Tahir I. Malik

Process controllability toolbox (PCTB)

Abstract The scope of the paper relates to the introduction of the concepts and functionality of controllability analysis for chemical processes and the development of an X-Window based software package, to be referred to as the Process Controllability ToolBox (PCTB). The application of PCTB to a vinyl chloride monomer (VCM) and polymerisation reactor process is considered. The ease of use which the Graphical User Interface (GUI) based software provides is demonstrated by a typical tutorial session.

A software package for process controllability analysis

Abstract The scope of the paper relates to the introduction of the concepts and functionality of controllability analysis for chemical processes ( Perkins, 1989 ) and the development of a user friendly software package, to be referred to as the Process Controllability Tool Box (PCTB). Process and control engineers in industry may use PCTB to assess plant design alternatives on the basis of their controllability. Alternatively, this can be achieved using dynamic simulation techniques, but with two disadvantages. First, dynamic simulation of a wide range of scenarios is very time consuming and secondly closed loop simulation would require models of actuators and measurement instruments as well as the need for control system structure and parameter tuning to be fully developed for each design option. Whilst there is little doubt that such simulations should be performed to verify the final design, there is a need for a less elaborate technique to aid the process engineer in screening alternatives at an earlier stage in the design process. The PCTB quantifies the inherent controllability characteristics of the plant alternatives on the basis of their mathematical model and provides insight to be used in choosing the best design.

The Virtual Product-Process Laboratory applied to personal care formulations

Abstract The objective of this paper is to illustrate the new advances in the virtual product-process design laboratory (virtual PPD-lab) which has been previously presented [1, 2]. Through the virtual PPD-lab, it is possible to generate and/or analyze alternatives for products and processes matching a set of predefined targets by performing virtual experiments in order to verify product feasibility, identify problems and validate the product. The significance of the virtual laboratory is that the experimental effort during the development of new products and processes can be reduced, sparing therefore, valuable time and resources. This paper highlights the new advances in the capabilities of the virtual PPD-lab and illustrates them through an industrial case study involving the analysis of a hair spray.

Controllability analysis and modelling requirements: an industrial example

Abstract This paper presents a controllability analysis procedure and modelling approach developed to address problems raised by industrial applications of controllability research. Most work on controllability analysis assumes a nonlinear dynamic model as its starting point using linearisation of the model to give a model for frequency domain analysis. Such models may be expensive and difficult to develop. This paper looks at the use of low order empirical dynamic models for controllability analysis. A heuristic controllability analysis procedure is presented which lends itself to the use of simple models and addresses the use of cascade controllers, which are a feature of many industrial problems, in a systematic way. An industrial example is presented and the procedure is applied successfully using simple gain-delay-lag models.

A case study in control structure selection for a chemical reactor

This paper describes the application of a systematic approach for control structure selection to an industrial reactor control problem investigated as part of a collaborative project between ICI and the Centre for Process Systems Engineering. The performance requirements are defined in terms of process constraints, an economic objective and a set of disturbances. The models required for the analysis are then developed. Following a qualitative analysis of the problem, a series of optimisation-based controllability tests are applied ranging from linear steady-state analysis to nonlinear dynamic analysis. These tests consider achievable performance with a multiloop PI(D) controller and with a linear multivariable controller. The performance of these two types of controllers is evaluated and the implications for control of the process is discussed. Finally, the effectiveness of the techniques used is reviewed based on experience on this application.

A comprehensive population balance model of emulsion polymerisation for PSD & MWD: Comparison to experimental data

Abstract A population balance model for emulsion polymerisation has been developed. This model captures PSD and MWD, both of which are key performance indicators for the end latex product. The model employs purely mechanistic kernels and is aimed at maximising predictive capacity. The model is validated against a multi-objective experimental target. The aim is to predict data for PSD, solids, particle number as well as global molecular weight. The experimental system investigated is a vinyl acetate/butyl acrylate copolymerisation with ionic emulsifier and thermal initiator. The predictive capacity is tested by tuning the model to one set of experimental data, then trying to predict results from a further perturbed experiment, with no further tuning. The results of this study indicate that the model is able to capture the main process trends as well as providing an accurate representation of quantitative data.

Rapid process refinement for the development of complex solution copolymers

Abstract The industrial manufacture of specialty free radical solution copolymers (FRPs) requires use of a variety of solvents and co-monomers based on the desired properties and end-use. The polymer composition, polymerization solvent, and process parameters have a significant impact on polymer properties such as copolymer composition and polymer molecular weight distribution (MWD). The scale-up and trouble-shooting of copolymerization processes is a significant challenge for the specialty polymers industry due to short project time-scales, limited resources available for each project, and the use of newly developed proprietary monomers. We present approaches that combine process systems and experimental approaches to support data and knowledge-based decisions in the context of live projects under commercial time constraints with only limited data available. These approaches are used for the evaluation and improvement of a batch process operating under reflux conditions that exhibits a large change in solvent boiling point due to the use of high boiling monomers. The approaches allow rapid process refinement and include thermodynamics and heat transfer considerations decoupled from the complexity of reaction kinetics and chemistry with assumptions on heat release rates. Controllability analysis can be carried out at different stages of the batch, sensitivity to the selected solvent tested, and recommendations made on solvent use and process conditions. In addition, we also present an innovative, sparse matrix-based representation of chain length dependent rates that has potential to deliver rapid solutions without loss of detail of MWD.

Rapid process design and development of complex solution copolymers

Abstract New, compositionally complex, Free Radical, solution co-Polymers (FRPs) are synthesized in our research laboratories to develop specialty materials with very specific and challenging combinations of product properties for advanced technology end applications. The co-polymer composition and polymer molecular weight distribution (MWD) are key factors in achieving the required properties and need to be reliably maintained in the scaled-up processes. We present significant developments involving use of thermodynamics, dynamic heat transfer, heat and mass balance models as well as polymerization kinetics models combined with selective experiments to rapidly progress to pilot and full scale production despite limited data. We also report development of a new, innovative, sparse matrix based representation for chain-length dependent polymerization kinetics that has potential to deliver rapid solutions without loss of detail for MWD. Future publications will elaborate each aspect further.