Simulation modelIn order to analyze

Simulation model
In order to analyze the impact of traceability improvements on
the consequences of a safety crisis we simulated recalls in the case
study. To do this, we developed a spreadsheet simulation model
implemented in Visual Basic for Microsoft Excel. These types of
simulation models are often preferable because of the software
usability and availability (Akkerman & van Donk, 2008). The
simulation model is based on a series of parameters that are classified
as constant (C), predetermined (P) or uncertain (U). Constant
parameters refer to parameters that remain unchanged, predetermined
to those that can actively be changed in the model, and
uncertain to unknown parameters (see also Akkerman & van Donk,
2010). For the unknown parameters, a probability distribution is
typically defined and the simulation model randomly chooses
a value for each simulation run. All data used for developing the
simulation model and their classification are shown in Table 1. It
should be noted that wherever a range of values is denoted,
a uniform distribution is used in the simulation.
In the chocolate production process the roasting process
represents a key step for improving the microbiological condition
as well as for defining the aroma profile of the final product (de
Muijnck, 2005). Safety and quality of the finished chocolate
strongly depend on the roasting process. Each batch of cocoa beans
received by the chocolate manufacturer is usually split into several
processing batches, whose dimension depends on the capacity of
the roasting equipment. Thus, each processing batch goes into
a specific roasting process. In this way, if a problem occurs to one
roasting process, only the finished chocolate produced with that
specific roasting process will suffer the consequences of the
problem. The processing batch size is therefore a key (predetermined)
parameter in the simulation model, and an essential
planning decision in practice.