Design Practice and Methods

Design practice combines creative insight with structured techniques to navigate complex problems, translating user and stakeholder needs into tangible solutions. Central to modern methods is multi-criteria decision‐making, which formalises the evaluation of competing objectives such as cost, performance, sustainability and usability. Frameworks like the Analytic Hierarchy Process and TOPSIS guide the weighting and ranking of alternatives, while information-theoretic measures (entropy) and consensus-building models refine expert judgments. Fuzzy-set theories extend these tools to handle uncertainty in preferences, and hybrid approaches integrate optimisation algorithms—genetic, game-theoretic or grey relational projection—to explore multi‐objective landscapes. Across sectors from consumer electronics and heavy machinery to service systems and biomedical devices, these methods accelerate concept selection, foster stakeholder alignment and ensure that design outcomes remain robust under variable conditions. By embedding systematic evaluation and iterative refinement throughout the project lifecycle, practitioners can reconcile creativity with rigour, delivering solutions that resonate with users and meet strategic goals on a global scale.

Research from Nature Portfolio

Recent studies have advanced integrated frameworks for design concept evaluation by combining entropy-based weighting with pairwise comparison methods and consensus models. A two-layer expert-weighting scheme first merges objective information-entropy measures with a multiplicative hierarchy process, then applies variance-minimisation to achieve group agreement—demonstrating marked improvements in decision confidence for large-scale systems. Complementary work has enhanced multi-attribute decision-making by embedding interval-valued picture fuzzy sets into Kano-AHP-GRP hybrids, automatically capturing vagueness and expert uncertainty to yield more accurate prioritisation of design criteria. These innovations underscore the value of hybridising quantitative and qualitative assessments within a unified decision protocol.

Research from all publishers

In product design, extensions to AHP and TOPSIS using Z-numbers have modelled decision-maker confidence alongside preference assessments, improving transparency in conceptual evaluation for consumer-goods applications. A combined TOPSIS–MOGA approach has been proposed to ensure continuity between conceptual and detailed design stages: initial concepts are ranked through hesitant-fuzzy TOPSIS with entropy-derived weights, then refined via multi-objective genetic algorithms, as demonstrated in power-equipment case studies. Furthermore, two-stage multi-objective analysis methods employ non-dominance filtering followed by weighted TOPSIS to reduce comparison workloads and identify optimal design schemes under assembly, manufacturing and cost constraints, as illustrated in compressor concept selection.

Design Practice and Methods publication trend

The graph below shows the total number of articles in design practice and methods across all publications each year (not limited to Nature Index journals).

Technical terms

Analytic Hierarchy Process (AHP): A structured technique for decomposing a decision problem into a hierarchy of criteria and deriving priority scales through pairwise comparisons.

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS): A ranking method that selects alternatives closest to an ideal solution and furthest from a nadir solution based on weighted distance measures.

Entropy Weight Model: An objective method for determining criterion weights by measuring the information content or disorder in performance data.

Multi-Attribute Decision-Making (MADM): A class of methods for evaluating and selecting among alternatives characterised by multiple, often conflicting, performance criteria.

Interval-Valued Picture Fuzzy Set (IVPFS): An extension of fuzzy sets that assigns to each element an interval degree of membership, non-membership and abstention, enabling nuanced uncertainty modelling.

Grey Relational Projection (GRP): A technique for ranking alternatives by quantifying their relational closeness to an ideal pattern in systems with incomplete information.

References

1. Optimization and selection of the multi-objective conceptual design scheme for considering product assembly, manufacturing and cost. Discover Applied Sciences (2022).
2. Multi-Indicators Decision for Product Design Solutions: A TOPSIS-MOGA Integrated Model. Processes (2022).
3. An integrated expert weight determination method for design concept evaluation. Scientific Reports (2022).
4. Conceptual Design Evaluation Considering Confidence Based on Z-AHP-TOPSIS Method. Applied Sciences (2021).
5. An integrated design concept evaluation model based on interval valued picture fuzzy set and improved GRP method. Scientific Reports (2024).