Supplementary Data for: "Optimizing the Build: A Review of Scheduling and Nesting Integration in 3D Printing", Systematic Literature Review Dataset (n=75)

SEARCH_STRING_DOCUMENTATION.txt Documentation of the database search strings used in the systematic literature search, including the Boolean operators and keyword combinations applied in Scopus, Web of Science, and Google Scholar. Search coverage: articles published up to January 2026. scopus_raw_export.ris Raw bibliography export from Scopus database prior to deduplication and screening. Retrieved using the Boolean search string combining additive manufacturing, scheduling, and nesting/packing keywords. Search conducted in 2025, covering articles published up to January 2026. Contains 88 records. wos_raw_export.ris Raw bibliography export from Web of Science (WoS) Core Collection prior to deduplication and screening. Retrieved using the same Boolean search string applied in Scopus. Search conducted in 2025, covering articles published up to January 2026. Contains 75 records. google_scholar_raw_export.ris Raw bibliography export from Google Scholar prior to deduplication and screening. Retrieved using the same Boolean search string. Search conducted in 2025, covering articles published up to January 2026. Contains records supplementing the Scopus and WoS results. Net_included_Lt_review.ris RIS-formatted bibliography file containing the full references of all 75 included studies, exported from Zotero reference management software. Compatible with all major reference managers (Zotero, Mendeley, EndNote). Supplement_1_Assessed_for_eligibility.xlsx Full-text eligibility assessment record for 153 articles retrieved after title/abstract screening. Each entry includes the article title, authors, year, and exclusion reason (if applicable) based on five predefined criteria. Used to construct the PRISMA flow diagram (Figure 1). Supplement_2_Data_Extraction_matrix.xlsx Structured data extraction matrix for all 75 included studies. Each article is coded across six dimensions: (1) problem scope and manufacturing environment, (2) algorithmic approach, (3) nesting dimensionality (2D planar vs. 3D volume), (4) part orientation flexibility (fixed, 2D Z-axis rotation, 3D dynamic rotation), (5) part shape representation (area-sum, bounding box, true shape), and (6) primary objective function. This matrix is the primary data source for all quantitative analyses, tables, and figures in the manuscript fig6_heatmap.py Python script used to generate Figure 6 (geometric complexity heatmap) in the manuscript. Requires matplotlib and numpy. Run with: python fig6_heatmap.py. Output: fig6_heatmap.png at 600 dpi.