Technology Selection and Assessment in Advanced Manufacturing Systems
Summary
Advanced manufacturing systems demand rigorous methods to identify, evaluate and integrate emerging technologies that enhance productivity, quality and sustainability. Technology selection and assessment encompass the systematic appraisal of hardware, software and process innovations against a spectrum of technical, economic and environmental criteria. In an era of digitalisation and Industry 4.0, decision-support frameworks increasingly combine data analytics, artificial intelligence and virtual simulation to manage uncertainty and complexity. Multi-criteria decision-making approaches allow stakeholders to balance performance objectives—such as throughput, energy efficiency and lifecycle cost—while accommodating interdependencies among subsystems. Hybrid methods that integrate structured modelling and fuzzy logic have proven effective in capturing expert judgement when quantitative data are scarce. Case studies in research centres and manufacturing plants illustrate how these frameworks guide strategic investment, accelerate technology transfer and ensure alignment with sustainability targets. By embedding real-time monitoring and digital-twin replicas, modern assessment pipelines can continuously validate technology performance, enabling dynamic re-prioritisation as market and regulatory conditions evolve. This synthesis highlights the importance of transparent, reproducible and adaptable selection processes to maintain global competitiveness and drive the next generation of smart factories.
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Technology Selection and Assessment in Advanced Manufacturing Systems publication trend
The graph below shows the total number of articles in technology selection and assessment in advanced manufacturing systems across all publications each year (not limited to Nature Index journals).
Technical terms
Multi-criteria decision-making (MCDM): A set of methods for ranking and selecting options based on multiple, often conflicting, evaluation criteria.
Analytic hierarchy process (AHP): A structured MCDM technique that decomposes decisions into a hierarchy of goals, criteria and alternatives, using pairwise comparisons to assign weights.
Analytic network process (ANP): An extension of AHP that captures interdependencies and feedback among decision elements through networked pairwise comparisons.
Fuzzy logic: A computational approach handling uncertainty and vagueness by allowing elements to have degrees of membership rather than binary states.
Interpretive structural modelling (ISM): A methodology for identifying and structuring relationships among components of a complex system to reveal hierarchical ordering.
Industry 4.0: The integration of cyber-physical systems, Internet of Things and data analytics into manufacturing to create intelligent, interconnected production environments.
References
- Assessment and Selection of Technologies for the Sustainable Development of an R&D Center. Sustainability (2020).
- A Model for Selecting Technologies in New Product Development. Mathematical Problems in Engineering (2012).
- Model for Technology Selection in the Context of Industry 4.0 Manufacturing. Processes (2023).
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