Researchers from the University of Derby have proposed a novel threshold-based governance framework designed to address this disconnect. The study, published in Discover Sustainability, quantifies the relationship between technical performance and sustainability metrics without requiring the retraining of complex machine learning models. By making these trade-offs visible and navigable, the framework equips maintenance practitioners with the ability to align their operations with strategic environmental, social, and governance goals. This approach represents a shift from purely algorithmic optimization to a more holistic management strategy that considers the broader impact of industrial decisions.

The core of the proposed framework relies on a utility function that incorporates strategic priority coefficients. These coefficients allow decision-makers to translate high-level organizational goals into specific operating points for their maintenance systems. For instance, a company prioritizing carbon reduction can adjust these coefficients to favor operating points that minimize environmental impact, even if it means accepting a slightly lower technical accuracy in failure detection. This flexibility is crucial for navigating the complex realities of industrial management, where sustainability targets often conflict with immediate reliability requirements.

To demonstrate the practical applicability of this framework, the researchers used a Random Forest classifier applied to the NASA C-MAPSS turbofan dataset as a proof-of-concept. This dataset is widely recognized in the field for its comprehensive representation of turbofan engine degradation. By varying thirty classification thresholds ranging from 0.3 to 0.9, the team generated a Pareto frontier of non-dominated solutions. This frontier maps out the optimal trade-offs between the F1-score, a measure of technical performance, and various sustainability metrics. The resulting map provides a clear visual and quantitative guide for where the system should operate based on specific strategic needs.

The analysis revealed a fascinating dual-regime trade-off structure that challenges conventional assumptions about performance optimization. In the initial regime, known as the win-win region, improving reliability was associated with a reduction in environmental impact. Specifically, as the F1-score increased from 0.458 to 0.614, the sustainability costs decreased. This suggests that there is a range of operation where enhancing the accuracy of failure detection actually leads to more efficient resource use, likely by preventing unnecessary maintenance interventions that waste energy and materials.

However, beyond the inflection point at an F1-score of approximately 0.614, the relationship shifts to a regime of diminishing returns. In this second phase, marginal gains in reliability correspond to increasingly rapid increases in sustainability costs. As the F1-score moves from 0.614 to 0.695, the environmental and financial penalties for pursuing higher accuracy become disproportionately large. This inflection point provides an evidence-based stopping rule for optimization, indicating that pushing for perfect technical accuracy is not always the most sustainable or cost-effective strategy for industrial operators.

To ensure the robustness of these findings, the researchers conducted extensive cross-validation, bootstrapping, and sensitivity analyses. These statistical methods were used to assess how the dual-regime structure holds up across different data splits and model choices. The results indicated that the qualitative trade-off structure was partially preserved, suggesting that the observed patterns are not merely artifacts of a specific dataset or model configuration. While the full details are provided in the supplementary materials, the consistency of the dual-regime behavior across various tests strengthens the credibility of the framework as a generalizable tool for industrial governance.

The implications of this work extend beyond the specific case study of turbofan engines. By closing a practical governance gap, the framework allows for a more nuanced approach to predictive maintenance. It acknowledges that sustainability and reliability are not always in direct conflict but can sometimes be aligned, depending on the operating point. This insight is particularly valuable for companies striving to meet stringent ESG targets without compromising the integrity of their industrial assets. The ability to quantify the carbon cost of improving failure detection by a specific percentage, such as five percent, provides a tangible metric for strategic planning.

Despite its contributions, the study acknowledges certain limitations that must be considered when applying the framework. The proof-of-concept was conducted using a single dataset and one model class, which limits the immediate generalizability to all industrial contexts. Furthermore, the impact values used in the analysis are illustrative and require domain-specific calibration to be applicable in real-world scenarios. Future research will likely focus on expanding the framework to include diverse datasets and model architectures, as well as integrating more detailed economic and environmental impact models to refine the utility function.

As industries continue to grapple with the dual mandates of reliability and sustainability, the need for practical governance tools becomes increasingly urgent. The threshold-based approach proposed by Massoud, Meziane, and AlZoubi offers a promising path forward by making the trade-offs explicit and manageable. By providing a structured way to navigate the complex relationship between technical performance and environmental impact, this framework empowers practitioners to make informed decisions that support both operational excellence and long-term sustainability goals. This shift in perspective is essential for the successful implementation of Industry 5.0 principles across various sectors.

Subject of Research: Threshold-based governance for balancing reliability and sustainability in predictive maintenance

Article Title: A threshold based governance approach to balancing reliability and sustainability in predictive maintenance

Article References: Massoud, A., Meziane, F., & AlZoubi, A. (2026). A threshold based governance approach to balancing reliability and sustainability in predictive maintenance. Discover Sustainability. https://doi.org/10.1007/s43621-026-04882-3

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04882-3

Keywords: Predictive Maintenance, Industry 5.0, Sustainability, Reliability, Pareto Frontier, ESG Governance, Random Forest, Carbon Emissions, Operational Efficiency, Dual-Regime Trade-off, threshold, based

The original formulation was deceptively simple. A threshold concept, Meyer and Land argued, is likely to be transformative, probably irreversible, integrative, possibly bounded, and potentially troublesome. Their now-famous example involved a cup of tea cooling after milk is added. At an everyday level, a learner might say cold milk makes hot tea cooler. Within a disciplinary way of thinking, however, the same event opens onto heat transfer, temperature difference, and thermal equilibrium. The learner must abandon the idea of hotness and coldness as isolated properties and grasp cooling as a relational process. That perceptual shift is not merely another fact acquired; it changes how the learner interprets the physical world. Crossing such a portal, the authors argued, leads to a transformed way of understanding without which the learner cannot progress, and mastery is both intellectually and personally transformational, altering identity itself.

