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Techne: Journal of Engineering, Technology and Industrial Applications
Published by Kalam Practica Media
ISSN : -     EISSN : 31246559     DOI : -
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation
Techne: Journal of Engineering, Technology and Industrial Applications is a peer-reviewed open-access journal dedicated to advancing scholarly work in engineering, applied technology, and industrial innovation. Techne publishes high-quality empirical research, technical reports, experimental studies, design analyses, case studies, and emerging technology reviews that contribute to the development and application of engineering solutions. The journal aims to bridge academic research and real-world technological practices by providing a platform for researchers, engineers, practitioners, and industry experts to disseminate new insights. Techne encourages submissions that demonstrate originality, methodological rigor, and practical value in supporting technological growth and industrial problem-solving. All submitted manuscripts undergo an objective and constructive review process conducted by experts in relevant fields. Techne is published by the Kalam Practica Research Group and operates under an open-access policy to ensure global accessibility of scientific knowledge. Scopes include (but are not limited to): Mechanical, electrical, and civil engineering Industrial systems and manufacturing technology Information technology and applied computing Automation, robotics, and control systems Energy systems and sustainable engineering Material science and industrial design Geospatial engineering and technical instrumentation Innovation, prototyping, and applied industrial research Techne welcomes interdisciplinary works and studies that integrate engineering with technology-driven industrial applications.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 42 Documents
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Data Center Thermal and Energy Efficiency: Modeling Sensor Degradation, Control Latency, and Hotspot Probability During Workload Transitions Jose Antonio Rivera Jose Antonio Rivera
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article develops an engineering-oriented framework that treats data center cooling as a reliability decision system, quantifying how uncertainty propagates through measurement, state estimation, threshold governance, and control execution to determine hotspot exceedance probability, excursion duration distributions, time-to-mitigation, nuisance interventions, and energy overhead. A scenario-based comparative quantitative study is presented for a representative row-based data hall with variable-speed CRAC/CRAH control and workload-driven power variability, comparing four operational architectures: baseline threshold control, increased sensing without governance, model-predictive control with limited drift handling, and a governance-optimized two-tier architecture combining nuisance-constrained alarms, drift-aware verification, workload-aware preemptive control, and staged mitigation actions. Results indicate that (i) tail risk of hotspot duration is dominated by control latency and sensor bias drift rather than by average temperature, (ii) dense sensing reduces random uncertainty but can increase nuisance intervention if alarms are not governed, and (iii) a governed two-tier strategy reduces hotspot tail risk while maintaining energy efficiency by shifting effort from disruptive interventions to bounded verification and preemptive setpoint shaping. The paper provides copy-ready tables and full prompts for data-driven figures suitable for Techne submission and adaptation to site-specific telemetry.
Integrated Decision Framework for Railway Signaling and Train Protection: Modeling Latency, Detection Uncertainty, and Capacity-Safety Trade-Offs Under Faults Nur Atiqah Hamzah Nur Atiqah Hamzah; Sokheng Tep Sokheng Tep
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that treats railway signaling as an end-to-end decision pipeline and quantifies how uncertainty propagates through occupancy detection, train localization, interlocking logic, radio block center messaging, onboard supervision, and operational recovery procedures to determine risk-relevant metrics such as probability of separation violation, probability of spurious braking, time-to-restrict and time-to-restore distributions, and expected capacity degradation during degraded modes. A scenario-based quantitative study is developed around three representative architectures that span fixed-block signaling with track circuits, fixed-block signaling with axle counters, and a moving-block style supervision concept consistent with modern CBTC or ETCS-level architectures, and for each architecture the study compares baseline thresholds and governance against a reliability-governed strategy that uses nuisance-constrained decision limits, drift-aware plausibility checks, redundant evidence fusion, and staged interventions. Results show that the tail of recovery time and the tail of nuisance restriction duration dominate operational cost, while dangerous exposure is dominated by rare false-clear and localization integrity failures that become most consequential when decision latency is long and when degraded-mode rules are ambiguous or inconsistently applied. The paper provides copy-ready tables and full prompts for data-driven figures suitable for Techne submission, emphasizing applied engineering interpretation rather than purely theoretical safety discussions.
