Feedback to user needs, requirements and preferences

The performance indicators in the last three columns of the results of Table 1 are important values for the primary and secondary users, mentioned in Chapter 3. The requirements of no water stripes and minimal coverage, are implemented in the algorithm script beforehand and are achieved this way. However, the performance requirements have still to be met. A cleaning speed of a speed of 125 m2/hr was desired. From the results however, it can be seen that this goal is far from reached. With a maximum of 27.30 m2/hr, the zigzag algorithm is the closest to the goal. This large difference in cleaning speed can be explained through the interpretation of the definition of cleaning speed. It is assumed that the manufacturers meaning of the term is the surface area covered by the robot, but not specifically fully cleaned. The current modeled algorithms cover specific areas multiple times in order to clean the window. This repeatedly traveled distance is not taken into account in the definition of the cleaning speed as derived from the results of the model. Besides that, a contradiction emerges when the cleaning speed and the reference algorithm are compared. The standard algorithm represents the state-of-the-art algorithm, however it does not hold up with the specifications of the state-of-the-art robots. Despite not corresponding with the state-of-the-art specifications, the zigzag algorithm is still faster than the reference algorithm, meaning that the time taken to clean a window is shortened which is beneficial for both window cleaning companies and for individual clients.

The requirement for the water consumption was equal to 0.25 L/min. From the results it can be seen that both developed algorithms are far from reaching this value, which is a positive result. For the window cleaning companies, the choice to either save time or water is now based on the results of the test. However, it is assumed that the profit on time-savings is more relevant than the earnings on water-savings. If the individual client is the supplier of the water, which is likely, the chance that the window cleaning company could change its algorithm for a particular job based on feedback could increase.