Current Research
Microcellular Nanocomposites
This research aims to advance the fundamental knowledge and process technology for mass-production of lightweight, high-performance, polymer-based nanocomposite parts. The goal is to create a synergistic marriage of two emerging and promising technologies: nanocomposites and microcellular injection molding. Polymer-based nanocomposites represent a new class of materials that offer improved tensile, heat resistance, barrier, and flame retardant properties. Nevertheless, commercialization of nanocomposites has been slow primarily due to high material costs and difficulty mixing nano-fillers with matrix polymers. Microcellular injection molding is capable of producing parts with a microcellular structure that exhibits superior dimensional stability while consuming less material and energy. This process also offers a plausible means to improve impact strength by blunting crack tips with microcells - a property that typically brittle nanocomposites lack. However, injection molding is inherently complex and dynamic as material elements undergo rapid and non-uniform cooling with variable pressure histories. This makes the control of creating fine and uniform microcells throughout the part difficult. Recent research by Professor Turng, Dr. Sarah Gong, and their group has shown that the presence of nano-fillers in microcellular composites helps to produce better cell structures and cell distributions at high weight reductions, while the addition of supercritical fluid to the microcellular injection molding process facilitates dispersion of nano-fillers in the nanocomposite, resulting in a better microstructure and strength-to-weight ratio. So far, this research has generated these benefits by (1) employing nano-fillers as nucleating agents and property enhancers, and (2) employing supercritical fluid to save material and disperse nano-fillers throughout various polymers.
An Innovative Microcellular Co-Injection Molding Process
Since 1976, plastics have been the most widely used materials in the U.S., surpassing steel, copper, and aluminum combined by volume. Among the various plastics processing methods, injection molding accounts for one-third of all polymers processed with a total product value exceeded $181 billion in 2000. This research is aimed at developing the scientific basis for a novel co-injection molding process that combines the aesthetic and processing advantages of injection molding with the benefits and property attributes of microcellular plastics (MCPs) developed at MIT in early 1980's. By integrating solid plastics with MCPs via co-injection molding, synergistic benefits, such as increased productivity, reduced energy consumption, additional design freedom in part geometry, and a means to control the microstructure and properties of the molded products, can be realized. Furthermore, this environmentally benign process is a perfect candidate for recycling of post-consumer plastics. This research under the direction of Professor Turng involves systematic analytical, experimental, and computational efforts to demonstrate the feasibility and advantages of this novel process, advance the understanding of process physics, develop computer modeling and simulation tools, and incorporate the research activities/results into the curricula to stimulate students' interest in advanced research and education. So far, a variety of microcellular co-injection parts have been successfully molded and the results show a very desirable microstructure and promising part quality.
3-D Injection Molding Simulation
Unlike other manufacturing processes, the quality and performance of injection-molded parts depend not only on the material, shape, and function of the part design, but also on how the material is processed during molding. As numerous new materials are being introduced to the market and the product development cycle is constantly compressed, traditional design approaches based on intuition, prior experience, and trial-and-error are quickly becoming less efficient and effective. With the advent of scientific-based computer-aided engineering (CAE) simulation tools, engineers can virtually evaluate alternative designs and materials without physically committing real material and machine time. Through computationally evaluating alternative designs, engineering know-how can be developed quickly and more cost-effectively as compared to molding trials on the shop floor. This research directed by Professor Turng aims to advance the state-of-the-art technology and developments of three-dimensional (3-D) CAE simulation for injection molding. Efforts have been made by Professor Turng's group to review the development of 3-D simulation, the governing equations, and the boundary conditions for 3-D filling and packing. This research also involves the evaluation of various numerical methods and algorithms to solve the governing equations and a variety of treatments derived for more stable and accurate solutions. Additionally, several surface- and volume-tracking methods employed to track flow fronts in three-dimensional geometry, as well as special issues related to three-dimensional simulation, are being studied.
Integration of Computer Simulation with Optimization
It is widely recognized that computer simulation enhances an engineer's capability to manage many important aspects of injection molding. However, there remains a gap between the numerical predictions and the ultimate objective of employing a simulation, which is to achieve optimal design and process set-up parameters. To bridge this gap, research by Professor Turng and his students has integrated a process simulation for injection molding with various optimization algorithms. This integrated system helps engineers determine the optimal design and processing parameters more efficiently and effectively. This research deals with the system implementation and experimental verification of an integrated CAE optimization tool that couples process simulation programs with optimization algorithms to intelligently and automatically determine the optimal design and process variables for injection molding. In addition, this study enables the evaluation and comparison of various local and global optimization algorithms in terms of computational efficiency and effectiveness. To ensure the reliability of the process simulation tool, experimental verifications have been conducted by comparing the predicted and actual linear shrinkage and pressure trace of injection molded test bars and by observing the optical retardation of an industrial precision optical lens. Furthermore, process and design optimization has been performed on the optical lens to minimize cycle time while keeping optical retardation below a specified threshold. With the help of this automated and integrated system, the overall optimization task can be accomplished in a single day instead of the 10 days required by the manual optimization approach.
Intelligent Process/Quality Control for Injection Molding
Injection molding process/quality control has been investigated for many years, especially as part quality requirements become more stringent due to the increased application of plastics. The goals of this research are to critically review the most recent advances in injection molding control and to propose a new intelligent control algorithm that addresses the quality of molded parts while taking into account the variations of material, machine, and process. This research organizes all related works into a multiple-level structure consisting of one feed-forward loop (process setup) and three feedback loops (machine control, process control and quality control). The three feedback loops are cascaded so that the output from the previous controller is the input to the next controller. Typical variables, models, and control methods have been evaluated for different levels of control. However, it has been found that real-sense, on-line quality control is rarely achievable without human intervention due to the lack of transducers for on-line quality response measurement. Based on the research progress to date, it has been concluded that the process/quality model and quality sensor are the two most important areas to further advance injection molding control. Hence, these two areas are the main subjects of this research. This research is being conducted by Professor Turng and his co-workers, including Dr. Z. B. Chen.
Web-based Knowledge Management System
In today's global economy, what an organization knows and how rapidly it learns are crucial to its long-term survival and success. Companies are beginning to realize that their competitive edge relies on the brainpower or "intellectual capital" of their employees and management. Knowledge management is the discipline by which organizations manage and re-use their enterprise-wide knowledge to gain a competitive edge. This research is aimed at developing a structural approach and sustainable knowledge management framework by which organizations such as the plastics companies can create, capture, organize, and manage their own knowledge to maintain a competitive advantage. In this research, systematic work has been conducted to (1) establish a multi-tier system architecture that supports global, secure, real-time, and multi-media communication of information and knowledge among team members separated by great distances, and (2) develop a scalable, high-cohesion, and low-coupling representation of domain knowledge that helps to convert semi-structured information to computer-readable format to assist creation, categorization, organization, retrieval, and sharing of knowledge. So far, a sustainable and scaleable prototype Knowledge Management System (KMS) for creating, capturing, organizing, and managing digital information in the form of Extensible Markup Language (XML) documents and other popular file formats has been developed by Professor's Turng group. A conference paper based on this research has been selected as the Best Paper for the Application of Education Technologies session at the International Conference on Education and Information Systems (EISTA '03).
