Cereals processing technology

44 Cereals processing technology
roller’s entire length, a simple two-dimensional analysis can describe the
system. Other features are that the rollers are rotating towards each other and
their rotational speeds are different. This differential is governed by the ratio of
the drive apparatus that powers the rolls.
Ruffet (1994) performed a theoretical review of the principal parameters
governing the operation of a roller mill using this two-dimensional description.
The parameters examined were power, specific power, the thrust on machine
components and the friction forces exerted on rolls. 16 The theoretical work was
tested for validity in a series of tests that were carried out at an industrial plant
on the first break rolls. In these experiments grinding performance, specific
power requirement, thrust forces, friction forces and differential forces were all
measured.
Brabend (1962) found that the use of large diameter rolls in some instances
avoided the difficulty of excessive thrust forces. Wanzenreid (1970) in his
experiments determined that a roll differential of 1.25 and a roll diameter of
250 mm were optimum for smooth roll grinding of semolina in flour mills.
Scanlon and Dexter (1986) performed similar experiments and in addition
measured flour colour, ash content and starch damage. In addition to finding that
an optimum existed for energy efficiency, it was found that as differential was
increased, starch damage and ash content increased.
3.8 Optimisation of processes
Optimisation refers to the achievement of optimal conditions within processes in
terms of process and economic performance. Optimisation represents a major
opportunity to reduce energy costs and improve quality. Optimisation algorithms
can identify the most economic operating conditions, select the best
combinations and loadings for plant and even determine the best production
schedules to meet requirements and minimise costs. Optimisation techniques are
generally applied in conjunction with the advanced control systems described
earlier.
In order to accomplish optimisation, a variety of steady state and dynamic
models have to be developed for individual unit operations and overall plant
performance. Mathematical techniques are then employed to find inputs to the
models that satisfy operational objectives while meeting quality and other
constraints. In turn these models have to be incorporated into computer
packages, which are user friendly enough to be useful to the process engineers.
Optimisation techniques include (Brinksmeier et al. 1998):
• Linear and quadratic programming.
• Gradient-based methods.
16
A similar treatment of the forces at work in a roller mill is given in the pamphlet on roller mills
produced by Birch (1930).