of the proposed algorithms. The findings demonstrate the proposed network's outstanding consistency with the algorithms used and its application and efficiency.

Counter-stereotype intervention for construction and demolition waste recycling products: A functional near infrared spectroscopy study

The generation and stock of construction and demolition (C&D) waste is increasing, which makes the environmental and economic problems serious. In recent years, China has also launched many policies to encourage and guide C&D waste recycling. However, most of these policies are aimed at contractors and recycling utilization parties, while the lack of publicity and promotion has led to the acceptance in the market is generally low. People may have a negative stereotype of this recycled material recycled from C&D waste.In order to explore a measure that can alleviate this problem, this study used experimental research methods from psychology and neuroscience to investigate the mechanisms of different presentation forms of counter-stereotype intervention materials. This study included two experiments: the pretest experiment verified the implicit-explicit stereotype and neuronal image representation of C&D recycling products through single category implicit association test (SC-IAT), semantic difference scale and functional near-infrared (fNIRS). The posttest experiment was based on the counter-stereotype intervention method and intergroup contact theory. A within-participants design was used to investigate the effectiveness of counter-stereotype intervention and the differences in two intervene presentation forms based on the pretest experiment.The results showed that the counter-stereotype intervention was effective in suppressing the activation of stereotypes. The effects of the intervention were similar for both the video and graphic formats. In the neuron imaging representation of the posttest experiment, the significantly activated brain region shifted from the right dorsolateral prefrontal cortex (R-dlPFC) to the left dorsolateral prefrontal cortex (L-dlPFC). L-dlPFC is highly associated with the modulation of cognition, indicating that after the counter-stereotype intervention, the necessity of C&D waste recycling and the credibility of the recycling product influenced the participants. So when the stereotype was reactivated, the signal in the L-dlPFC was suppressed, weakening the expression of the stereotype. This also suggests that the mechanism of counter-stereotype intervention is to strengthen the brain regulatory system rather than to inhibit the activation of stereotypes at the source.

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State-of-health diagnosis of lithium-ion batteries using the fractional-order electrochemical impedance model

The rapid growth of the battery industry has encouraged manufacturers to develop suitable materials that provide maximum safety for their products and customers, evaluate the product's shelf life before marketing, and recycle waste products to preserve the environment. This study presented a new aging diagnosis method using harmonic analysis combined with a fractional-order impedance model (FOIM) to monitor the aging and state-of-charge (SoCs) of lithium-ion batteries (LIBs). The proposed model showed reasonably good accuracy with experimental results from the literature, with a mean squared error (MSE) and a mean absolute percentage error (MAPE) of less than 2% and 0.2%, respectively. On the other hand, to understand the aging patterns and to establish the aging laws incorporated into the simulation models, the FOIM of the LIBs was connected in series with both a pulse-width-modulated (PWM)-controlled direct current (DC/DC) converter and the load to monitor the aging of the LIBs. The harmonic analysis of the acquired current signal enabled the measurement of frequency spectrum amplitude (FSA) variations at low (50 Hz) and high (1000 Hz) frequencies in different ages and SoCs of the LIBs operation. Additionally, the proposed diagnostic technique confirmed that the harmonic signatures indicated differences between different ages and the SoCs of the battery.

Metaheuristic optimizers to solve multi-echelon sustainable fresh seafood supply chain network design problem: A case of shrimp products

Seafood products are sought-after among communities all over the globe and are the main sources of essential nutrition for humans. Recently, the seafood supply chain networks have encountered obstacles that new sustainability regulations and the pandemic have brought forward. In this study, a novel supply chain network is developed for fresh seafood, considering sustainability aspects, to ideally balance the financial aspect of the network while enhancing the recycling of waste products. Moreover, four metaheuristics are employed to conquer the computational complexity of exact solution methods. To evaluate the performance of the algorithms in addressing the complexity of the proposed seafood supply chain model, some numerical examples in three different scales are designed. The obtained results from metaheuristic optimizers are assessed based on five effective measures. To facilitate the statistical analysis process, each measure is normalized using the relative deviation index indicator. According to the results obtained from the implementation of metaheuristic algorithms, it can be concluded that the multi-objective grey wolf and multi-objective golden eagle optimizers outperform the other two solution methods in terms of quality of solutions. Therefore, they can be applied efficiently in solving real-world seafood supply chain network problems.

Analysis of factors influencing the creation and stimulation of the Australian market for recycled construction and demolition waste products

Growing population and urbanisation have led to a significant increase in construction and demolition (C&D) waste generation. There are urgent calls for government and industry to develop better methods for C&D waste management. The creation and stimulation of a market for recycled construction and demolition waste have emerged as a targeted intervention to divert waste from landfill sites and create a second life for waste material. This study evaluates key factors affecting the creation and stimulation of the market for C&D recycled waste products in Australia. Through an extensive review of the literature and several semi-structured interviews involving 27 stakeholders from across the architecture, engineering and construction (AEC) industry, this study establishes four groups of enablers (i.e., encouragement factors, education, enforcement and engagement) and barriers (i.e., operations, market, governance and logistics) to creating and stimulating a market for C&D waste. Furthermore, the institutional theory was applied to findings to demonstrate how normative, coercive and mimetic drivers influence AEC's stakeholders' decisions and justify their C&D waste management practices. The study proposes a Framework for Waste Market Development (FfWMD) to provide practical solutions to overcome the current barriers identified in this study. The study findings guide government decision-makers and AEC industry practitioners to facilitate end markets for C&D waste and contribute to achieving a circular economy (CE). Further empirical studies on the elements of the FfWMD can be developed to test the complex interactions between stakeholders and processes.

