PERFORMANCE MEASUREMENT IN LVHM MANUFACTURING: KPIS, TECHNOLOGIES, AND STARTUP GAPS

Abstract

The high degree of product variability and the ever-changing demands of customers make performance monitoring a constant struggle in low-volume high-mix (LVHM) production settings. This research provides a systematic literature review in accordance with PRISMA principles, examining 42 peer-reviewed papers (2021–2025) sourced from Scopus and Web of Science. Research has indicated that lead time and makespan are the predominant performance indicators. Moreover, digital twins, reinforcement learning, and discrete-event simulation are being increasingly used to increase scheduling efficiency and cost effectiveness. A bibliometric study using R Studio indicates a significant focus on job shop scheduling and AI-driven optimisation. Critically, there is a substantial gap in the literature, as no study explicitly addresses startup LVHM manufacturing. This review lays the foundation for performance frameworks specifically designed for LVHM manufacturers in the early stages of development.