Contracted near-shore service part production predictive modelling using BOM-based feature generalisation and deep statistical learning

Donovan Fuqua, Faruk Arslan, Victor Pimentel, Jimoh Fatoki, Barry Brewer, Phillip W. Witt and Edward Kennedy

International Journal of Information and Decision Sciences, 2026, vol. 18, issue 2, 83-103

Abstract: Intermittent service part production (SPP) is a common manufacturing resource planning (MRP II) problem occurring when a customer requests spare parts from the manufacturer for an item no longer in production but still in widespread use. Manufacturers increasingly turn to contracted SPP (outsourcing) for fabrication of specialised components, including service parts. Despite the ubiquity of contracted SPP in contemporary manufacturing, it is a neglected area of study that relies on dated research, standard operations research models, and simplistic forecasting. Most available literature depends upon the availability of maintenance and part reliability information generally not available to contracted suppliers. In practice, manufacturers tend to add rough service demand estimates into contract costs or negotiate additional production as separate orders. Our model adds to SPP theory by managing irregularly contracted SPP by component item families using out-of-sequence service order histories as a proxy for reliability data.

Keywords: smart MRP II; lumpy demand; agile manufacturing; explainable machine learning; demand chain management; DCM. (search for similar items in EconPapers)
Date: 2026
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