Lean principles for organizing items in an automated storage and retrieval system: an association rule mining – based approach

• Autorzy: Bevilacqua Maurizio , Ciarapica Filippo Emanuele , Antomarioni Sara

Identyfikatory

DOI

10.24425/mper.2019.128241

• Języki publikacji: EN

Abstrakty

EN

The application of the 5S methodology to warehouse management represents an important step for all manufacturing companies, especially for managing products that consist of a large number of components. Moreover, from a lean production point of view, inventory management requires a reduction in inventory wastes in terms of costs, quantities and time of non-added value tasks. Moving towards an Industry 4.0 environment, a deeper understanding of data provided by production processes and supply chain operations is needed: the application of Data Mining techniques can provide valuable support in such an objective. In this context, a procedure aiming at reducing the number and the duration of picking processes in an Automated Storage and Retrieval System. Association Rule Mining is applied for reducing time wasted during the storage and retrieval activities of components and finished products, pursuing the space and material management philosophy expressed by the 5S methodology. The first step of the proposed procedure requires the evaluation of the picking frequency for each component. Historical data are analyzed to extract the association rules describing the sets of components frequently belonging to the same order. Then, the allocation of items in the Automated Storage and Retrieval System is performed considering (a) the association degree, i.e., the confidence of the rule, between the components under analysis and (b) the spatial availability. The main contribution of this work is the development of a versatile procedure for eliminating time waste in the picking processes from an AS/RS. A real-life example of a manufacturing company is also presented to explain the proposed procedure, as well as further research development worthy of investigation.

Słowa kluczowe

EN

lean management; AS/RS; Association Rules; data mining; Industry 4.0; 5S; shoe manufacturing

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2019
• Tom: Vol. 10, No. 1
• Strony: 29--36
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Bevilacqua Maurizio

• Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche Via Brecce Bianche, 12, 60131, Ancona, Italy

autor

Ciarapica Filippo Emanuele

• Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Italy

autor

Antomarioni Sara

• Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Italy

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