Performance Metrics for Leak Detection and Pressure Control in Urban Water Networks: Assessing Latency, Drift, and Response Efficacy Randy A. Cruz Randy A. Cruz
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that treats leak detection and pressure management as an end-to-end decision system, modeling uncertainty propagation from instrumentation through inference and threshold governance into outcomes that utilities actually manage, including probability of missed leaks, false alarm rate, time-to-detection and time-to-intervention distributions, expected volume loss before containment, and probability of customer pressure noncompliance under mitigation actions. A scenario-based quantitative study is developed for a generic but realistic distribution network with district metered areas and pressure zones, using flow and pressure telemetry augmented by periodic acoustic surveys, and four operational architectures are compared: baseline fixed-threshold minimum night flow, increased sensing without governance, model-based residual detection with limited drift management, and a governance-optimized two-tier architecture that combines nuisance-constrained thresholds, drift-aware plausibility checks, adaptive confirmation sampling, and staged pressure interventions aligned with evidence strength. Results show that (i) leakage loss and customer impact are dominated by tail behavior in detection and verification latency rather than by mean leak rate, (ii) sensor drift and baseline instability drive false stability that delays detection when fixed thresholds are used, and (iii) reliability improves most when governance reduces long-tail verification times and when pressure management is staged to reduce loss without causing pressure violations. The paper provides copy-ready tables and complete prompts for data-driven figures suitable for Techne submission and for adaptation to utility telemetry datasets.
Dispatch Reliability in Commercial Aviation Maintenance Operations: Quantifying Delay Risk under Fault Uncertainty, MEL Governance, and Spare-Part Constraints Lim Wei Jun Lim Wei Jun; Tran Minh Khoa Tran Minh Khoa; Ploy S. Rattanakul Ploy S. Rattanakul
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents a reliability-centered engineering framework that treats maintenance dispatch as an end-to-end decision pipeline, explicitly modeling uncertainty propagation from fault detection and diagnostic confidence through MEL deferral decisions, spares availability, maintenance task duration variability, and crew scheduling constraints into distributional outcomes that operations manage, including probability of delay exceeding defined thresholds, expected delay minutes per departure, probability of cancellation, time-to-release distributions, and nuisance troubleshooting burden. A scenario-based quantitative study is developed for a representative narrow-body fleet operating a hub-and-spoke schedule, comparing four dispatch decision architectures: baseline reactive troubleshooting, enhanced diagnostics without governance, risk-based dispatch supported by confidence scoring, and a governance-optimized two-tier approach that constrains nuisance maintenance actions while preserving safety and compliance through standardized MEL decision rules, verification triggers, and spare-part risk pooling. Results show that (i) tail delay outcomes are dominated by diagnosis and spares-induced recovery latency rather than by mean task time, (ii) increased diagnostic messages without governance can increase nuisance actions and worsen punctuality, and (iii) the strongest reliability gains come from standardizing decision governance and aligning escalation with evidence confidence rather than from analytics alone. The paper provides up to three copy-ready tables and full prompts for data-driven figures suitable for Techne submission.
