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An automated model for materials management and control

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  • R. Navon
  • O. Berkovich

Abstract

Current, manual, materials management and control procedures are unsatisfactory: they are labour intensive, inaccurate and error prone. The result is waste and surplus of materials, delays, decrease in productivity and lack of up-to-date, real-time information regarding the status of purchase orders (PO), the levels of inventory, the actual vs. planned usage of materials, and others. The purpose of the present work was to develop an automated model, which alleviates some of these problems. Prior to developing the model, a field survey was conducted to learn, at first hand, what the typical problems with materials management and control are. The model initiates materials purchasing, follows up the status of PO, records materials data as they arrive to the site and their movement around the site, makes recommendations, generates reports and issues warnings. The model was implemented, tested and evaluated in an ongoing building construction project. The onsite experiments confirmed that automated materials management and control are feasible, resulting in real benefits, such as time savings, and availability of up-to-date and accurate information regarding stocks of materials on site.

Suggested Citation

  • R. Navon & O. Berkovich, 2006. "An automated model for materials management and control," Construction Management and Economics, Taylor & Francis Journals, vol. 24(6), pages 635-646.
    • Handle: RePEc:taf:conmgt:v:24:y:2006:i:6:p:635-646
    DOI: 10.1080/01446190500435671
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    References listed on IDEAS

    as
    1. A. Agapiou & L. E. Clausen & R. Flanagan & G. Norman & D. Notman, 1998. "The role of logistics in the materials flow control process," Construction Management and Economics, Taylor & Francis Journals, vol. 16(2), pages 131-137.
    2. C. S. Poon & Ann Yu & L. Jaillon, 2004. "Reducing building waste at construction sites in Hong Kong," Construction Management and Economics, Taylor & Francis Journals, vol. 22(5), pages 461-470.
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    Cited by:

    1. Mabaran Rajaraman & Glenn Philen & Kenji Shimada, 2019. "Tracking Tagged Inventory in Unstructured Environments through Probabilistic Dependency Graphs," Logistics, MDPI, vol. 3(4), pages 1-23, September.
    2. Sonja Kolarić & Mladen Vukomanović & Antonio Ramljak, 2022. "Analyzing the Level of Detail of Construction Schedule for Enabling Site Logistics Planning (SLP) in the Building Information Modeling (BIM) Environment," Sustainability, MDPI, vol. 14(11), pages 1-22, May.
    3. Mabaran Rajaraman & Kyle Bannerman & Kenji Shimada, 2020. "Inventory Tracking for Unstructured Environments via Probabilistic Reasoning," Logistics, MDPI, vol. 4(3), pages 1-29, July.
    4. Honglei Liu & Jiule Song & Guangbin Wang, 2021. "A Scientometric Review of Smart Construction Site in Construction Engineering and Management: Analysis and Visualization," Sustainability, MDPI, vol. 13(16), pages 1-19, August.

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