Multi-Criteria Decision Making in Machine Tool Selection

Machine tool selection is a critical decision in modern manufacturing, encompassing evaluation of technical performance, cost efficiency, operational flexibility and lifecycle sustainability. Multi-Criteria Decision Making (MCDM) provides structured frameworks to synthesise quantitative and qualitative factors, reconciling conflicting objectives such as precision, throughput, maintenance requirements and environmental impact. Traditional single-criterion approaches often overlook complex interactions among production speed, tool wear, energy consumption and acquisition cost. Contemporary MCDM techniques employ hierarchical structuring of criteria, pairwise comparisons and normalisation procedures to derive weighted scores for alternative machines. The integration of fuzzy logic allows decision-makers to express subjective assessments in linguistic terms – for example “high rigidity” or “moderate cost” – while preserving mathematical rigour. Outranking and scoring methods such as PROMETHEE, COPRAS and ELECTRE have been adapted to machine tool evaluation, enabling robust ranking under uncertainty. Advances in digitalisation and Industry 4.0 have further enriched MCDM models by incorporating real-time monitoring data, predictive maintenance indicators and sustainability metrics. The global significance of optimising machine tool portfolios spans reduced production costs, improved product quality, enhanced resource efficiency and strengthened competitiveness across automotive, aerospace and precision engineering sectors.

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Recent studies have refined hybrid MCDM architectures to address vagueness inherent in expert judgements. One investigation combined a fuzzy Analytic Hierarchy Process (AHP) with the COmplex PRoportional ASsessment (COPRAS) method, embedding a linguistic reference relation into AHP to capture imprecise pairwise comparisons. The resulting fuzzy COPRAS stage ranks machine tools by computing closeness coefficients, demonstrating enhanced discrimination among alternatives in uncertain environments and offering a practical template for questionnaire-based data collection in industrial settings.

Another approach has merged the Delphi technique with AHP and the PROMETHEE outranking method within a fuzzy-set framework. Experts first converge on key criteria via iterative Delphi rounds, after which fuzzy AHP derives attribute weights. PROMETHEE’s positive and negative preference flows then establish a comprehensive ranking of pressing machines in a real-world manufacturing case study. Sensitivity analyses underscore the stability of selections against weight variations, highlighting the model’s utility in strategic capital investment decisions.

Multi-Criteria Decision Making in Machine Tool Selection publication trend

The graph below shows the total number of articles in multi-criteria decision making in machine tool selection across all publications each year (not limited to Nature Index journals).

Technical terms

Multi-Criteria Decision Making (MCDM): A family of methods for evaluating and prioritising alternatives against multiple, often conflicting criteria.

Analytic Hierarchy Process (AHP): A structured decision technique that decomposes a problem into a hierarchy and uses pairwise comparisons to assign weights to criteria and score alternatives.

Fuzzy Set Theory: A mathematical framework that models uncertainty by allowing elements to belong to sets with varying degrees of membership between zero and one.

COPRAS: A numerical assessment method that ranks alternatives by calculating proportional relationships of criteria contributions to ideal and anti-ideal solutions.

PROMETHEE: An outranking approach that compares alternatives pairwise on each criterion, aggregates preference flows and derives a complete ranking.

Delphi Technique: An iterative consensus-building process that collects expert judgements anonymously to identify and refine decision criteria.

References

1. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation. PLOS ONE (2015).