Quantifying Defect Escape Risk in Additive Manufacturing: The Impact of Sensor Uncertainty and Control Latency Nuraini Alwi Nuraini Alwi
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that models AM quality control as an end-to-end decision system, quantifying how uncertainty propagates from monitoring signals through feature extraction, thresholds, verification inspection, and corrective interventions into distributional outcomes that matter in production: probability of defect escape, probability of false alarm, scrap risk, rework burden, time-to-detection relative to layer deposition, and expected quality cost per part. A scenario-based quantitative study is developed for laser powder bed fusion (LPBF) manufacturing of safety-relevant components, comparing four quality control architectures: baseline post-build inspection, enhanced in-situ monitoring without governance, model-based anomaly scoring with limited drift handling, and a governance-optimized two-tier architecture that constrains nuisance alarms, uses drift-aware verification triggers, and applies staged corrective actions aligned with evidence strength and layer timing. Results show that (i) defect escape risk is dominated by decision latency and sampling limitations rather than by average signal quality, (ii) adding sensors without governance can increase scrap and operator fatigue due to nuisance triggers, and (iii) a governed two-tier approach reduces defect escape while stabilizing operational workload by using quantile-based alarm governance and early-stage corrective action windows. Up to three copy-ready tables and figure prompts are provided for Techne submission.
Thermal in Cold Chain Logistics: Modeling Time-Above-Threshold Risk under Sensor Uncertainty, Door-Open Events, and Packaging Variability Siti Farhana Ismail Siti Farhana Ismail
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that models cold chain thermal control as an end-to-end decision system and quantifies how uncertainty propagates from sensing and environment through exposure modeling and escalation logic into distributional outcomes that matter in operations, including probability of temperature threshold exceedance, expected time-above-threshold per shipment, probability of quality excursion beyond allowable exposure, and the effectiveness of mitigation actions such as pre-cooling, lane-specific packaging selection, and staged escalation during dwell. A scenario-based quantitative study is developed for generic refrigerated transport and cross-dock handling of high-risk perishables and temperature-sensitive products, comparing four operational architectures: baseline compliance logging, increased sensor density without governance, model-based exposure forecasting with limited drift handling, and a governance-optimized two-tier approach that constrains nuisance alarms while improving time-to-decision through drift-aware plausibility checks, door-event segmentation, and staged interventions. Results indicate that tail exposure behavior is dominated by door-open frequency and decision latency rather than by mean trailer temperature, that adding sensors without governance can increase workload and reduce response discipline, and that the two-tier governed approach reduces both exceedance probability and nuisance alarms while improving intervention timeliness, especially under high-variability loading conditions. Up to three copy-ready tables and full prompts for data-driven figures are provided for Techne submission.
Engineering for Cosmetic Product Quality and Supply Continuity: Modeling Defect Escape, Batch Release Latency, and Complaint Risk Under Measurement Uncertainty Sreymao Pech Sreymao Pech; Ayesha Rahman Ayesha Rahman
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that treats cosmetic quality assurance as an end-to-end decision system and quantifies how uncertainty propagates from incoming raw material variability through in-process controls, laboratory testing, and release decisions into distributional outcomes relevant to production and brand risk, including probability of defect escape, probability of false rejection, time-to-release distributions, complaint incidence risk, and expected cost per batch. A scenario-based quantitative study is developed for representative skin-care and color cosmetic products across three risk profiles, comparing four operational architectures: baseline end-of-line testing, increased testing density without governance, model-based risk scoring with limited drift handling, and a governance-optimized two-tier approach that constrains nuisance rejections while improving early detection through drift-aware controls, stratified sampling, and staged release decisions. Results indicate that defect escape is dominated by sampling and release latency tails rather than by mean lab accuracy, that expanding tests without governance can increase false rejection and slow release, and that a two-tier governed strategy reduces defect escape while stabilizing throughput and complaint risk. Up to three copy-ready tables and full prompts for data-driven figures are provided for Techne submission.
