|dc.description.abstract||Blends of poly butylene terephthalate (PBT) and polycarbonate (PC) form a very important class of commercial blends in numerous applications requiring materials with good chemical resistance, impact resistance even at low temperatures, and aesthetic and flow characteristics. PC and PBT are usually blended in a twin screw extruder (TSE). Product melt volume flow rate (MVR) is a property used to monitor product quality while blending the PC/PBT in a twin screw extruder. It is usually measured off line in a quality control laboratory using extrusion plastometer on samples collected discretely during the compounding operation. Typically a target value representing the desired value of the quality characteristics for an in-control process, along with upper and lower control limits are specified. As long as the MVR measurement is within the control limits, the sample is approved and the whole compounded blend is assumed to meet the specification. Otherwise, the blend is rejected. Because of infrequent discrete sampling, corrective actions are usually applied with delay, thus resulting in wasted material.
It is important that the produced PC/PBT blend pellets have consistent properties. Variability and fault usually arise from three sources: human errors, feed material variability, and machine operation (i.e. steady state variation). Among these, the latter two are the major ones affecting product quality. The resulting variation in resin properties contributes to increased waste products, larger production cost and dissatisfied customers. Motivated by this, the objective of this project was to study the compounding operation of PC/PBT blend in a twin screw extruder and to develop a feasible methodology that can be applied on-line for monitoring properties of blends on industrial compounding operations employing available extruder input and output variables such as screw speed, material flow rate, die pressure and torque.
To achieve this objective, a physics-based model for a twin screw extruder along with a MVR model were developed, examined and adapted for this study, and verified through designed experiments. This dynamic model for a TSE captures the important dynamics, and relates measurable process variables (screw speed, torque, feed rates, pressure etc.) to ones that are not being measured (material holdups and compositions at the partially and filled section along a TSE barrel). This model also provides product quality sensors or inferential estimation techniques for prediction of viscosity and accordingly MVR. The usefulness of the model for inferential MVR sensing and fault diagnosis was demonstrated on experiments performed on a 58 mm co-rotating twin-screw extruder for an industrial compounding operation at a SABIC Innovative Plastics plant involving polycarbonate – poly butylene terephthalate blends.
The results showed that the model has the capability of identifying faults (i.e., process deviation from the nominal conditions) in polymer compounding operations with the twin screw extruder. For instance, the die pressure exhibited a change as a function of changes in raw materials and feed composition of PC and PBT. In the presence of deviations from nominal conditions, the die pressure parameters are updated. These die pressure model parameters were identified and updated using the recursive parameter estimation method. The recursive identification of the die pressure parameters was able to capture very well the effects of changes in raw material and/or composition on the die pressure. In addition, the developed MVR model showed a good ability in monitoring product MVR on-line and inferentially from output process variables such as die pressure which enables quick quality control to maintain products within specification limits and to minimize waste production.||en