Jose M. Castro

Recursive approach to copolymerization statistics

Abstract A new method is presented for calculating average values of molecular weight, chain length and sequence distributions in linear copolymerization. The method provides a considerable expedient to these results over most other approaches since the average values are calculated directly, bypassing the calculation of distributions themselves. The approach is applicable to polymerizations possessing a first order Markovian statistical character, and relies on the recursive nature of this type of chain. Several examples are given, some new results for the AA, BB, CC (urethane-like) system are obtained and the recursive approach is contrasted with older approaches.

Modelling and simulation in reactive polymer processing

Modelling and simulation in reactive polymer processing have been active research areas for the past decades in academic institutions as well as within the industry. Both areas have played a key role in advancing and optimizing reactive polymer processing operations. The objective of this paper is to review the two major classifications of models used to simulate polymer processes: physics based models and empirical models. Additionally, a section on multiple criteria optimization using data envelopment analysis has been included for completeness. The work presented here helps define a decision-making framework for the creation of reactive polymer process models and for the effective selection of settings of the process variables based on these models.

Simultaneous Optimization of Mold Design and Processing Conditions in Injection Molding

Injection molding (IM) is considered the foremost process for mass-producing plastic products. One of the biggest challenges facing injection molders today is to determine the proper settings for the IM process variables. Selecting the proper settings for an IM process is crucial because the behavior of the polymeric material during shaping is highly influenced by the process variables. Consequently, the process variables govern the quality of the part produced. The difficulty of optimizing an IM process is that the performance measures (PMs), such as surface quality or cycle time, that characterize the adequacy of part, process, or machine to intended purposes, usually show conflicting behavior. Therefore, a compromise must be found between all of the PMs of interest. In the past, we have shown a method comprised of Computer Aided Engineering, Artificial Neural Networks, and Data Envelopment Analysis (DEA) that can be used to find the best compromises between several performance measures. The analyses presented in this paper are geared to make informed decisions on the compromises of several performance measures. These analyses also allow for the identification of robust variable settings that might help to define a starting point for negotiation between multiple decision makers. Future work will include adding information about the variability of PMs on the DEA analysis and the determination of process windows with efficiency considerations. This paper discusses the application of this method to IM and how to exploit the results to determine robust process and design settings.

Development of a service-simulating, accelerated aging test method for exterior tire rubber compounds I. Cyclic aging

Aging of tire rubber compounds in real service is affected by multiple factors. This process cannot be accurately represented by conventional single-factor tests. A novel cyclic aging test is proposed as a multiple factor, service simulating, accelerated aging test method. It includes four sub-tests of oxygen bomb, dynamic ozone, ultraviolet light, and water solution attack. The proposed cyclic test is compared against thermal, dynamic ozone, and dynamic outdoor aging by characterizing material property degradation as a function of aging time. Four formulations of exterior tire rubber compounds are used as experimental materials. The experimental results show that the proposed cyclic aging test is closer to dynamic outdoor aging than the conventional dynamic ozone and thermal aging tests. The static modulus increases with thermal aging, and decreases with dynamic ozone aging time. For dynamic outdoor and cyclic aging, the modulus initially increases, but then later decreases, showing traces of both of the previously mentioned results. It is also found that the size of the specimen has a significant affect on aging. Such effect can be utilized to accelerate the artificial aging without elevating the temperature.

MULTIPLE QUALITY CRITERIA OPTIMIZATION IN REACTIVE IN-MOLD COATING WITH A DATA ENVELOPMENT ANALYSIS APPROACH II: A CASE WITH MORE THAN THREE PERFORMANCE MEASURES

Sheet Molding Compound (SMC) is a widely utilized material to manufacture automotive exterior body panels. Compression molded SMC parts are often coated with the objective to provide additional surface properties, provide environmental protection, and/or enhance aesthetics. One of the most rapidly increasing coating methods is called In-Mold Coating (IMC) in which a liquid thermoset is injected onto the surface of the cured SMC part while this is still in the mold. Cycle time, dimensional consistency, and surface finish are among the most important performance measures (PMs) to consider in the production of SMC due to their impact in profit and quality, hence these measures are also important when using IMC. Frequently, the PMs exhibit conflicting behavior i.e. lowering the cycle time might imply decreasing the part surface quality and/or achieving a lower overall part dimensional consistency. For this reason, one must exercise especial care to identify the best compromises between the PMs along with the processing conditions that result in these best compromises. The task of finding the best compromises poses a multiple criteria optimization problem. This paper describes an application of IMC to SMC where the multiple criteria optimization problem is addressed with a non-parametric approach known as Data Envelopment Analysis (DEA). The use of a graphical approach to identify the best compromises is not possible in the case presented here because four PMs have been included. This fact makes the use of the proposed approach completely necessary to solve the problem at hand.

