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Research/Technical Note
Structural Performance of an Articulating Aluminum Stair System Under Variable Inclination Angles
Nikhilkumar Patel*
Issue:
Volume 11, Issue 5, October 2026
Pages:
104-112
Received:
12 August 2026
Accepted:
21 August 2026
Published:
9 September 2026
Abstract: Articulating stair systems provide temporary access across changing elevations by allowing the stair frame to rotate while the walking treads remain approximately level. The resulting structure is not geometrically fixed: deployment angle changes effective member length, load path, bending demand, and stability. This study develops an angle-aware structural verification framework for an 18-step, 36 in wide aluminum stair system and compares two documented finite-element design states at 55° and 30°. The baseline structure uses 6061-T6 aluminum and was evaluated in SAP2000 using the load framework and member resistance procedures documented in the source structural calculation package, including ASCE/SEI 7-16, the 2022 California Building Code, and the 2020 Aluminum Design Manual. The governing side beam/stringer combined demand-to-capacity ratio increased from 0.731 at 55° to 0.948 at 30°, corresponding to a 29.7% increase in critical utilization and a reduction in remaining unity margin from 26.9% to 5.2%. Decomposition of the interaction check showed that major-axis bending governed the change: the major bending demand-to-capacity contribution increased from 0.661 to 0.892, while major bending demand increased from 1.353 to 1.785 ft-kip. At the same time, the reported axial-compression capacity of the side member decreased from 1.756 to 0.673 kip because of the longer effective member length and associated buckling response in the shallow configuration. Tread-member utilization remained low, decreasing from 0.034 to 0.017. The results demonstrate that the shallow-angle configuration, rather than the steep-angle configuration, controls the baseline unbraced system. The scientific contribution is a configuration-dependent interpretation of articulating stair behavior in which inclination is treated as an explicit structural design variable. The proposed framework can be extended to full-angle parametric analysis, reinforced configurations, connection assessment, fatigue studies, and experimental validation.
Abstract: Articulating stair systems provide temporary access across changing elevations by allowing the stair frame to rotate while the walking treads remain approximately level. The resulting structure is not geometrically fixed: deployment angle changes effective member length, load path, bending demand, and stability. This study develops an angle-aware s...
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Research Article
Low-Cost Laser Decapsulation of Wire-Bonded Memory Packages with Dual Thermal Gating for Forensic Data Preservation
George Lloyd*
Issue:
Volume 11, Issue 5, October 2026
Pages:
113-123
Received:
14 August 2026
Accepted:
24 August 2026
Published:
15 September 2026
Abstract: Chip-off examination remains the method of last resort in digital forensics, applied when a device is locked, damaged or non-responsive, and it is the only route to data on many embedded targets such as vehicle event recorders and dashcams. The dominant removal technique is thermal reflow at approximately 360°C, and this is destructive to the evidence it recovers: charge leakage from flash memory is Arrhenius in temperature, so two minutes at 250°C consumes retention equivalent to centuries of room-temperature storage. This work develops a lower-temperature alternative using a consumer-grade 455 nm diode laser costing a small fraction of industrial equipment, together with an open-source browser-based tool that predicts thermal behaviour and gates recipes against two independent safety limits: wire-bond intermetallic damage and charge-retention loss. A finite element campaign in COMSOL Multiphysics characterised an eMMC package under a six-pass recipe. Two structural findings emerged. The bond-plane bulk temperature proved independent of remaining encapsulant thickness, because in quasi-steady state all absorbed power crosses the bond plane at fixed loop height regardless of the cap above it, which places the entire pass-to-pass risk in the per-pulse transient. Resolving finite spot size rather than assuming a one-dimensional heat source changed the predicted bond temperature from 181 to 272°C, which would condemn the process, to 94 to 139°C, which clears it. The campaign also identified two compensating errors in the tool's own analytical gate, which was corrected against the simulation. A single bench measurement, of laser spot size, returned 0.08 mm and satisfied a criterion recorded in advance. The wider bench validation programme is specified in full but was not executed, so the thermal model retains unverified status and all thermal figures reported are predictions rather than measurements. The claim advanced is one of data preservation, which is independent of encryption because charge leakage flips physical cells regardless of their contents.
Abstract: Chip-off examination remains the method of last resort in digital forensics, applied when a device is locked, damaged or non-responsive, and it is the only route to data on many embedded targets such as vehicle event recorders and dashcams. The dominant removal technique is thermal reflow at approximately 360°C, and this is destructive to the evide...
