Tool indexing, switching, and loading problems in CNC-based production systems: a structured review and research agenda

Abstract Tool-related setup and handling losses remain an important source of non-machining time in computer numerical control (CNC)-based production systems, yet the literature is fragmented across the job sequencing and tool switching problem (SSP), tool loading, the tool indexing problem (TIP), and turret-index optimisation. This article reviews that problem family from a manufacturing-systems, operations-research, and production-research perspective. Using a Scopus search executed on 30 March 2026 and documented through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020-inspired screening procedure, 137 records were identified and 93 studies were retained. The corpus is organised into three decision-centric streams: sequence-centric switching models, loading-centric allocation and flexible manufacturing system (FMS) planning models, and slot-centric indexing models, plus a small residual set of bridging and review papers. The review compares problem definitions, formulations, solution methods, benchmark practices, and manufacturing-system implications. Within the retained Scopus corpus, SSP appears to be the most methodologically mature stream, loading-centric studies tend to offer greater operational realism but weaker benchmark continuity, and TIP/turret studies tend to be closer to machine physics but rest on a thinner empirical base. The paper closes with a corpus-supported research agenda on CNC-derived benchmarks, integrated switching/loading/indexing models, disturbance-aware and real-time decision support, validation on production data, and reproducible computational evidence.

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Publication Details

Journal
The International Journal of Advanced Manufacturing Technology
Published
2026-09-16
DOI
https://doi.org/10.1007/s00170-026-19131-0
Primary Topic
Scheduling and Optimization Algorithms
Type
article
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article

Tool indexing, switching, and loading problems in CNC-based production systems: a structured review and research agenda

Soumen Atta
The International Journal of Advanced Manufacturing Technology
Scheduling and Optimization Algorithms
article

Tool indexing, switching, and loading problems in CNC-based production systems: a structured review and research agenda

Soumen Atta
article en

Abstract

Abstract Tool-related setup and handling losses remain an important source of non-machining time in computer numerical control (CNC)-based production systems, yet the literature is fragmented across the job sequencing and tool switching problem (SSP), tool loading, the tool indexing problem (TIP), and turret-index optimisation. This article reviews that problem family from a manufacturing-systems, operations-research, and production-research perspective. Using a Scopus search executed on 30 March 2026 and documented through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020-inspired screening procedure, 137 records were identified and 93 studies were retained. The corpus is organised into three decision-centric streams: sequence-centric switching models, loading-centric allocation and flexible manufacturing system (FMS) planning models, and slot-centric indexing models, plus a small residual set of bridging and review papers. The review compares problem definitions, formulations, solution methods, benchmark practices, and manufacturing-system implications. Within the retained Scopus corpus, SSP appears to be the most methodologically mature stream, loading-centric studies tend to offer greater operational realism but weaker benchmark continuity, and TIP/turret studies tend to be closer to machine physics but rest on a thinner empirical base. The paper closes with a corpus-supported research agenda on CNC-derived benchmarks, integrated switching/loading/indexing models, disturbance-aware and real-time decision support, validation on production data, and reproducible computational evidence.

The International Journal of Advanced Manufacturing Technology
Openalex Percentile: Top 11%
Scheduling and Optimization Algorithms
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