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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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Causal SEO Experimentation in Applied Digital Marketing: Quasi-Experimental Methods for Measuring Organic Impact Under Confounding Irfan Nurdiansyah Irfan Nurdiansyah
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents a causal experimentation framework for SEO that is designed to be practical under real-world constraints where classical randomized controlled trials are often infeasible, and it formalizes quasi-experimental approaches that can quantify organic impact using page-group level designs, matched controls, and time-series counterfactual modeling. The methodology integrates difference-in-differences, synthetic control, and Bayesian structural time series approaches within an operational workflow that begins with hypothesis and mechanism specification, continues through intervention scoping and eligibility gating, and ends with robustness checks that explicitly test sensitivity to indexation delays, lag structure, and spillover effects across query and page clusters. A generic case design is used to demonstrate how the framework can estimate the causal lift of three common SEO interventions, namely title and snippet rewrites, internal linking reinforcement, and performance improvements, while controlling for temporal demand changes and segment-level volatility. Results show that the largest source of measurement error is not statistical noise but design leakage, particularly when treatment and control groups share overlapping query intent or when interventions cause redistribution of impressions within a site rather than net growth, and the study therefore emphasizes guardrails including intent isolation, contamination monitoring, and pre-registered success metrics. The article contributes to Techne’s applied technology scope by translating SEO evaluation into an engineering measurement problem, providing implementable causal designs, and offering decision-ready reporting templates that reduce false positives and improve the reliability of organic optimization programs.
Predictive Maintenance for Rotating Equipment in Process Manufacturing: A Reliability-Based Framework Using Vibration, Thermal, and Electrical Signatures Dimas Arya Nugroho Dimas Arya Nugroho; Reza Mahendra Saputra Reza Mahendra Saputra
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents a reliability-based predictive maintenance framework that integrates vibration condition indicators, infrared thermography, and motor electrical signatures into a unified decision pipeline that supports early detection, fault isolation, and maintenance prioritization under realistic noise, load variation, and data completeness constraints. The framework is engineering-oriented rather than tool-oriented, meaning that it defines measurable acceptance limits, uncertainty handling, and verification pathways so that maintenance decisions are defensible and repeatable, and it evaluates performance using detection reliability, lead time, false alarm governance, and economic consequence rather than using model accuracy in isolation. A generic case design is developed for typical process industry assets, and representative datasets are used to demonstrate how feature distributions shift across failure modes such as bearing wear, misalignment, imbalance, cavitation, and electrical asymmetry, while showing how multi-sensor fusion reduces decision uncertainty and improves time-to-decision compared with single-signal approaches. Results indicate that vibration broadband velocity and acceleration envelope metrics provide the earliest warning for mechanical degradation but are vulnerable to confounding under load and hydraulic variability, that thermal imaging strengthens fault localization and reduces nuisance alarms when integrated as a verification layer, and that motor current signature indicators improve detection of electrical defects and rotor bar issues that do not immediately appear in mechanical vibration. The study concludes with practical guidance for implementation, including recommended monitoring intervals, threshold governance strategies aligned with reliability criticality, and data-driven visualization templates suitable for Techne submissions and industrial reporting.
Process Control Reliability in Wastewater Treatment: Data-Driven Monitoring of Nutrient Removal, Aeration Efficiency, and Compliance Risk Under Sensor Drift and Influent Variability Michael K. Jensen Michael K. Jensen; Ethan W. Brooks Ethan W. Brooks; Amelia J. Collins Amelia J. Collins
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article develops an applied engineering framework for monitoring and controlling activated sludge nutrient removal with an emphasis on compliance risk, aeration energy efficiency, and sensor reliability. The framework integrates mass-balance-informed indicators, statistical drift detection for key online sensors, and a tiered alarm strategy that distinguishes transient disturbances from sustained process deterioration. A generic case-based evaluation is presented for nitrification and denitrification performance under influent ammonia shocks, dissolved oxygen control variability, and sensor drift scenarios, and performance is evaluated using probability of limit exceedance, time-to-detection, and energy-normalized removal efficiency. Results show that dissolved oxygen and ammonia sensor drift can create false confidence or false alarms depending on control logic, that aeration dominates energy consumption and must be governed by risk-aware setpoints rather than fixed targets, and that combining online monitoring with periodic laboratory validation improves reliability by preventing drift from being absorbed as “normal.” The paper provides copy-ready KPI tables and figure prompts for OJS submission and plant reporting, supporting implementation in diverse plant contexts.
