ISBN
979-13-87631-36-9
Fecha de publicación
28-12-2024
Licencia
D. R. © copyright 2024; Aurora Irma Máynez Guaderrama y Virginia Guadalupe López Torres.
Luis Ricardo Vidal Portilla
Universidad Autónoma de Ciudad Juárez
0000-0001-5248-5845
Salvador Noriega Morales
Universidad Autónoma de Ciudad Juárez
0000-0001-7813-5835
Jesús Andrés Hernández Gómez
Universidad Autónoma de Ciudad Juárez
0000-0003-2325-2051
Erwin Adam Martinez Gomez
Universidad Autónoma de Ciudad Juárez
0000-0002-7753-2545
Acerca de
Advanced Manufacturing Technology (AMT) is essential for achieving manufacturing companies’ strategic goals by enhancing product development, planning, processes, and control. It strategically optimizes business activities and serves as a model to adapt to the operating environment. AMT, as both an approach and philosophy, efficiently integrates design and manufacturing functions through computer systems and data management (Azemi et al., 2019; Bedworth et al., 1991; Wilhelm & Parsaei, 1991; Yu et al., 2015). The widespread adoption of AMT brings both quantitative and qualitative benefits across various production stages, including product design, manufacturing planning, material handling, real-time tracking, and product quality improvement (Berman et al., 2009; Cotton & Schinski 1999; Marri et al., 2000). However, organizational structural changes are often necessary for successful adoption because of technological complexity, as noted by Lucianetti et al. (2018) and Saberi et al. (2010). Although extensive literature exists in AMT implementation processes, effectiveness, and associated risks, much of it remains anecdotal and controversial. Although it constitutes valuable empirical evidence, it is not conclusive. Therefore, it is crucial to conduct cutting-edge research on the factors influencing its effectiveness.
AMT evaluation is crucial during the planning phase. Assessment must be correct, objective and comprehensive to select the best option (Lakymenko, Alfned & Thomassen, 2016). It should consider diverse interests, including long-term effects, competitiveness, equipment reliability, user-friendliness, and other variables (lo Storto, 2018). Effective planning requires analyzing various qualitative and quantitative factors, understanding their interplay within and outside the company, and assessing the industrial environment (Al-Ahmari, 2008). This ensures a confident decision regarding the technology that best fosters business development and competitiveness. The subsequent paragraphs discuss some models for evaluating these factors and their associated challenges (Ocampo, Hernández-Matías & Vizán, 2017).
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