Comparison of Three Order Picking Support Systems with Respect to Sequencing Storing : A simulation study of supply methods

Abstract: Background In recent decades, industrial processes have been moving towards more automated solutions. Despite this, some processes have fallen behind and not been as developed as others. The picking process can account for up to 55% of inventory operating costs for companies, which is why one tries to find new methods in hope of making the process cheaper and more efficient.   Today, the order picking processes are still at about 80% fully manually controlled. However, various picking support systems have been developed to make the process more efficient, but more research is needed in the area to help companies make decisions about which system that is best for implementation.   Purpose The purpose of this study was to investigate and determine which of the two support systems, Pick to Voice and Pick to Light that performs betterin terms of time, error and workload. To put the results into perspective, the study also includes a fully manual method of picking, Pick by Paper. The intention is giving companies more basis in their choices when implementing a picking support system in their business.   Methods This study was conducted together with Scania, which distributes transport solutions worldwide. They provided us with space and the resources to conduct physical simulations in their warehouse and made staff available to participate and answer a survey. Simulations were conducted on two different articles for each of the picking support systems. Data were collected from both the questionnaires and simulations and were compiled and statistically tested in SPSS.   Results The results show that there are significant differences between the different picking support systems both in terms of time and workload. It also showsthat frustration and mental demand were the two factors that have the greatest impact on workload according to the participants in this study.   Conclusions The conclusions that can be drawn from this study are that the partially automated picking support systems performs better and have less workload than the fully manual method. Pick to Light proved to be the best of the partial automated picking support systems, both in terms of time and workload.