Cereals processing technology

5. Dynamic modelling of the process.
6. Development of a supervisory control strategy specific for a given process.
7. Testing and tuning of the developed control strategy/controller by
simulation.
8. Implementation of a pre-tuned controller.
The utilisation of high performance computer systems for automation allows
the application of advanced control techniques to overcome existing dynamic
limitations in processes, particularly if older mechanical equipment is utilised.
Case studies have demonstrated that steady state optimisation provides the basis
to increase plant throughput up to 15 per cent (Keintzel et al. 1998). Subsequent
dynamic optimisation minimises the effort required for control system design
through off-line evaluations and potentially provide a further 10 per cent gain.
3.8.4 Flour mill optimisation to date
Niernberger and Phillips’ (1972) work is typical of the application of computer
techniques to the milling industry. In this case linear programming methods are
employed to optimise wheat grist formulation. The paper by Liu et al. (1992)
demonstrates a similar approach twenty years later but encompassing a broader
range of parameters. Their work produced a model of the milling process, but
made no attempt to optimise the process.
Willm (1985) demonstrated the manner in which mill optimisation is
performed currently. This is an effective method of optimisation but it is totally
empirical. The analysis discusses the practice of visiting the production site,
visually assessing materials and acting on the observations based on experience.
This practice is effective where the individual is experienced but once this
person leaves the site the experience leaves with him and performance can only
deteriorate from that point.
Takahashi et al. (1990) developed a knowledge-based system whose function
was to store in a hierarchical fashion all parameters associated with a particular
process flow. A user interface was developed which enabled unskilled operators
to retrieve and store relevant information. Such a system could be developed
further to incorporate models of the process. This application was merely a
database that stored all mill technical parameters in a structured manner for
intuitive data recovery. No analysis or manipulation of the data was performed.
Moss et al. (1991) provide an example of how training and staff development
within the flour milling industry is practised. The objective of all training
programmes is vocationally oriented and so the finer points of optimising
processes are lost on trainees.
Odhuba (1999) developed models of the breakage of wheat at first break and
used the General Algebraic and Modelling System (GAMS) 19 to optimise the
non-linear models obtained. This is the first piece of work in this field that aims
19 GAMS is a proprietary computer-based optimisation package.
Wheat, corn and coarse grains milling 47