A pressure-temperature dual sensing methodology for injection molding monitoring

2009 2009

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Abstract (summary)

Injection molding is a widely employed manufacturing process in modern industry for mass production of plastic parts. Of the various parameters that affect the quality of injection molded products, the pressure and temperature distribution within the mold cavity are the most critical factors, as improper setting of the filling pressure or cooling speed may lead to defects such as sinks, flashes, or short shots. With increasing mold complexity and the related high cost to structurally modify the mold for sensor accommodation, the ability to integrate multiple, miniaturized sensors within the mold cavity for on- line, multi-point pressure and temperature distribution measurement while minimizing mold structure modification becomes highly attractive to the industry.

This thesis presented the design of a self-energized, acoustic wireless sensing methodology for the simultaneous measurement of pressure and temperature right at the mold cavity, within one sensor package. The sensor harvests energy from the pressure variation of the polymer melt during the injection molding process, and utilizes ultrasonic pulses as the carrier to wirelessly transmit pressure and temperature information through the injection mold. A significant advantage of the designed sensing method is that it avoids drilling through-holes in the injection molds or holding plates, which are costly to implement but necessary for installing traditional wired sensors, thereby allowing multiple sensors to be embedded within a complicated mold structure to improve the observability of the polymer state during the injection molding processes.

Research conducted in this thesis addresses four aspects of the complete solution: (1) Design of a dual-parameter modulation method suited for injection molding environment, (2) Structural optimization of the energy harvesting component, known as a piezoceramic stack, for a minimal volume of the stack while maintaining the minimum Signal-to-Noise Ratio required for reliable signal reception, (3) Design of a multi-layer ultrasound transmitter for effective transmission of the ultrasonic pulses through injection mold steel, and (4) The investigation of signal propagation within the mold cavity and the optimal localization of the receiver to obtain maximum signal strength on the back surface of the injection mold.

The developed sensing methodology was systematically evaluated through experiments using a sensor prototype on a Milacron T100 injection molding machine. States of the melt at multiple locations in the mold cavity were retrieved from the sensor data to provide real- time process feedback for the machine controllers. This information will enable the development and widespread implementation of state variable control algorithms for injection molding to reduce the time required for process set-up and stabilization, and improve part quality and consistency. The energy harvesting and signal modulation mechanisms developed from this research provide a new means to power sensors for the condition monitoring and health diagnosis of dynamic systems and processes in a broad range of applications.

Indexing (details)

Mechanical engineering
0548: Mechanical engineering
Identifier / keyword
Applied sciences; Dual parameter sensing; Injection molding; Sensors; System monitoring; Ultrasound communication
A pressure-temperature dual sensing methodology for injection molding monitoring
Fan, Zhaoyan
Number of pages
Publication year
Degree date
School code
DAI-B 70/12, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
Gao, Robert X.
Committee member
Chait, Yossi; Gong, Weibo; Kazmer, David O.
University of Massachusetts Amherst
Mechanical Engineering
University location
United States -- Massachusetts
Source type
Dissertations & Theses
Document type
Dissertation/thesis number
ProQuest document ID
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
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