Purpose-Item classification based on ABC-XYZ analysis is of high importance for strategic supply and inventory control. It is common to perform the analysis with past consumption data. In this context, the purpose of this study is to test the hypothesis that an integration of demand forecasts can improve the performance of item classification, in particular the performance of ABC-XYZ analysis. Design/methodology/approach-For the study, real data of an industrial enterprise in the mechanical engineering sector (focal company) were analyzed and evaluated. Findings-The study shows that a comprehensive data analysis of the focal company can recommend a specific implementation of the ABC-XYZ classification. In contrast to the classic method of making the ABC-XYZ analysis based on consumption data only, the approach developed in this paper offers considerable advantages. These are quantifiable in respect to an assumed optimal reference classification. Originality/value-The evaluation of the results is very promising and applicable to other branches besides mechanical engineering.
Logistics is a very dynamic and heterogeneous application area which generates complex requirements regarding the development of information and communication technologies (ICT). For this area, it is a challenge to support mobile workers on-site in an unobtrusive manner. In this contribution, wearable computing technologies are investigated as basis for a "mobile worker supporting system" for tasks at an automobile terminal. The features of wearable computing technologies are checked against the requirements of the application area to come to an usable and acceptable mobile solution in an user-centred design process.
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