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Research/Technical Note
A Success-Centric Evolution of Reliability-Centered Maintenance in Modern Asset Management
Irete Daniel Olorunfemi*
Issue:
Volume 10, Issue 2, December 2026
Pages:
20-34
Received:
11 June 2026
Accepted:
27 June 2026
Published:
17 July 2026
Abstract: Reliability-Centered Maintenance (RCM) has served as the dominant industrial maintenance philosophy for nearly five decades, delivering substantial gains in safety, availability, and cost control. However, its core vocabulary, built around Failure Mode, Mean Time Between Failures, and the Potential-to-Functional Failure curve, frames organizational cognition around breakdown rather than performance excellence. This article proposes a complementary, success-oriented framework, the Potential Success Curve (PSC), and demonstrates its practical alignment with contemporary asset management practice. Methodologically, the study employs an integrative cross-disciplinary review with deductive construct development, comparative standards analysis, and worked operational examples. Grounded in Prospect Theory, Appreciative Inquiry, Safety-II, and the lineage of transformative management methodologies including Total Productive Maintenance (TPM), Lean, Total Quality Management, and Six Sigma, the framework introduces several novel constructs: the Golden Spot (an asset’s optimal performance envelope), Mean Time of Optimal Performance (MTOP), Mean Time to Restore Golden Spot (MTTRg), Success Rate, Overall Performance Excellence (OPE), Success Mode and Effects Analysis (SMEA), and Root Success Analysis (RSA). A new D-I-S-G model extends the traditional D-I-P-F curve. The framework is operationalized through a SMART (Specific, Measurable, Applicable, Realistic, Time-bound) validation structure and is mapped explicitly to ISO 55000: 2024, ISO 55001: 2024, API 580/581, SAE JA1011, ISO 14224, and IEC 60300. The article further demonstrates how emerging technologies, including artificial intelligence, digital twins, and the Industrial Internet of Things, serve as practical enablers of the framework, and quantifies the potential impact on the industrial business landscape. While the proposed constructs require empirical validation, their theoretical foundations are individually well established, and the framework is positioned as a complementary layer that enhances rather than replaces established practice. The principal limitation of the study is the absence of primary empirical data; all proposed constructs are explicitly formulated as testable propositions, and the research agenda for field validation is set out in Section 12.2.
Abstract: Reliability-Centered Maintenance (RCM) has served as the dominant industrial maintenance philosophy for nearly five decades, delivering substantial gains in safety, availability, and cost control. However, its core vocabulary, built around Failure Mode, Mean Time Between Failures, and the Potential-to-Functional Failure curve, frames organizational...
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Research Article
Why Disclosure Regimes Fail to Produce Accountability:
A Theory of Transparency Architecture
Amanda Reid*
Issue:
Volume 10, Issue 2, December 2026
Pages:
35-50
Received:
27 July 2026
Accepted:
5 August 2026
Published:
22 August 2026
Abstract: Contemporary governance regimes rely on disclosure mandates to render complex organizations accountable, yet the expansion of transparency reporting in platform governance, financial markets, and environmental policy has produced no commensurate expansion in oversight capacity. This persistent gap between disclosure volume and accountability motivates the present study. This Article argues that the gap arises because prevailing approaches misspecify transparency as a binary or scalar property, obscuring a structural problem: the systematic decoupling of disclosure breadth, informational resolution, and reporting institutionalization. This misspecification is not incidental but structural, since the measurement frameworks used to evaluate transparency actively incentivize the failure modes they are designed to detect. To address this problem, the Article develops a general theory of transparency architecture failure and proposes the Transparency Architecture Typology, which disaggregates transparency into three analytically distinct dimensions and identifies the mechanisms (compliance optimization, template rigidity, and informational cost asymmetry) that systematically drive disclosure regimes toward formally compliant but informationally inadequate configurations. From this framework, six theoretical propositions are derived, each specifying falsifiable conditions that anchor an empirical research program. The account is grounded in illustrative evidence drawn from platform disclosure episodes and financial reporting, which confirms that the framework’s structural predictions correspond to identifiable patterns in the observable record. The Article concludes by reframing transparency as an epistemic design problem and by specifying the architectural conditions under which disclosure can generate the informational basis that accountability requires, with direct implications for the design of mandatory disclosure regimes such as the European Union’s Digital Services Act.
Abstract: Contemporary governance regimes rely on disclosure mandates to render complex organizations accountable, yet the expansion of transparency reporting in platform governance, financial markets, and environmental policy has produced no commensurate expansion in oversight capacity. This persistent gap between disclosure volume and accountability motiva...
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Case Report
Geopolitical Sustainability of Powering Distributed Artificial Intelligence in Pakistan
Babar Shahzad Chaudary,
Petri Pulli*
Issue:
Volume 10, Issue 2, December 2026
Pages:
51-67
Received:
18 September 2026
Accepted:
30 September 2026
Published:
23 October 2026
DOI:
10.11648/j.stpp.20261002.13
Downloads:
Views:
Abstract: Artificial intelligence (AI) is increasingly deployed across a continuum ranging from stationary data centers and semi-stationary computing platforms to autonomous vehicles, robots, wearable devices, implants, and Internet of Things nodes. Across this distributed continuum, reliable power supply and the availability of critical raw materials become system-level constraints. This study investigates how power-supply requirements of distributed AI propagate into material and geopolitical dependencies, with particular attention to Pakistan. A Design Science Research approach is applied to a representative wearable-edge-cloud healthcare architecture for assisting visually impaired persons. The artefact is decomposed into power, sensing, communication, computation, and interaction subsystems; representative components are mapped to critical materials; materials are grouped by affinity; and mining, refining, and geographic concentration are examined using peer-reviewed literature and authoritative mineral and energy sources. The analysis identifies recurring dependencies on lithium, graphite, copper, cobalt, rare-earth elements, semiconductor materials and, for prospective hydrogen configurations, platinum-group metals. It also shows that cloud offloading shifts rather than removes material dependency because communication, data center, grid, and backup-energy infrastructures introduce additional upstream requirements. For Pakistan, the study distinguishes documented mineral production and resource development from prospective geological occurrences and downstream refining capability. The results indicate that geological endowment alone does not ensure access to technology-grade materials. The paper therefore contributes a traceable analytical chain linking AI service architecture, power subsystems, component/material dependencies, geographic supply concentration, and geopolitical vulnerability. Scenario analysis is used as a stress test rather than a prediction, highlighting the value of diversified sourcing, processing capability, strategic cooperation, and adaptable system design for resilient distributed AI deployment.
Abstract: Artificial intelligence (AI) is increasingly deployed across a continuum ranging from stationary data centers and semi-stationary computing platforms to autonomous vehicles, robots, wearable devices, implants, and Internet of Things nodes. Across this distributed continuum, reliable power supply and the availability of critical raw materials become...
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