A simulation-based assessment of service-oriented supply models on the performance of warehouse robotic solutions

Compounded by complex demand requirements and scarcely available workforce, firms are seeking alternatives to traditional warehousing systems, favouring robotized solutions able to increase productivity while maintaining high flexibility. The diffusion of such solutions has been lately associated with business models that, moving towards service-oriented offer configurations and financial models, promise to improve resources’ utilization and automation expenditures, especially in contexts of high uncertainty and dynamicity. Despite emerging as a relevant trend among robotics manufacturers and logistics system integrators, the value that service-oriented supply models could bring to warehouse performance is still widely unexplored. This work aims at addressing this gap, assessing the impact of service-oriented supply models on the financial and operational performance of warehouse robotic solutions and their suitability to contexts of different demand variability. For this purpose, an exploratory simulation study was carried out. Two alternative strategies for the supply of an autonomous mobile robot fleet in an order picking system were simulated and their impact on system performance was quantified. A sensitivity analysis based on real-life suppliers’ data uncovered the extent to which different contextual demand and supply characteristics impact operational and financial warehousing performance. Such analysis resulted in the identification of convenience areas for the two supply models. Results contribute to nascent literature on service-oriented supply models in warehousing, serving as a base for future research and providing insights to both firms seeking to adopt robotic solutions and technology providers in shaping their offerings.