Cold Chain Logistics Thermal Reliability: Modeling Temperature Excursions, Sensor Uncertainty, and Time-to-Intervention for Perishable Supply Chains James H. Whitaker James H. Whitaker; Emily R. Dawson Emily R. Dawson
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article advances a thermal reliability engineering framework for perishable cold chains that explicitly links (i) excursion event structure (probability, cumulative excursion minutes, and maximum duration), (ii) sensor uncertainty (noise, bias, drift, and missingness), and (iii) time-to-intervention (detection latency plus operational response delay) into a unified decision model for quality protection and compliance risk governance. The framework decomposes risk by process stage (warehouse, loading/staging, line-haul, cross-dock, last-mile) and treats monitoring as a decision pipeline whose performance is evaluated by missed-excursion rate, false-alarm rate, and tail-risk sensitivity rather than by point accuracy alone. A representative case-based analysis, calibrated to typical refrigerated vehicle dynamics reported in the literature, demonstrates that operational exposure during staging and cross-docking dominates excursion minutes and upper-tail risk, often outweighing marginal benefits from lowering refrigeration setpoints. Results further show that multi-sensor placement improves detection of localized hot spots only when persistence logic and stage-aware thresholds are applied; otherwise, false alarms rise and intervention effectiveness falls. The paper concludes with governance recommendations for stage-specific thresholds, drift-aware calibration policies, and intervention prioritization rules that are immediately usable for KPI reporting and audit-ready cold chain control.
Additive Manufacturing Quality Control Under Production Variability: Quantifying Dimensional Accuracy, Surface Integrity, and Process Stability Using In-Process and Post-Process Metrology Nabila S. Hidayat Nabila S. Hidayat; Fajar Prakoso Wicaksono Fajar Prakoso Wicaksono; Ardiansyah Putra Kurniawan Ardiansyah Putra Kurniawan
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article proposes an applied engineering quality control framework that treats part quality as the output of a controlled process with measurable uncertainty rather than as a post hoc inspection event. The framework integrates in-process monitoring outputs with post-process metrology to quantify how variability propagates into dimensional deviation and surface roughness, and it formalizes decision governance using statistically defined acceptance criteria, false reject constraints, and escape risk limits. A production relevant tiered inspection strategy is evaluated conceptually through three inspection tiers: rapid in-process screening, intermediate dimensional sampling, and final verification metrology. Representative results patterns show that dimensional deviation is strongly location dependent within the build volume, surface roughness is disproportionately sensitive to build orientation and energy density, and anomaly score screening can reduce inspection burden only when thresholds are governed to control nuisance alarms and periodically recalibrated without absorbing drift into the baseline. The paper concludes with practical guidance for inspection planning, acceptance limit design, baseline management, and traceable release logic aligned with standards oriented requirements for purchased AM parts and critical applications.
The Impact of Load Variability on Data Center Infrastructure: Quantifying Resilience and Operational Risk Nur Aisyah Ramli Nur Aisyah Ramli; Muhammad Fikri Hasan Muhammad Fikri Hasan
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an applied reliability engineering framework for data center operations that quantifies cooling resilience, power quality stability, and uptime risk using measurable operational indicators rather than purely qualitative compliance checklists. The framework models thermal risk through time-to-threshold metrics derived from rack inlet temperatures, airflow margin indicators, and cooling response latency, while power risk is modeled using voltage and frequency quality statistics, transient event rates, and uninterruptible power supply (UPS) stress indicators. A generic case-based evaluation demonstrates how normal load variability and maintenance switching events shift the distributions of thermal and electrical indicators, and how risk-based governance can reduce nuisance alarms while improving early detection of conditions that precede service-impacting incidents. Results show that the most common reliability bottleneck is not total capacity, but degraded margin caused by uneven airflow distribution, partial containment failures, and localized hot spots, and that power disturbances primarily elevate risk when combined with reduced thermal margin or when UPS response is delayed by maintenance states. The paper provides copy-ready tables for operational KPI reporting, along with prompts for scientific figures suitable for Techne publication, and concludes with implementation guidance for alarm governance, preventive maintenance scheduling, and integrated power-thermal risk management.
Yield Reliability Engineering in Semiconductor Manufacturing: Quantitative Control of Defectivity, Overlay, and Linewidth Under Process Drift Nguyen Quang Huy Nguyen Quang Huy; Tran Thi Bao Linh Tran Thi Bao Linh; Phan Minh Tuan Phan Minh Tuan
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents a quantitative yield reliability framework that models yield loss as a consequence of uncertainty propagation through process control loops, linking defectivity, overlay, and linewidth control to operational decisions such as tool matching, run-to-run control tuning, and lot disposition. The proposed approach integrates metrology uncertainty characterization, process drift modeling, multivariate statistical process control, and risk-based hold and release governance, with performance evaluated using probability of excursion detection, false alarm burden, time-to-decision, and expected yield at risk. A generic case-based analysis is developed for a representative lithography-etch stack where overlay and critical dimension interact with defectivity, demonstrating how random variation and systematic drift generate different failure signatures and require different control actions. Results indicate that the largest operational gains come from governance rather than from aggressive thresholding, specifically by combining stage-aware baselines, persistence rules, and verification pathways that separate true drift from transient noise and measurement bias, and by prioritizing control actions based on yield-risk impact rather than on deviation magnitude alone. The paper provides copy-ready tables and figure prompts suitable for Techne submission and for manufacturing reporting, and concludes with practical guidance for implementing yield reliability engineering as a decision system that balances sensitivity, stability, and throughput.
