There are countless injection molding formulas, and every engineer must remember each one.
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The clamping force is determined by: F = (Am x Pv) / Where:
For instance, if the mold cavity projected area is 270cm^2 and the filling pressure is 220kg/cm^2, the clamping force is: F = (270 x 220) / = 59.4TON
The injection pressure is given by: Pi = (P x A) / Ao Where:
For a pump pressure of 75kg/cm^2, an effective injection cylinder area of 150cm^2, and a screw cross-sectional area of 15.9cm^2 (for a diameter of 45mm), the injection pressure is: Pi = (75 x 150) / 15.9 = 707 kg/cm^2
The injection volume is: V = π x (Do/2)^2 x ST Where:
For a screw diameter of 42mm and an injection stroke of 165mm, the injection volume is: V = π x (4.2/2)^2 x 16.5 = 228.6cm^3
The injection weight is: Vw = V x η x δ Where:
Given an injection volume of 228.6cm^3, a mechanical efficiency of 0.85, and a specific gravity of 0.92, the injection weight is: Vw = 228.6 x 0.85 x 0.92 = 178.7g
The injection speed is: S = Q / A Where:
For a motor speed of RPM, a pump discharge volume of 85 cc/RPM, and an effective injection cylinder area of 140 cm^2, the injection speed is: S = (85 x ) / (60 x 140) = 10.1 cm/sec
The injection rate is: Sv = S x Ao Where:
For an injection speed of 10cm/sec and a screw diameter of 42mm, the injection rate is: Sv = 13.85 x 10 = 138.5g/sec
These formulas offer a foundational grasp of the pivotal parameters in injection molding, ensuring optimal results in the molding process.
Using the constant π/4 = 0.785:
Injection Weight (gr) = Theoretical Injection Volume x Plastic Specific Gravity x Injection Constant (0.95).
Pump Single Turn Volume (cc/sec) = Injection Cylinder Area (cm²) x Injection Speed (cm/sec) x 60 seconds / Motor Speed.
Pillar Diameter² (cm²) x 0.785 x Young's Modulus (scm4 approx. kg/cm²) x 4 = Approximate Clamping Force (Ton).
Product Layout Projection Area (in²) x Standard Thickness (1.5mm) / Average Product Thickness (mm) x Material Constant / PS Material Constant (1) = Clamping Force (Ton).
Ejection Force (Ton) = Ejection Cylinder Area (cm²) x System Maximum Pressure (140kg/cm²) / .
Appropriate Horsepower:
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Actual Hourly Power Consumption (KW/Hr) = (Motor Capacity + Electric Heating Capacity + Dryer Capacity) x Power Usage Constant (approx. 40%).
Injection Capacity = Injection Pressure (kg/cm²) × Injection Volume (cm³) /
Injection Horsepower PW (KW) = Injection Pressure (kg/cm²) × Injection Rate (cm³/sec) × 9.8 × 100%
Injection Rate V (cc/sec) = π/4 × d² × g Where:
Injection Thrust F (kgf) = π/4 × (D1² ' D2²) × P × 2 Where:
Injection Pressure P (kg/cm²) = [π/4 × (D1² ' D2²) × P × 2] / (π/4 × d²)
Plasticizing Capacity W (g/sec) = 2.5 × (d/2.54)² × (h/2.54) × N × S × / / 2 Where:
System Pressure (kg/cm²) is the highest working pressure set within the hydraulic circuit.
Injection Speed: Speed = Distance / Time
Polymer injection-molding is one of the most used manufacturing processes for the production of plastic products. Its electricity consumption highly influences its cost as well as its environmental impact. Reducing these factors is one of the challenges that material science and production engineering face today. However, there is currently a lack of data regarding electricity consumption values for injection-molding, which leads to significant errors due to the inherent high variability of injection-molding and its configurations. In this paper, an empirical model is proposed to better estimate the electricity consumption and the environmental impact of the injection-molding process. This empirical model was created after measuring the electricity consumption of a wide range of parts. It provides a method to estimate both electricity consumption and environmental impact, taking into account characteristics of both the molded parts and the molding machine. A case study of an induction cooktop housing is presented, showing adequate accuracy of the empirical model and the importance of proper machine selection to reduce cost, electricity consumption, and environmental impact.
Climate change is forcing companies to perform risk management as well as look for opportunities to reduce the environmental impact of their operations [1,2].