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Research Article
Modelling and Simulation for Engineering Design: A Case Study of Second Order Differential Equations
Issue:
Volume 11, Issue 5, October 2026
Pages:
124-131
Received:
4 April 2026
Accepted:
14 April 2026
Published:
22 September 2026
Abstract: This study investigates the application of second-order differential equations in the modelling and simulation of engineering systems, with a mass–spring system adopted as a representative case study for vibration-based design problems. The aim is to demonstrate how analytical and numerical approaches can be integrated to accurately predict system dynamics and support engineering design decisions. The governing equations are derived from Newton’s second law and solved analytically using characteristic equation methods, while numerical solutions are obtained using the fourth-order Runge–Kutta technique. Key system parameters, including mass, damping coefficient, and spring stiffness, are defined and used to simulate system response under dynamic conditions. The results show strong agreement between analytical and numerical solutions, validating the accuracy of the computational approach. Furthermore, the simulations reveal that system performance is highly sensitive to damping and stiffness variations, which directly influence oscillation amplitude, settling time, and stability. The findings demonstrate that second-order differential equation models provide a robust framework for predicting system behaviour and optimizing engineering design. It is concluded that integrating modelling and simulation techniques into computer-aided design (CAD) environments can significantly enhance design efficiency and performance evaluation. The study recommends the incorporation of advanced simulation-driven tools and intelligent control strategies to further improve the reliability and adaptability of engineering systems.
Abstract: This study investigates the application of second-order differential equations in the modelling and simulation of engineering systems, with a mass–spring system adopted as a representative case study for vibration-based design problems. The aim is to demonstrate how analytical and numerical approaches can be integrated to accurately predict system ...
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Research Article
AI-Driven Optimization of Smart Energy Systems Using Advanced Materials and IoT for Sustainable Environments in Emerging Economies
Djilali Khaine*
Issue:
Volume 11, Issue 5, October 2026
Pages:
132-140
Received:
3 September 2026
Accepted:
20 September 2026
Published:
23 October 2026
Abstract: The transition toward sustainable energy systems requires the integration of advanced digital technologies, intelligent control strategies, and high-performance materials capable of improving energy efficiency while reducing environmental impacts. In this context, the convergence of Artificial Intelligence (AI), the Internet of Things (IoT), and advanced energy materials offers significant opportunities for developing more adaptive, predictive, and sustainable energy systems. This study proposes an integrated framework combining AI, IoT, and advanced energy materials for the monitoring, prediction, optimization, and intelligent management of smart energy systems. The proposed architecture is structured into four complementary layers: intelligent sensing and IoT-based data acquisition, secure data transmission and data preprocessing, AI-based prediction and decision-making, and dynamic energy optimization. Linear Regression (LR), Random Forest (RF), and Long Short-Term Memory (LSTM) models are considered as representative approaches for energy-consumption prediction, enabling the analysis of relationships between energy demand and relevant environmental and operational variables. The methodology incorporates climatic conditions, indoor temperature and humidity, occupancy, energy demand, solar-related parameters, and material-related thermal characteristics. Advanced materials, including thermal energy storage and phase-change materials, are considered as functional components capable of improving thermal stability and reducing energy demand. Experimental and real-world evidence from international building-energy studies supports the feasibility of the IoT-AI and advanced-material components. In addition, the UCI Appliances Energy Prediction dataset provides an experimentally measured benchmark for investigating data-driven energy prediction using real building-energy and environmental measurements. The integrated framework further introduces multi-objective optimization to balance energy consumption, operating costs, carbon emissions, thermal performance, and system constraints. By establishing a continuous feedback loop between sensing, prediction, optimization, and control, the proposed approach provides a flexible basis for intelligent energy management. The framework is designed to be transferable to buildings and distributed energy systems in emerging economies, where energy efficiency, environmental sustainability, digitalization, and resource constraints represent major challenges. Overall, the study highlights the potential of integrating AI, IoT, and advanced materials as complementary technologies for developing resilient, efficient, and sustainable smart energy systems.
Abstract: The transition toward sustainable energy systems requires the integration of advanced digital technologies, intelligent control strategies, and high-performance materials capable of improving energy efficiency while reducing environmental impacts. In this context, the convergence of Artificial Intelligence (AI), the Internet of Things (IoT), and ad...