Dynamic Research on Three-Player Evolutionary Game in Waste Product Recycling Supply Chain System

Recycling channel construction plays an important role in the development of closed-loop supply chains. In particular, the emergence of online recycling channels has made up for the shortcomings of traditional recycling channels with poor information and limited markets. This paper constructs an evolutionary game model to investigate the cooperation between manufacturers and e-commerce platforms with government intervention or not. The result shows that whether an enterprise actively participates in the cooperative recycling depends on the actual cost of establishing the cooperative recycling system. Additionally, the government support and supervision will affect the actual cost of cooperation. When the actual cost of establishing a collaborative recovery system is very large, under the influence of government interventions, there will be two kinds of evolutionary results for enterprises, either with cooperation or not at the same time. On the contrary, when the actual cost is small or medium, both manufacturers and the platforms will choose to cooperate. Thus, government participation in a cooperative recovery system is the best strategic option.

Mechanical and durability properties of concrete incorporating weathered coarse Linz-Donawitz (LD) steel slag

Concrete usage in recent decades has skyrocketed, which has led to immense pressure on the natural resources such as sand and aggregates involved in its production. The circular economy concept, i.e., usage and recycling of waste products, can be incorporated into concrete production to alleviate the overutilization of natural resources. LD slag is presently dumped as a landfill, aggravating limited land availability and polluting groundwater by leaching heavy metals in it. Previous studies employed Linz-Donawitz (LD) Slag as an alternative to natural aggregates in concrete production. However, none of the studies has focused on the comparative behavior of weathered LD slag incorporated in normal concrete (NC) and metakaolin-based high-strength concrete (HSC). The present experimental study focuses on determining the optimum replacement level of coarse aggregates with LD Slag. Coarse aggregates were replaced with LD Slag at 25, 50, 75 and 100%. Mechanical and durability properties such as hardened concrete density, ultrasonic pulse velocity, compressive strength, split tensile strength, flexural strength, modulus of elasticity, drying shrinkage, water absorption, sorptivity and abrasion resistance were evaluated. Results showed that replacing 75% of coarse aggregates with LD Slag displayed better results for said properties compared to the control mix, both for NC and HSC. Compressive strength, split tensile strength, flexural strength and modulus of elasticity were improved in the range of 7–9%, 19–29%, 6–11% and 7–16% for 75% replacements at 90 days of testing, respectively. Along with lower water absorption, abrasion, and drying shrinkage, the sorptivity coefficient was also reduced compared to control mixes at all testing ages. The usage of LD slag in concrete will result in waste elimination and management and prevent soil contamination.

Experimental and Artificial Neural Network-Based Study on the Sorptivity Characteristics of Geopolymer Concrete with Recycled Cementitious Materials and Basalt Fibres

The environmental concerns regarding the production of the most widely consumed cement construction material have led to the need for developing sustainable alternatives. Using recycled industry waste products such as fly ash and slag via geopolymerisation has led to the development of geopolymer cement—an efficient replacement for ordinary Portland cement (OPC). Adopting geopolymer cement and concrete as a construction material reduces greenhouse gas and promotes the recycling of waste products. This study explores the suitability of a unique geopolymer concrete mix made of recycled cementitious materials including industry waste products such as fly ash, micro fly ash and slag for use in aggressive environments. Sorptivity tests are conducted to assess the durability of concrete and indicate the cementitious material’s ability to transmit water through the capillary forces. This study thus reports on the sorptivity characteristics of a newly developed self-compacting geopolymer concrete and two other fibre geopolymer concrete mixes containing 1% (by weight) of 12 mm- or 30 mm-long basalt fibres. The addition of basalt fibres indicated less water absorption and moisture ingress than the mix without fibres. The study used 18 specimens from three geopolymer concrete mixes, and the results showed that adding fibres improved the durability performance in terms of resistance to moisture ingress. Finally, an artificial neural network model is developed to predict the absorption rates of geopolymer concrete specimens using MATLAB. The prediction models reported excellent agreement between experimental and simulated datasets.

