Hybrid Additive–Subtractive Manufacturing Process Planning: A Hypothesis-Guided Systematic Review of Integration, Simulation, Prediction, and Multiparametric Decision Support

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Abstract
Hybrid additive–subtractive manufacturing enables complex, precise production but creates major process-planning and integration challenges. This study identifies gaps in hybrid process planning, particularly for laser metal deposition and machining, using the Hybrid Manufacturing Process Planning Model (HPPM) as a conceptual reference. A PRISMA-guided systematic mapping review of Scopus and Web of Science yielded 1056 documents classified across four dimensions: holistic planning, simulation–planning integration, predictive capabilities, and multi-parameter management. Corpus-level rule-based semantic mapping was validated against consensus from seven experts using a stratified 100-document sample and complemented by a structured engineering appraisal of a targeted 100-document full-text verification set. Only 0.95% of documents showed partial planning integration, with none meeting the holistic framework criteria. Simulation–planning connections occurred in 1.42%, but only 1.23% reached functional or framework-level integration. Predictive capabilities appeared in 91.76%, although only 17.42% were planning-linked, while multi-parameter evidence occurred in 28.31%. The engineering appraisal identified persistent bottlenecks in geometry/data interoperability, thermal-to-geometric transfer, coordinate consistency, kinematics, machinability, and feedback. The principal gap is therefore the coordinated integration of physical, computational, and decision interfaces required for executable hybrid process planning.

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