Analysis of the relationship between available information and performance in facility logistics

Regarding the amount of processed information, there are two basic approaches to handle today’s increasing requirements for facility logistics systems. First, the collection of all achievable information about the system and its load in order to predict future system states accurately; theoretically, this could lead to optimal results. Second, the use of rather simple heuristics with less need for information but higher flexibility and robustness instead. This approach is for instance being realized with the Internet of Things in facility logistics. This paper analyses the dependency of throughput time and capacity utilization on available information for two limiting cases. While a ‘best possible’ case assumes that the material flow control has all relevant information about the system and loads, a ‘worst reasonable’ case considers the same for very limited information. The influence of layout, throughput, and element availabilities on this relationship is analyzed for both cases on the basis of a scalable generic test system and steady flow situations. In total, nine simulation studies are conducted and analyzed regarding throughput time and element utilization as performance indicators. Implications for the importance of information on performance depending on system complexity are discussed, and directions for further research are provided.