A Framework for Green Interior Design and Simulation Using Immersive VR Technology

The green decoration indoor environment design method has become the main trend in recent years with the rising awareness of environmental protection. The green design strategy emphasizes the reduction of production materials, packaging materials, recycling of waste products, and material recycling. Generally, green interior design is a kind of cognition of friendly treatment to the environment. Considering the future use and development of space to adopt flexible strategies, the design process should incorporate the possibility of future changes. The flexible strategies can reduce the future part of the change and can redecorate waste. In the process of creativity and design, the design objectives should be clearly defined, and the frequency of modification should be reduced. This research introduces a framework for green interior design and simulation using immersive VR technology. The concept of regeneration is used to achieve maximum utilization and minimum damage. It improves the efficiency of using resources; on the other hand, it reduces the impact of interior design on human health and environment.

The Influence of Media in Purchasing Decisions for Recycled Construction and Demolition Waste Products: An Functional Near Infrared Spectroscopy Study.

The increasing hazards caused by construction and demolition (C&D) waste is an inevitable problem in the development of the construction industry. Many countries have successively launched many policies to encourage and guide the recycling of C&D waste, which has greatly improved the recycling rate of C&D waste. However, most of these policies only regulate contractors but do not promote C&D waste recycling products enough. It has led to an increase in the production of C&D waste recycling products while the acceptance in the market is generally low. Consumers believe that products made with “garbage” may have problems such as quality defects. In order to explore a measure that can mitigate this problem, this study uses functional near infrared spectroscopy (fNIRS) to investigate whether the influence of media can increase consumers’ willingness to purchase products for recycling construction and demolition waste, and thus increase consumers’ choice to purchase products for C&D recycling waste. This experiment consists of two phases. First, a pre-test experiment to obtain pre-intervention brain images characterizing consumers’ original attitudes toward C&D recycling waste products through a functional near-infrared imaging brain technique and a questionnaire. Second, The post-test builds on the pre-test to investigate the effectiveness of the intervention. The activation mechanism of the consumer purchase decision is further investigated by fNIRS data. The behavioral results showed that the choice of recycled C&D waste products was significantly higher after the intervention. The fNIRS results further revealed the significantly higher activation of the dorsolateral prefrontal cortex (dlPFC), orbitofrontal cortex (OFC), and medial prefrontal cortex (mPFC) after the intervention. These findings suggest that consumers’ purchase willingness is significantly improved after intervention, and their purchase behavior changed substantially. This study also demonstrates the great potential of fNIRS for interdisciplinary research in engineering management and neuroscience.

A multi-objective optimization framework for a sustainable closed-loop supply chain network in the olive industry: Hybrid meta-heuristic algorithms

A closed-loop option for reusing, remanufacturing, and recycling waste products in the olive industry creates a high added value for this business network. This fact motivates the implementation of closed-loop supply chains for adopting an efficient and sustainable strategy in the olive industry in Iran. As one of the developing countries, Iran must redesign their supply chain networks to meet the standards of sustainable development goals. In this regard, the triple bottom line approach focuses on a sustainable design considering all economic, environmental, and social factors in supply chain networks. The main novelty of this paper is to merge the sustainable Closed-Loop Supply Chain Network (CLSCN) design and the olive industry. Hence, a multi-objective optimization framework is proposed to make location, allocation, and inventory decisions for the considered problem. Based on the triple bottom line approach, the objectives of the optimization model are to minimize the total cost and carbon dioxide (CO2)emissions and maximize job opportunities. In small instances, the model is solved by an epsilon-constraint method. To address the high complexity of large-scale networks, this study innovates new hybrid optimization algorithms. In this regard, a hybrid of Virus Colony Search Algorithm (VCS) and Simulated Annealing (SA) and a combination of Electromagnetism-like Algorithm (EMA) and Genetic Algorithm (GA) are proposed for the first time. To confirm their efficiency, an extensive comparison with individual algorithms is carried out by different multi-objective optimization metrics. Finally, some sensitivity analyses are performed to discuss some practical insights for the supply chain managers working in the olive industry in Iran.

Recovery of Waste Material from Biobags: 3D Printing Process and Thermo-Mechanical Characteristics in Comparison to Virgin and Composite Matrices.

The purpose of this study is to limit the environmental impact of packaging applications by promoting the recycling of waste products and the use of sustainable materials in additive manufacturing technology. To this end, a commercial polylactide acid (PLA)-based filament derived from waste production of bio-bags is herein considered. For reference, a filament using virgin PLA and one using a wood-based biocomposite were characterized as well. Preliminary testing involved infrared spectroscopy, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). The effect of printing parameters (namely bed temperature, layer thickness, top surface layers, retraction speed, and distance) on the final aesthetics of 3D printed parts was verified. The results allow us to attest that the thermal properties of recycled polymer are comparable to those of virgin PLA and biocomposite. In the case of recycled polymer, after the extrusion temperature, bed temperature, and printing speed are estabilished the lowest allowable layer thickness and an appropriate choice of retraction movements are required in order to realize 3D-printed objects without morphological defects visible to the naked eyes. In the case of wood biocomposite, the printing process was complicated by frequent obstructions, and in none of the operating conditions was it possible to obtain an aesthetically satisfying piece of the chosen geometry (Lego-type bricks) Finally, mechanical testing on the 3D printed parts of each system showed that the recycled PLA behaves similarly to virgin and wood/PLA filaments.