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Research Papers

Characterizing Energy Consumption in Injection Molding: Model Versus Logger

[+] Author and Article Information
Andrea Sánchez-Valencia

Smithers Rapra, Ltd.,
Shawbury SY4 4NR, Shropshire, UK
e-mail: ASanchezValencia@smithers.com

Julien Loste

Smithers Rapra, Ltd.,
Shawbury SY4 4NR, Shropshire, UK
e-mail: JLoste@smithers.com

1Corresponding author.

Manuscript received June 28, 2017; final manuscript received October 16, 2017; published online January 3, 2018. Assoc. Editor: Karl R. Haapala.

J. Manuf. Sci. Eng 140(3), 031013 (Jan 03, 2018) (10 pages) Paper No: MANU-17-1397; doi: 10.1115/1.4038294 History: Received June 28, 2017; Revised October 16, 2017

Recent changes in legislation along with environmental initiatives to drive sustainability and reduce carbon emissions have sprouted the development of energy models to characterize manufacturing processes. In the case of injection molding, much work has been performed in coupling sensors with control statistical systems to promptly identify process' instabilities, such as pressure drops or fluctuations in the filling point. Latest energy models for injection molding make use of injection pressure and temperature parameters that are a function of the machine, mold geometry, and process characteristics. The latest state-of-the-art way to measure energy consumption is through the use of energy loggers, which provide power data at the end of the production cycles. Although seemingly correlated, little has been published on the extrapolation of cavity signals for their use in energy calculations. In this study, the advantages and disadvantages of using cavity sensors in injection molding are explored; a novel approach to the use of cavity sensors' pressure and temperature data is proposed by exploring their input in an energy model for the estimation of specific energy consumption (SEC). The model was validated against power data obtained via an energy logger; the averaged energy reported by the model indicated a range of 60–67% accuracy.

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Figures

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Fig. 1

Molded part used for the injection molding study: (a) dimensions and flow systems are indicated, along with a (b) accompanying isometric view

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Fig. 2

Location of sensors in the injection mold used

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Fig. 3

Cavity pressure profile. Adapted from Refs. [8] and [16].

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Fig. 4

DOE results for the cavity pressure near the gate (left) and cavity pressure at the end-of-fill (right), along with the process temperature

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Fig. 5

Power data as a function of experiment no. obtained from the energy logger

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Fig. 6

Comparative plots of the SEC data of the energy logger (-logg) compared against that obtained theoretically (-th)

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Fig. 7

Predictive accuracy of the SEC energy model as a function of varying parameter, Tinj. Logger data are representative of experiment A02.

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