Dimitris Mourtzis et al. / Procedia CIRP 79 (2019) 574–579
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Augmented Reality based system to support warehouse management, connecting the operators with a central inventory management platform. To verify the proposed design, it is applied in papermaking industry.
by the identification of the possible system configurations [20]. Thomas and Meller presented a statistical-based methodology to develop guidelines, used to design a manual and case- picking warehouse [21]. The aforementioned publications make apparent warehouse design follows a structure sequence of interdependent steps. Nevertheless, there are many differences among the various approaches described above, which steam from the various combinations of design process activities when they are grouped into steps [18]. The past few years, warehouse planning was considered to be a very complex issue due to the absence of the simulation and computing power [3]. In many cases, it was not feasible to experiment on real environment as production rate did not allow to make changes. Nowadays, there are many simulation tools that make warehouse design and planning easier and give to the industry the opportunity to test different scenarios, supporting decision making [22]. A technology that starts to gain ground in industrial applications is Augmented Reality. From knowledge distribution through technical instructions in assembly tasks [23] to remote maintenance support [24], AR is tested in different applications, until it becomes mature enough (both from hardware but also from technical knowledge side) to be fully integrated into manufacturing. Its applicability, as it may be used through various host device, and its mobility has proven to be a great advantage that allows it to be easily used in the production line [25]. Additionally, it has proven to be useful for providing positioning instructions, both in maps navigation but also in large warehouse facilities for inventory management and package retrieval, facilitating the operators to efficiently manage large facilities with changing stocks (such as the case of logistics warehouses) [8]. Based on the aforementioned literature review, it becomes apparent that simulation modelling, in terms of warehouse design, is a one-way selection [26]. This happens due to the fact that simulation models can be extremely valuable, timely and cost-effective means to study the performance characteristics of a proposed warehouse layout. Additionally, novel technologies that may improve inventory management and increase the efficiency of product retrieval in vast warehouses are welcome. Towards that end, this paper suggests a method for warehouse design, considering the integration of mobile devices and Augmented Reality to support product location retrieval by the warehouse operators and efficient inventory management. The developed approach is applied in a papermaking industry for validation. 3 Warehouse design to support Augmented Reality package retrieval This paper presents an innovative and easy to adapt methodology which can give a reliable solution to the problem of warehouse design and simulation that seems to concern the majority of the industries in our days. This methodology aims to keep a high service level while minimizing the inventory costs.
2
State of the art
According to ELA (2004), the capital and operating costs of warehousing in Europe represent about 25% of logistics costs, whilst figures for the USA show that warehousing contributes to about 10% [9]. In spite of warehouse significance in supply chain, there is limited effort in the literature towards that direction [10]. Although, publications show that there is an abundance of information written on analyzing particular aspects of warehouse designing problem, it is the combination of all these aspects that has to be taken into consideration and classified in a strict order so as act as a basis for a successful approach to warehouse design [11]. Warehouse design problems have been early reported in the literature. Oxley [12] presents a comprehensible list of steps which are based on the key features of the previous authors, while also defining the overall system requirements of the supply chain. He emphasizes that the warehouse design should be focused on the storage and handling requirements and that the building should then be designed around these. This basic framework of steps is also enhanced by Rowley [13] with Oxley’s contribution. Simulation models have b een applied since the early 1980’s through basic simulation packages as presented by Ashayeri, et al. [14]. Most of the research done in simulation field is due to the need for optimal warehouse design and planning, where novel technologies could be early adopted. For example, Automated Guided Vehicle (AGV) transport systems where soon adopted in warehouse applications [15]. Gu et al. provided an extensive overview of warehouse performance analysis models, claiming that simulation models are typically used for evaluating one design alternative, but that they are less suited for design-space exploration [4]. Andriansyah et al. presented a layered warehouse simulation model built from reusable components that considers varying number of storage aisles and workstations in a miniload-workstation order-picking system [16]. A further step has been added to the former publication which has to do with the use of computer simulation. Rouwenhorst et al. stated that a design process runs through a hierarchical framework, identifying strategic, tactical and operational decisions [11]. Rushton et al. (2006) have made a refinement of steps in their earlier edition so as to recognize the importance of flexibility in warehouse design issue [17]. The iterative nature of design process is clarified by the equipment and staffing calculations now being presented after the layout design rather than before, as with most other frameworks. Baker and Canessa explored the current literature on the overall methodology design, validated and refined the general results from the literature with reference to warehouse companies [18]. Accorsi et al. applied an integrated decision-support system for the design and management of a storage system [19]. Mital and Krejci presented a modelling framework and an effective algorithm to design material handling systems and warehouses
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