Heineken's goal with respect to safety is to reduce the number of accidents to zero. Such a drastic reduction can only be achieved by considering safety as early as in the design phase, when most impact can be made. Therefore, the purpose of this research is to enable the easy generation of different design concepts and evaluate them with regard to safety. Since most accidents currently occur in Heineken's warehouse loading areas, this is the area considered in this thesis. In order to evaluate the generated designs with respect to safety, safety has been quantified into a single value, the risk level. This risk level is the result of the possible consequence of an accident (the impact), the number of times an activity is expected to occur (the frequency) and the chance that this activity results in an accident (the probability). These values depend on the type of accident, or hazard, which is any unsafe condition or potential source of an undesirable event with potential for harm or damage. The hazards corresponding to the top three most occurring accidents have been identified and have been evaluated. For the generation and evaluation of design concepts, a parametric model has been developed. By changing parameters, designs with different operating processes, equipment types, layouts, and more, can quickly be generated and visualised for the designer. Also the movements that occur in the warehouse area can be simulated. The model counts the number of times a hazard occurs and determines the corresponding frequency score. The scores for the impact and probability are based on expert opinion. The risk level is subsequently calculated. Using the parametric model, the risk level resulting from the twelve most occurring hazards in the warehouse loading area of Heineken is evaluated for different scenarios. The findings show that the current method that is used to determine the frequency score is not suitable for activities that typically occur a lot, which is the case in the warehouse loading area. Therefore, an alternative method is proposed, which uses an exponential distribution to score the number of times that a hazard can occur. By analysing design choices regarding the type of picking process (directly from warehouse, using cross-docking or using pre-staging), the level of automation, the number of aisles, the distance between loading points and designing crossings on a different level, the preferred design choices are found.