Sensors Target Plastics Industry

What comes to mind when the word “plastic” is mentioned? Computer keyboards, cell phone cases, beverage bottles, or medical implants?  The answer is, plastics are in all of them. In fact, plastics are found in virtually every facet of contemporary life, from industrial products (such as automotive parts) to consumer products (e.g. refrigerators). Many of these products are manufactured in injection molds of myriad – often complex – shapes and sizes, using polymer blends that possess just the right properties desired for the intended applications.

For decades, plastics have been popular due to their low cost and durability. Because plastics are made from petroleum, as supplies of oil decline or become less available, and as the price trends higher, the need to reduce waste and ensure product quality in plastics manufacturing is gaining greater urgency.

Robert Gao, Pratt & Whitney Chair Professor in Mechanical Engineering at UConn, and David Kazmer, a professor of plastics engineering at UMass-Lowell, have been engaged in research that promises to help the U.S. plastics industry operate more efficiently, economically and environmentally friendly.

In injection molding, plastic pellets are fed into a rotating, drill-like barrel where they are subjected to high temperatures and pressures that convert them to a molten state.  The molten plastic is then forced through a nozzle into the mold cavity.  Once the cavity is completely filled, the plastic in the cavity cools down.  The mold then opens and the shaped product is ejected. The cycle then starts all over again. The illustration on the left depicts the major components of an injection molding machine.

According to Dr. Gao, the plastics industry is the nation’s third largest manufacturing sector, with nearly $374 billion in annual shipments. However, the process of injection molding, like any manufacturing process, isn’t 100% exact, and flaws can reduce the quality of the end product. For example, fracture lines may emerge from non-uniform temperatures across the mold, the mold cavity may fill incompletely due to air pockets, etc. These flaws can cost the manufacturer significantly in terms of energy, wasted feedstock, reduced productivity, and ultimately, reduced profitability.

The plastic industry has been looking for technological breakthroughs that will enable manufacturers to better see how the molding process has taken place within the cavity, in order to better control the process and part quality. However, the difficulty of accessing the mold cavity, together with the harsh environmental conditions within it, present major roadblocks.  As a result, process measurements are generally done external to the cavity, and manufacturers rely upon general “rules of thumb” to drive the process.  The ability to detect process parameters in real time, within the mold and without affecting the process itself, could offer manufacturers much improved predictability.

Supported by a recent grant of $553k from the National Science Foundation, Drs. Gao and Kazmer are set to  develop a novel sensing method to improve the observability and controllability of injection molding – first through computer simulation and then through experimental evaluation on a real-world molding machine. They believe that miniaturized acoustic sensors, embedded within a mold, could provide valuable information about the processes taking place as the molten plastic undergoes the processes that shape it.

They envision the deployment of an array of such sensors within the injection mold, flush with the surface of the cavity. Such a sensor array will capture the melt temperature, pressure, velocity, and viscosity in real time during the process, and wirelessly transmit the data to an external receiver, by means of coded acoustic waves.  Through advanced signal processing algorithms, these critical parameters can be recovered.

The two professors, who have been research collaborators since the late 90’s, bring complementary skills to the team: Dr. Gao is an expert in physics-based sensing and wireless communications, while Dr. Kazmer specializes in polymers and process control.

Dr. Gao anticipates that the sensing method resulting from this research will enable insight into the mechanism and dynamics taking place inside the mold, and enable optimization of the molding process through the synergistic effort with Dr. Kazmer. As a result, manufacturers can improve process control, reduce waste generation and save energy.

Dr. Gao’s expertise in sensing, mechatronic system design, and signal processing holds diverse applications beyond manufacturing. One project sponsored by the Genes and Environment Initiative (GEI) of the National Institutes of Health pairs him with researchers in kinesiology and mathematics. His laboratory has recently developed a sensory device that can be worn on the body to continually monitor human breathing frequency, respiration volume, and body movement.  Based on the real-time data provided by the sensors, the team has developed algorithms to analyze how intensively people have worked out, and how they have been exposed to environmental pollutant as a result of their physical activities. It’s one of many research projects that benefits from his close understanding of mechanics and physical/electrical principles. Read more about Dr. Gao’s research here.