Reliability and Safety-Driven Availability in Railway Signaling: Quantitative Modeling of Failure Modes, Degraded Operations, and Delay Risk I Made Arya Pratama I Made Arya Pratama; Ni Luh Putu Sari Dewi Ni Luh Putu Sari Dewi; Bagus Aditya Wicaksana Bagus Aditya Wicaksana
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an applied, quantitative framework that integrates safety-driven system behavior with availability and delay modeling for modern signaling architectures, covering interlocking, track detection (track circuits and axle counters), point machines, wayside signals, and train-to-wayside communication components typical of CBTC/ETCS-like systems. The framework combines reliability block diagrams and Markov availability modeling with delay propagation estimates and decision governance for alarms and degraded-mode escalation, enabling evaluation of design and operational strategies using measurable criteria such as probability of service-impacting unavailability, expected delay minutes per day, false alarm burden, and recovery time distributions. A generic, non-site-specific case design is used to compare three operational strategies: reactive maintenance with conservative degraded working, preventive maintenance with fixed intervals, and condition-based maintenance with governed diagnostics and targeted response. Results show that the largest availability gains typically come from reducing mean time to repair and controlling diagnostic escalation rather than from marginal improvements in component failure rate, and that delay risk is dominated by a small fraction of prolonged incidents where recovery is slowed by troubleshooting ambiguity and operational coordination. The paper also demonstrates that alarm governance and verification pathways materially reduce unnecessary service restrictions without compromising fail-safe principles by ensuring that uncertain faults trigger the least disruptive safe response compatible with evidence quality. Practical outputs include copy-ready tables for reliability and delay KPIs and figure prompts for scientific visualizations suitable for Techne submissions and engineering reporting.
Power Grid Protection: Quantitative Engineering of Dependability, Security, and Cascading Risk Under Modern Operating Conditions Sokha Chan Sokha Chan; Sophea Chea Sophea Chea; Dara Heng Dara Heng
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents an applied engineering framework for quantifying protection reliability in terms of misoperation risk, failure-to-trip risk, and their downstream consequences for unserved energy and cascading probability. The framework models protection as a decision pipeline in which measurement uncertainty, logic design, communications, and human governance jointly determine outcomes, and it evaluates strategies using metrics meaningful for utility operations: probability of correct operation, misoperation rate, mean time to recovery, expected unserved energy, and risk-weighted outage impact. A generic transmission-and-distribution boundary case is developed with representative line, transformer, and bus protection functions, and scenario-driven quantitative results are provided for instrument transformer saturation events, evolving fault current conditions under high inverter penetration, communication-aided scheme degradation, and settings lifecycle errors. Results indicate that many of the most consequential reliability improvements arise from governance and verification pathways, particularly settings validation, event-driven self-monitoring, and staged fallback logic, rather than from incremental relay hardware upgrades alone. The paper concludes with implementation guidance for condition-based maintenance, alarm and event triage, and risk-based testing intervals, and it provides copy-ready tables and scientific figure prompts suitable for Techne submissions and operational reporting.
Topography-Aware Geospatial Digital Marketing: A Systematic Literature Synthesis of Local SEO, Spatial Targeting, and Accessibility-Driven Consumer Intent Maria Lourdes Santos Maria Lourdes Santos; Jose Miguel Dela Cruz Jose Miguel Dela Cruz; Angela Mae Villanueva Angela Mae Villanueva
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 2 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents a systematic literature synthesis (SL) that consolidates research across digital marketing, information systems, spatial analytics, and urban studies to build an engineering-oriented understanding of how topography and geospatial constraints influence local SEO performance, location-based advertising effectiveness, and omnichannel conversion outcomes. Using a transparent SL protocol, the review organizes findings into thematic clusters: (1) geospatial signals in local search and discovery, (2) geo-targeting and geo-fencing for paid media, (3) accessibility-based segmentation and service areas, (4) place-based content strategy and location credibility, (5) measurement, attribution, and privacy constraints, and (6) operational models and decision support for topography-aware marketing. The synthesis identifies a persistent gap: limited integration of topographic friction and network travel-time into mainstream digital marketing workflows, despite strong evidence that accessibility mediates consumer intent and moderates campaign outcomes. The article proposes a conceptual framework, offers copy-ready tables for SL reporting and practice translation, and provides figure prompts for scientific visualizations suitable for Techne submissions. The resulting contribution is an applied roadmap for designing digital marketing as a location-intent system grounded in physical accessibility rather than simplistic distance, with implications for local SEO governance, media efficiency, conversion reliability, and equitable service delivery.

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