Product scheduling for thermal energy reduction in papermaking industries

Papermaking is considered as an energy-intensive industry partly due to the fact that the machinery and procedures have been designed at the time when energy was both cheap and plentiful. A typical paper machine manufactures a variety of different products (grades) which impose variable per-unit raw material and energy costs to the mill. It is known that during a grade change operation the products are not market-worthy. Therefore, two different production regimes, i.e. steady state and grade transition can be recognised in papermaking practice. Among the costs associated with paper manufacture, the energy cost is 'more variable' due to (usually) day-to-day variations of the energy prices. Moreover, the production of a grade is often constrained by customer delivery time requirements. Given the above constraints and production modes, the product scheduling technique proposed in this paper aims at optimising the sequence of orders in a single machine so that the cost of production (mainly determined by the energy) is minimised. Simulation results obtained from a commercial board machine in the UK confirm the effectiveness of the proposed method. © 2011 IFAC.

Simulation-based optimal sensor scheduling with application to observer trajectory planning

The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous. This general case is important as it is the natural framework for many applications. The aim is to minimise the variance of the estimation error of the hidden state w.r.t. the action sequence. We present a novel simulation-based method that uses a stochastic gradient algorithm to find optimal actions. © 2007 Elsevier Ltd. All rights reserved.