Multiple quality criteria optimization in reactive in-mold coating (IMC) with a data envelopment analysis approach

Reactive in-mold coating (IMC) products have been used successfully for many years to improve the surface quality of Sheet Molding Compound (SMC) compression molded parts. IMC provides a smooth, sealed surface used as conductive or non-conductive primer for subsequent finished painting operations. The success of IMC for SMC parts has recently attracted the interest of thermoplastic injection molders. The potential environmental and economic benefits of using IMC as a primer and, in the ideal case, to replace painting completely are large. Most optimization studies in Reactive Polymer Processing involve a compromise between different performance measures. In most cases the controllable variables have a conflicting effect on the relevant performance measures. IMC is not the exception. These performance measures need to be balanced, each against the other, in order to obtain the best compromise. The ideal compromise will depend on the final part quality requirements. In this work, the use of Data Envelopment Analysis (DEA) is explored to identify the best compromises among several performance measures. We have selected two case studies to illustrate the use of this technique. In the first case, we apply DEA to select the locations for two IMC injection nozzles for a thermoplastic part to optimize two quality measures. In the second case, we study the simultaneous optimization of cycle time, surface quality, and dimensional consistency for SMC parts. The first case is aimed to demonstrate the application of DEA with a simple example; in fact, the best compromises in such example could have been identified graphically. The second case, however, provides an example where the multidimensionality of the problem makes the use of DEA critical to elicit a proper solution.

Improving mixing efficiency of a polymer micromixer by use of a plastic shim divider

In this paper, a critical modification to a polymer based affordable split-and-recombination static micromixer is described. To evaluate the improvement, both the original and the modified design were carefully investigated using an experimental setup and numerical modeling approach. The structure of the micromixer was designed to take advantage of the process capabilities of both ultraprecision micromachining and microinjection molding process. Specifically, the original and the modified design were numerically simulated using commercial finite element method software ANSYS CFX to assist the re-designing of the micromixers. The simulation results have shown that both designs are capable of performing mixing while the modified design has a much improved performance. Mixing experiments with two different fluids were carried out using the original and the modified mixers again showed a significantly improved mixing uniformity by the latter. The measured mixing coefficient for the original design was 0.11, and for the improved design it was 0.065. The developed manufacturing process based on ultraprecision machining and microinjection molding processes for device fabrication has the advantage of high-dimensional precision, low cost and manufacturing flexibility.

Setting the Processing Parameters in Injection Molding Through Multiple-Criteria Optimization: A Case Study

In this correspondence, a case study involving statistical characterization and multiple criteria optimization on injection molding is presented. This case study is the first application of a method previously described in the literature involving data envelopment analysis geared toward setting design and process variables to meet several performance measures.

Effective Mass Diffusivity in Composites

Gas diffusion is important in composite manufacturing, while moisture diffusion is important for composite performance. In this study, analytical models are developed to predict the mass diffusivity of both square and hexagonal arrays of cylindrical cylinders. These models are able to bridge the gap between continuum calculations via finite differencing of finite element analysis and simple/trivial models. By breaking the liquid region into zones and making some general assumptions about the diffusion in those zones, simplified models have been developed, which rely solely on the geometry and fiber volume fraction. The models are fairly accurate for a broad porosity range, but specially at low porosity values. A single weight factor is proposed to compensate for the error introduced by the model assumptions. When the weight factor is incorporated, the modified models agree extremely well with the experimental data for the whole porosity range.

A Viscometer for Fast Polymerizing Systems

A parallel‐disk viscometer capable of measuring the viscosity rise isothermally for fast polymerizing systems has been designed and characterized. Criteria for isothermal operation are given. The viscometer has been specifically designed for polyurethane chemical systems used in reaction injection molding (RIM) and is adaptable enough to be coupled directly to various commercial RIM machines. Some minor modifications may be needed for other reactive systems. The viscometer in its present design is not highly precise, but is rugged and inexpensive.