Subsequent scholarship expanded the list of characteristics to eight, adding discourse, reconstitution, and liminality, the unstable betwixt-and-between state borrowed from anthropologists Van Gennep and Turner in which learners oscillate between old and emerging understandings. That expansion, however, became a target. Critics such as David Rowbottom argued that threshold concepts lack clearly stated necessary and sufficient criteria, while others questioned whether all five original criteria must be present each time a threshold is identified. In medical education, Brown, Whybrow, and Finn went further, describing a floating signifier problem in which definitional ambiguity lets threshold concepts mean different things in different contexts, and asking whether the field should simply close the door on the framework altogether.

The methodological critiques cut deeper still. Studies vary enormously in who identifies threshold concepts, whether students, academics, or practitioners; in the methods used; and in how agreement is reached. Without explicit criteria, researchers may be characterising entirely different things as thresholds: a difficult topic, a core disciplinary idea, a curricular bottleneck, or a genuinely transformative concept. A third line of critique raised political concerns, arguing that naming particular concepts as thresholds privileges certain disciplinary worldviews, presents disciplines as more coherent than they are, and risks treating identity formation as primarily cognitive rather than social. Naming something a threshold concept, these critics note, is never a neutral act; it determines what counts as disciplinary knowledge and whose expertise is legitimised.

The new analysis does not dismiss these critiques but reframes them. Drawing on Sarah Hill’s work in prosthetics education, the authors emphasise that troublesome knowledge and threshold concepts are not synonymous. Many concepts are simply hard to learn, such as biomechanical calculations or anatomical lists, without producing the integration and ontological transformation necessary for threshold status. A true threshold concept requires contextualised experience and associated memories that bind procedural and disciplinary concepts together, ultimately shifting the learner’s worldview. Content can be difficult without being a threshold; what distinguishes a threshold is that it changes the learner’s sense of self. Davies and Mangan’s work in economics reinforces this structural view: genuine mastery occurs only when disciplinary concepts, the theoretical lenses of a field, are integrated with procedural concepts, the methods through which the discipline constructs arguments.

The authors also challenge the binary view of threshold crossing, in which a student either gets it or does not. Calduch and Rattray’s concept of postliminal variation, the variation in the point and state of exit into a new conceptual space, suggests that different, valid transformations can arise from the same threshold concept. Far from being a defect, this variability is evidence that thresholds are living sites of knowledge creation rather than fixed checkpoints. In a vivid metaphor, the authors compare threshold concept characteristics to a cake recipe: the ingredients matter, but the proportions vary by discipline, some cakes contain no fat at all, and the threshold concept is the baked outcome of interacting characteristics, not any single ingredient. Evaluating a threshold concept on the basis of one characteristic alone, they argue, leaves a bad taste.

The analysis’s most novel contribution is its positioning of uncertainty tolerance as the central analytic lens for the field. Uncertainty tolerance describes how individuals respond to unknowns across cognitive, emotional, and behavioural domains, whether the source is complexity, ambiguity, or probability. Land himself framed threshold concepts as a pedagogy of uncertainty, and the new paper argues that this construct offers a robust mechanism for distinguishing true, identity-shaping thresholds from merely troublesome knowledge. Learners can respond adaptively to the uncertainty of liminality, with curiosity and confidence, or maladaptively, through disengagement, denial, or endless certainty-seeking without forward progress. In high-stakes contexts such as education, research suggests most people will feel emotionally distressed regardless of their behavioural response, which makes the educator’s role in scaffolding that distress critical.

This reframing carries concrete implications for curriculum design and assessment. Rather than eliminating thresholds or smoothing the learner’s journey, educators should strategically identify these junctures and scaffold learner resilience, timing exposure to discipline-related thresholds and supporting adaptive responses through questioning preconceptions, transferring knowledge across contexts, presenting multiple points of view, and working through purpose-built grey cases. Assessment, meanwhile, should not simply ask whether learners acquired content but should generate evidence of how learners reason, act, and position themselves when existing assumptions no longer provide certainty: reflective writing, concept maps, portfolios, and narrative accounts of uncertainty can reveal uncertainty responses, conceptual integration, and identity-level change. The authors also stress that identification should not rest with instructors alone; learners’ accounts of their own discomfort in the liminal space are essential evidence, guarding against the framework becoming an unexamined mechanism for reproducing dominant professional norms.

The paper acknowledges its own limits: it is conceptual rather than empirical, and the link between threshold concepts and uncertainty tolerance requires investigation across disciplines, learner groups, and institutional contexts. But its closing argument is deliberately recursive. The framework of threshold concepts, the authors conclude, is itself a threshold concept: troublesome, requiring educators to tolerate ambiguity; liminal, forcing a renegotiation of teachers’ own identities; and, once understood not as a rigid rulebook but as a lens for complexity, irreversibly transformative in how one experiences education. To master the framework is to accept that learning in higher education is not a linear transfer of knowledge but a complex, uncertain, and profoundly human struggle, and that the goal of education is not to remove that struggle but to equip learners to navigate it.

Subject of Research: The theoretical coherence of the threshold concepts framework in higher education and its integration with uncertainty tolerance

Article Title: Threshold concepts: Tensions and truths

Article References: Threshold concepts: Tensions and truths. (n.d.). https://doi.org/10.1007/s10734-026-01752-9

Image Credits: AI Generated

DOI: 10.1007/s10734-026-01752-9

Keywords: threshold concepts, higher education, uncertainty tolerance, liminality, troublesome knowledge, curriculum design, transformative learning, professional identity, pedagogy, assessment, educational theory, Threshold