Articles

Key Performance Indicators (KPIs) in Additive Manufacturing: Evaluation of Efficiency, Quality and Sustainability in 3D Printing Processes

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 As a researcher specializing in additive manufacturing (AM), I have authored this study titled “Key Performance Indicators (KPIs) in Additive Manufacturing: Evaluation of Efficiency, Quality, and Sustainability in 3D Printing Processes.” The work explores AM’s explosive growth, with the global market at 21.9 billion in 2025, projected to hit USD 647.7 billion by 2035 at a 22-23% CAGR, driven by innovations in materials, AI integration, and applications in aerospace, automotive, and biomedicine. AM transforms traditional manufacturing through on-demand production, waste reduction, and supply chain optimization, supporting circular economy principles via localized fabrication and emission cuts.

Utilizing the SALSA methodology, conducted a systematic review of 158 articles (narrowed to 10 key studies from 2015-2025), identifying AM-specific KPIs: efficiency (adapted OEE, varying with build variety); quality (tensile strength up to 55.2 MPa, dimensional deviation 0.048 mm); sustainability (energy consumption, recyclability challenges in PLA/ABS); costs; and delivery times.

Limitations include adapting traditional metrics to AM’s anisotropy and variability, plus unstandardized sustainability data. A pilot test on 10 parts across five hypothetical Hidalgo companies yielded averages like 74.4% OEE and 83.9% material efficiency, underscoring AI’s role in optimization. Ultimately, robust KPIs foster informed AM adoption, aligning with a SDGs 9 and 12 for resilient, sustainable industries.

Proposed Design of Service Quality Performance Management System for Indonesian HSR

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In some countries, the development of High-Speed Railway (HSR) represents a significant technological advancement which helps modern society’s value of time and various activities. Despite of having complex operational support and significant financial outlays, studies have shown that HSR sector has several growth barriers due to poor punctuality, reliability, pricing, and inconvenient passenger journeys. These brought specific impact on deciding factors whether or not passengers choose the transport option as it affected passenger satisfaction level. Recognizing the global challenge, this paper anticipates the impending Indonesian HSR operation by observing passengers’ relevant service quality attributes. The findings served as the performance management design’s foundation. In order to assist HSR operators to improve passenger experience and satisfaction, this study aims to identify the relevant service quality of Indonesian HSR potential passengers as one of many solutions to eliminate lack of demand problem. Qualitative and quantitative data analysis from in-depth interviews with several Indonesian railway expert and information from prior publication of Asian HSR which was used to carry out external benchmarking, validate results, support design process, and create contextual performance indicators for attributes using Knowledge-Based Performance Management System (KBPMS). This paper produced numbers of service quality performance indicators whose prioritization was arranged in specific order. Five variables are used to measure tangibility attributes’ performance, whereas six variables are used to measure reliability attributes’ performance. Tangibility and reliability were chosen based on Indonesian railway market preference and common success factor of HSR best practices. This performance indicators were specifically developed based on these attributes’ sub-attributes which has been contextualized. In contrast to other countries, Indonesian HSR place a distinctive value on physical facilities as it affects travelling motivation. These new insights would direct Indonesian HSR operators to develop targeted solutions to increase passenger satisfaction and economic benefits.