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Research Article
DMAIC, Augmented: Generative AI Strengthens Lean Six Sigma Execution
Oleg Smirnov*
Issue:
Volume 11, Issue 5, October 2026
Pages:
141-146
Received:
16 May 2026
Accepted:
26 May 2026
Published:
26 October 2026
Abstract: This article examines how generative artificial intelligence (AI) assistants can strengthen Lean Six Sigma (LSS) execution across every phase of the Define-Measure-Analyze-Improve-Control (DMAIC) methodology. The objective is to give LSS practitioners field-tested patterns, quantified cycle-time data, and a governance framework for integrating AI assistants into quality-improvement projects without compromising methodological rigor. The investigation draws on recent industry deployments using Anthropic’s Claude assistant and a construct called skills: versioned playbooks that bundle written instructions, scripts, reference data, and validation rules into reusable artifacts. Methods include direct measurement of cycle-time deltas across Define, Measure, and Control tasks; four worked Analyze-phase examples spanning hypothesis testing, Measurement System Analysis, Statistical Process Control, and regression interpretation; and analysis of a multi-skill portfolio deployed at a small aviation services client. Results demonstrate substantial efficiency gains: project-charter drafting time fell from 90 to 120 minutes to roughly 6 minutes; monthly payroll consolidation fell from 90 minutes to under 30 seconds (a 99.4 percent reduction) with the first-pass error rate dropping to zero; cross-system benefits reconciliation fell from 4 hours to under 60 seconds, with monthly completion improving from 5 of 12 cycles to 12 of 12. The aggregate skills portfolio at one client achieved approximately 84 hours of administrative cycle-time savings per year. The article identifies six required governance controls (human review, version control, controlled prompts, sensitive-data boundaries, hallucination mitigation, and auditability) and aligns them with ISO 9001: 2015 and the NIST AI Risk Management Framework. The conclusion is that generative AI does not alter DMAIC methodology; it lowers the cost of executing each phase well, expanding the share of LSS that is practiced in fact rather than only in theory. The findings support Master Black Belts and quality champions in deliberately piloting AI-enabled tooling, prioritizing Control-phase tasks first, and treating skill development as a formal deliverable with version control, ownership, and quality gates.
Abstract: This article examines how generative artificial intelligence (AI) assistants can strengthen Lean Six Sigma (LSS) execution across every phase of the Define-Measure-Analyze-Improve-Control (DMAIC) methodology. The objective is to give LSS practitioners field-tested patterns, quantified cycle-time data, and a governance framework for integrating AI a...
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Research Article
A Device for Laying Film on Potato Ridges
Issue:
Volume 11, Issue 5, October 2026
Pages:
147-151
Received:
12 October 2026
Accepted:
21 October 2026
Published:
31 October 2026
DOI:
10.11648/j.ajmie.20261105.16
Downloads:
Views:
Abstract: This article presents the results of field trials and an economic efficiency assessment of a developed film-laying machine designed for potato ridges. The main objective of the study was to evaluate the machine’s operational performance, the quality of the technological process, and its economic advantages compared with the existing manual method. The developed machine was aggregated with tractors of classes 0.9–1.4 and tested under actual production conditions on farms in the Namangan region of Uzbekistan. During the field trials, several key indicators were determined to assess the quality and efficiency of the machine’s operation, including soil density, planting depth, ridge-top width, ridge height, and fuel consumption. The experimental results showed that soil density ranged from 1.14 to 1.16 g/cm3, planting depth was 6.7–7.7 cm, ridge-top width was 26.8–29.0 cm, and ridge height was 17.3–18.2 cm. Fuel consumption during operation ranged from 3.1 to 3.9 kg/ha. These indicators were used to characterize the machine’s performance and its suitability for use in potato cultivation. In addition to the field trials, technical and economic calculations were conducted to determine the practical benefits of introducing the developed machine into agricultural production. The economic assessment focused on labor requirements and operating costs per hectare, which are important factors affecting the efficiency of potato cultivation. The results demonstrated that, compared with the existing manual method, the proposed machine reduced labor requirements by 86.23% and operating costs per hectare by 23.51%. These findings indicate that the developed film-laying machine can improve the mechanization of potato ridge preparation, reduce the labor burden on agricultural workers, and lower production costs. Overall, the study confirms the machine’s potential to improve operational efficiency and support more economical potato production under the tested field conditions.
Abstract: This article presents the results of field trials and an economic efficiency assessment of a developed film-laying machine designed for potato ridges. The main objective of the study was to evaluate the machine’s operational performance, the quality of the technological process, and its economic advantages compared with the existing manual method. ...
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