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Two researchers suggest a new approach to the most fundamental warehousing operation of all.

Synergy between computer and manager may be the basis on which effective decision support systems can be constructed.

The purpose of this paper is to propose a decision model to choose between kitting and line stocking at the level of single parts, while taking into account the variable operator walking distances. Different ways of feeding assembly lines, such as kitting and line stocking not only have an impact on in-plant logistics flows but also determine the amount of stock that is available at the line. This, in turn, has an impact on operator walking distances during assembly.

A mixed integer linear programming model is developed for the assignment of parts to one of both methods, and to be able to extensively test the model, an algorithm is created for the construction of representative datasets.

Parts are often kitted because of a space constraint at the line, but even without a space constraint, the shorter walking distances might give preference to kitting. An analysis is presented that demonstrates how specific part characteristics influence the chances of a part being kitted.

Our research model can be extended to include, e.g., the study of alternative in-plant logistic designs and the outsourcing of kitting to a third-party logistics provider (3PL) or to the suppliers.

The objective assignment model and the insights obtained from it are valuable for logistics and production engineers that otherwise have to rely solely on intuition. In situations with thousands of components, intuition mostly falls far short.

First, existing models do not consider variable walking distances, which are shown to have a crucial impact on the decision. Second, the data instances created allow for a systematic comparison of future research in the field.

The combination of the latest advancements in information and communication technologies with the latest developments in AutoID technologies, especially radio frequency identification (RFID), brings the possibility of high-resolution, item-level visibility of the entire supply chain. In the particular case of retail, visibility of both the stock count and item location in the shop floor is crucial not only for an effective management of the retail supply chain but also for physical retail stores to compete with online retailers. The purpose of this paper is to propose an autonomous robot that can perform stock-taking using RFID for item-level identification much more accurately and efficiently than the traditional method of using human operators with RFID handheld readers.

This work follows the design science research methodology. The paper highlights a required improvement for an RFID inventory robot. The design hypothesis leads to a novel algorithm. Then the cycle of development and evaluation is iterated several times. Finally, conclusions are derived and a new basis for further development is provided.

An autonomous robot for stock-taking is proven feasible. By applying a proper navigation strategy, coupled to the stream of identifications, the accuracy, precision, consistency and time to complete stock-taking are significantly better than doing the same task manually.

The main limitation of this work is the unavailability of data to analyze the actual impact on the correction of inventory record inaccuracy and its subsequent implications for the supply chain management. Nonetheless, it is shown that figures of actual stock-tacking procedures can be significantly improved.

This paper discloses the potential of deploying an inventory robot in the supply chain. The robot is called to be a key source of inventory data conforming supply chain management 4.0 and omnichannel retail.