SIMULATION
One tool consistently under-utilised by the food industry is that of simulation. Simulation is the use of a mathematical model or models to describe the relationship between the parameters that can be observed in a particular system. The food industry has been neglected quite seriously in terms of simulation tools despite the significant potential of such applications. Simulation is a valuable tool for the development of a new process or the alteration of an existing one. It can be very cost-effective in comparison to carrying out full-scale trials in the plot plant. Calculations based on different conditions can be carried out rapidly on a computer yielding the results in a very short time. Full-scale experiments can thus be rationalised with considerable financial and time savings. If a production plant is to be made more efficient, with greater productivity and improved quality assurance, greater knowledge of the process allied with data on the raw material and product is required. The development of model systems is also important. Increased knowledge of the physical process can save money and lead to better quality in the end-product (Skjiildebrand et al., 1993).
This project has used BATCHES from Batch Process Technologies for all necessary simulation work to date. Although not written specifically for the food industry it offers a degree of adaptation which makes it useful for applications in the food industry. It has already been successfully applied to the simulation of a brewhouse operation in a Belgian brewery (Mignon & Hermia, 1992, 1994). BATCHES has the ability to simulate both batch and semicontinuous processes in the biochemical, food and pharmaceutical industries. It is a data driven package. A BATCHES simulation model consists of three buildings blocks:
- equipment
- recipe network
- sequencing information
The BATCHES model allows the user to (1) evaluate alternative system configurations and operating procedures, (2) identify bottlenecks, (3) assess the requirements for capacity expansion, and (4) evaluate scheduling strategies. The output obtained consists of graphs, and a comprehensive summary report containing a mass balance summary, equipment and resource utilisation statistics, cycle time and waiting time information and, finally, time lost due to waiting for materials and resources. BATCHES is currently being used to develop a simulation model for a local brewery.