IoT usage in warehouses and their advantages and disadvantages

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Order picking

The picking process is interconnected with the storage process. Factors such as the storage location assignment are having tremendous effects on the order picking. The goal of the picking process is to minimise the travel distance of the picker which entails that the storage locations needs to be properly established in order to receive positive results in picking (Elbert, Franzke, Glock, & Grosse, 2017; Li, Huang, & Dai, 2016). The actual connection with the storage process starts with the picking of goods out of the storage area in order to fulfil the needs of customers or production orders (De Koster et al., 2007; Elbert et al., 2017; Lu et al., 2016). Picking is a crucial link to other warehousing processes and can have considerable effects for the in-time delivery to the end-consumer (De Koster et al., 2007; Lu et al., 2016). An uncertain picking process can moreover not only affect the customer but also truck drivers who have to deal with waiting-times (Zhao et al., 2017). The order picking process is the most time-consuming and labour-intensive warehousing process and has therefore a high contribution to the warehouse operation costs (De Koster et al., 2007; Wutthisirisart et al., 2015; Zhao et al., 2017). Picking accounts for around 55 to 75 percent of the total warehouse costs (Habazin et al., 2017; Li et al., 2016; Lu et al., 2016). The labour- and cost-intensity is prioritising order picking for productivity improvements (De Koster et al., 2007). In general, improvements can be made by automating the picking activity which is however difficult for small and medium-sized companies (Elbert et al., 2017). Until now order picking is still mostly done by humans (De Koster et al., 2007; Elbert et al., 2017).
The order picking is taking place either manually or automated depending on the available systems in the warehouse (De Koster et al., 2007; Habazin et al., 2017; Li et al., 2016). It involves the clustering and scheduling of predetermined customer orders, identifying the storage locations, picking the products from the right shelf and preparing it for shipping (De Koster et al., 2007). Habazin et al. (2017, p. 59) describe the actual picking process as “lifting, moving, picking, putting, packing, and other related activities”. Several picking zones are often installed in the picking area in order to avoid control problems (Habazin et al., 2017).

Two types of order picking

Two different picking types can be distinguished for the stock movement within the picking process – picker-to-part and part-to-picker. In a scenario where a picker is traveling to the respective item the picking type is defined as a picker-to-part system – which is the worldwide common used one with more than 80 percent coverage in West European systems (Li et al., 2016; Lu et al., 2016). De Koster et al. (2007) distinguish picker-to-part systems again in low-level and high-level picking. Pickers collect the requested items from a storage shelf while travelling alongside for a low-level picking. In turn for the high-level picking the pickers are travelling to defined locations on a lifting order-pick vehicle (truck or crane). When the vehicle arrives at the right storage location it stops and lets the picker do the actual picking (De Koster et al., 2007).
Part-to-picker is the more recent approach and refers to situations where an item is brought to the picker with no interface between picker and storage location (Li et al., 2016). The automated storage and retrieval system (AS/RS) is one of the part-to-picker systems, moving along the aisles on a track and retrieving loads into the shelves (De Koster et al., 2007; Hanne & Dornberger, 2017). Operations can be done on round trips as modern AS/RS usually have the capacity for more than one load. Empty drives can be avoided when the stock movement is connecting stock replenishment with order picking (De Koster et al., 2007; Hanne & Dornberger, 2017).

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Shipping

Just like the first warehousing process (receiving), shipping is not discussed in detail in the literature and only briefly mentioned as the final warehousing process. For the sake of completeness and as this paper is investigating the integration of IoT technologies on all warehousing processes, shipping is briefly captured.
The actual shipping is usually performed by a freight company. Therefore the last process step performed within the warehouse can be seen in loading. Dependent on the used warehouse information system, loading is done manually or automatically with the usage of a scanner. As a step in between order picking and shipping, packing and the consolidation of goods is necessary in order to prepare the shipping (Habazin et al., 2017).

IoT technologies integrated in the warehousing processes

The IoT infrastructure can “redesign factory workflows, improve tracking of materials, and optimize distribution costs” (Lee & Lee, 2015, p. 431). These changes can also be used to manage the inventory level in a warehouse with the possibility of having internal communication between devices. Furthermore, IoT connects people and devices with the Internet or different systems at any time and place. This leads to much faster processing times and reduces mistakes (Lee & Lee, 2015; Trab et al., 2017). It is furthermore stated that by means of IoT, RFID technology with tags and readers can help to obtain real-time information about objects (Jiang et al., 2015; Zhao et al., 2017). These are only the first steps that can be done in order to further improve the warehousing processes. The introduction of more and more smart objects which are connected with each other and the whole network are the future (Lee et al., 2017). The new form of communication between objects in real-time is another approach for improvements in warehousing processes and can help cutting operation costs (Goudarzi, Tabatabaee Malazi, & Ahmadi, 2016). The IoT integration in the warehousing processes will be discussed in detail in this chapter.

1. Introduction .
1.1 Background
1.2 Research problem
1.3 Research purpose and questions
1.4 Structure
2. Literature Review
2.1 Internet of Things / IoT
2.2 Warehousing processes
2.3 IoT technologies integrated in the warehousing processes
2.4 Summary literature review
3. Research Methodology
3.1 Research philosoph
3.2 Qualitative researc
3.3 Research process
3.4 Research method
3.5 Time horizon
3.6 Data collection process
3.7 Data analysis
4. Results
4.1 Company 1 – construction industry .
4.2 Company 2 – automotive industr
4.3 Company 3 – consumer goods
4.4 Company 4 – automotive industr
4.5 Company 5 – e-commerce
4.6 Company 6 – consumer goods
5. Analysis
5.1 IoT usage in warehouses and their advantages and disadvantages
5.2 IoT integration in the receiving and shipping process
6. Conclusion
6.1 Summary of the study
6.2 Contribution of result
6.3 Limitations and further research
7. Reference list