E-Commerce Fulfillment Reliability: Quantifying Order Promise Risk Under Inventory Inaccuracy, Pick-Pack Variability, and Carrier Uncertainty Budi Santosa Budi Santosa
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that models end-to-end promise fulfillment as uncertainty propagation across (i) inventory record confidence and SKU-level availability risk, (ii) pick-pack execution time variability including congestion and exception loops, and (iii) lane-dependent carrier transit time distributions that exhibit heavy tails and disruption regimes. The framework evaluates operational architectures in terms of distributional service outcomes relevant to engineering management, including probability of promise violation, conditional lateness severity, stockout-at-pick cancellation probability, wrong-item defect probability, and cost index under normal and disrupted conditions. A scenario-based quantitative study is developed for a generic multi-node network with two fulfillment centers and one drop-ship node serving standard and expedited commitments, and four architectures are compared: baseline fixed-buffer promise logic, increased automation without governance redesign, distribution-aware (quantile) promise setting with limited inventory control, and a governance-optimized two-tier approach that integrates inventory confidence scoring, staged verification for low-confidence commitments, dynamic routing under congestion risk, and dynamic carrier selection based on lane variance. Results show that reliability gains are driven more by controlling promise tail risk and preventing low-confidence inventory commitments than by improving mean pick rates alone, that adding automation without revising promise governance can increase mispromises during disruptions, and that the two-tier governed architecture reduces promise violations and cancellations while lowering exception-driven defects and stabilizing labor escalation. The article provides three copy-ready tables and complete prompts for scientific, data-driven figures suitable for Techne submission.
Risk-Aware Quality Assurance in Wastewater Treatment: Modeling Effluent Exceedance Probability Under Stochastic Influent and Sensor Decay Nguyễn Thị Thu Hà Nguyễn Thị Thu Hà
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that treats wastewater treatment control as an end-to-end decision and reliability system, quantifying how uncertainty propagates from sensing and influent disturbances through control actions and process dynamics into distributional outcomes that matter operationally: probability of exceeding effluent thresholds for ammonia, total nitrogen, and phosphate; time-above-limit; nuisance alarm rate; energy and chemical cost index; and time-to-recovery under upset events. A scenario-based quantitative study is developed for a generic activated sludge facility with nitrification–denitrification and chemical phosphorus removal, comparing four control architectures: baseline PID with fixed setpoints, increased sensor deployment without drift governance, model-based soft-sensing and predictive control with limited alarm governance, and a governance-optimized two-tier architecture that combines drift-aware sensor validation, redundancy and plausibility checks, event-segmented control actions, and staged alarms aligned to compliance risk rather than raw sensor thresholds. Results demonstrate that compliance risk is dominated by tail behavior in influent and by sensing drift interacting with slow biological dynamics, that adding sensors without governance can increase nuisance interventions and destabilize operation, and that the two-tier governed architecture reduces exceedance probability while lowering unnecessary chemical dosing and stabilizing operator workload. Three copy-ready tables and complete prompts for data-driven figures are provided for Techne submission.
Fintech Transaction Fraud Decision: Quantifying Loss, Friction, and Detection Risk Under Drift, Adversarial Adaptation, and Operational Latency Sophea Nguon Sophea Nguon; Sokly Phan Sokly Phan; Vuthy Chea Vuthy Chea
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 4 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an engineering-oriented framework that models fraud prevention as an end-to-end reliability system and quantifies how model uncertainty, drift, and decision latency propagate into distributional outcomes relevant to operations and governance, including fraud capture rate, false decline rate, expected net loss, customer friction cost, review workload, and time-to-decision. A scenario-based quantitative study is developed for card-not-present and account-to-account style transactions across normal and disruption regimes, comparing four architectures: baseline rules with static thresholds, ML scoring without calibration or governance, calibrated ML with cost-sensitive thresholds, and a governance-optimized two-tier architecture that combines calibrated risk scoring, uncertainty-aware routing to manual review, step-up verification for medium-risk cases, and dynamic thresholding under drift detection. Results show that ungoverned model deployment can reduce fraud loss but increase friction and false declines during drift, that calibrated thresholds improve stability but remain vulnerable when review capacity saturates, and that a two-tier governed approach reduces net loss while stabilizing customer impact and operational workload, particularly during fraud surges. Three copy-ready tables and complete prompts for data-driven figures are provided for Techne submission.

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