The concern regarding the achievement of sustainable development is patent in the literature. Strategies to achieve a cleaner industrial sector have been discussed using, for example, analytical tools that help in the decision-making of an industrial process [3] or linking lean manufacturing practices with the lifecycle assessment methodology in order to reduce the environmental impact [4].
Polymer injection-molding is a standard manufacturing process that is typically characterized by high production volumes [5]. Electricity is required during several steps of this process, from the movements of the machine that allow the closure of the mold, filling the cavity, holding and ejecting of the part, to the plasticizing phase of the polymer and the needs of cooling for both the machine and its parts. In order to carry out these steps of the cycle, injection-molding machines are composed of two different units: the injection unit and the clamping unit. The injection unit is responsible for heating the polymer up to the injection temperature by rotating the screw and using electric resistors. The clamping unit works as a press supplying a clamping force that allows the closure of the mold during filling. To avoid defects in the parts due to partial mold opening, this clamping force should be higher than the one exerted by the injection pressure during the filling phase of the molding process. A wide range of injection machines are used in the industry, with their clamping force being the main distinguishing characteristic. According to the way the movements of the machines are powered, we can divide them into three groups: hydraulic (pumps), hybrid (hydraulic with another mechanism to help the hydraulic system), and electric (servomotors), with the last one being the most well recognized for its more efficient technology.
As injection-molding is an important manufacturing process, analyzing its environmental impact'and identifying ways to reduce it'is of interest to achieve a more sustainable development in the industrial sector.
As discussed in earlier work by the authors, the electricity consumption of the injection-molding process is the main factor that generates environmental impact [6,7]. Due to this, achieving savings in the electricity consumption will not only directly reduce the environmental impact but will also reduce the economic cost.
Therefore, injection-molding producers should have the goal of possessing an in-depth knowledge of their machines in order to ably optimize their consumption, while obtaining these two clearly important benefits.
Life Cycle Assessment (LCA) is a methodology that allows researchers to quantify the environmental impact of a product, process, or service. LCA studies have been applied to a wide range of products in most work fields [8,9,10,11,12,13,14]. Increasing knowledge about the injection-molding process will also lead to an improvement in the LCA field because databases such as EcoInvent, which are used in the Life Cycle Inventory (LCI) phase, are key to the results obtained in LCA studies.
EcoInvent LCI dataset for the injection-molding process is created by calculating the average of three processes'injection-molding of poly(vinyl chloride) (PVC), polypropylene (PP), and polyethylene terephthalate (PET)'and considering an average electricity consumption (1.47 kWh/kg) as well as an average consumption of water, lubricating oils, chemicals, fillers, solvents, packaging materials, natural gas for the factory, generated waste, etc. [15]. However, as previously explained, the highest contribution to the environmental impact is caused by the electricity consumption [6,7].
Not many studies with experimental data of injection-molding and its electricity consumption can be found in the literature. Mianehrow and Abbasian published an interesting study of monitoring energy [16], which analyzed how different factors, such as machine technology or process-related parameters, affect electricity consumption, with the cycle time and throughput (kg processed per hour) being the most important factors. More studies have been published in recent years regarding the environmental impact of the injection-molding process. Thiriez reviewed the complete process, including the compounding of the raw material. In this research, it was indicated that the type of injection-molding machine has a significant impact on the electricity consumption of the process, as will also be seen in this paper [17]. Other authors focused their research on the environmental performance of biodegradable polymers by studying its manufacturing process. They highlighted the necessity of following a holistic approach, considering, at the same time, the influence of the process when designing a part [18,19]. Studies concerning the estimation of electricity consumption of the injection-molding process have been carried out using a theoretical approach instead of experimental, such as the one used in this paper [20,21]. Spiering et al. remarked the importance of deeply analyzing the life cycle inventories of manufacturing processes [22].
In this research work, results from experimental measurements have been analyzed in order to define an empirical model that allows the estimation of electricity consumption of a specific injection-molding process depending on several parameters. Through this empirical model, a more precise value can be obtained to further assess the environmental impact and the costs related to this manufacturing process.
Moreover, the environmental impact of the manufacturing process of the parts used to build the model will be calculated in Section 3.2 using these electricity consumption values as the key for calculation.
A case study will also be carried out in Section 3.3, comparing several scenarios for the manufacturing of a plastic component. Employing this case study, the empirical model can be validated for values outside the ones originally used to create the model, showing the applicability of this model and the implemented methodology.
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