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Journal of Engineering Management and Systems Engineering
JEAVV
Journal of Engineering Management and Systems Engineering (JEMSE)
JERRSD
ISSN (print): 2958-3519
ISSN (online): 2958-3527
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2026: Vol. 5
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Journal of Engineering Management and Systems Engineering (JEMSE) is a peer-reviewed open-access journal dedicated to advancing the integration of engineering management principles with systems engineering methodologies. The journal provides a scholarly platform for studies that address the planning, analysis, design, implementation, and optimisation of complex engineering systems and organisational processes. JEMSE encourages contributions that strengthen methodological innovation while demonstrating strong relevance to industrial practice. Research topics include digital transformation in engineering operations, lifecycle and risk management, system modelling and decision support, socio-technical integration, and performance evaluation of engineering systems. The journal welcomes interdisciplinary perspectives that connect management strategies with advanced engineering technologies to support effective decision-making in dynamic environments. Committed to rigorous peer-review standards and timely dissemination of knowledge, JEMSE is published quarterly by Acadlore, with issues released in March, June, September, and December.

  • Professional Editorial Standards - Every submission undergoes a rigorous and well-structured peer-review and editorial process, ensuring integrity, fairness, and adherence to the highest publication standards.

  • Efficient Publication - Streamlined review, editing, and production workflows enable the timely publication of accepted articles while ensuring scientific quality and reliability.

  • Gold Open Access - All articles are freely and immediately accessible worldwide, maximising visibility, dissemination, and research impact.

Editor(s)-in-chief(2)
dragan marinković
Department of Structural Analysis, Technical University of Berlin, Germany
dragan.marinkovic@tu-berlin.de | website
Research interests: Structural Analysis; FEM based Real-Time Simulations; Smart Structures; Composite Materials; Transport and Logistics; Decision-Making Approaches
dragan pamucar
Faculty of Organizational Sciences, University of Belgrade, Serbia
dpamucar@gmail.com, dragan.pamucar@fon.bg.ac.rs | website
Research interests: Operational Research; Mathematical Programming; Multi-Criteria Decision Making; Uncertainty Theories; Fuzzy Sets and Systems; Neuro-Fuzzy Systems; Neutrosophic Sets; Rough Sets

Aims & Scope

Aims

The Journal of Engineering Management and Systems Engineering (JEMSE) is a forward-thinking publication that stands at the forefront of bridging engineering management with systems engineering. It distinguishes itself by diving deep into the multifaceted layers of these fields, underscoring their crucial role in driving innovation and efficiency in the broader engineering landscape. JEMSE's mission is to provide a dynamic forum for the exchange of groundbreaking ideas and methodologies, spotlighting the intricate interplay between management strategies and systems engineering solutions. The journal aims to reshape conventional understanding and practices, fostering a dialogue that spans from theoretical advancements to actionable engineering applications.

JEMSE is committed to advancing the knowledge frontier in engineering management and systems engineering. It invites contributions that challenge existing paradigms and introduce novel approaches to engineering problems. The journal prioritises in-depth exploration and rigorous analysis, ensuring that each publication not only adds to the academic discourse but also has practical relevance in the real world.

Key features of JEMSE include:

  • A strong emphasis on integrating systems engineering methodologies with advanced management practices across industrial sectors;

  • A focus on bridging theoretical frameworks and real-world engineering applications for innovation and efficiency;

  • Encouragement of interdisciplinary studies combining technology, management science, and decision analytics;

  • Promotion of sustainable, data-driven, and human-centred approaches in engineering systems development;

  • A commitment to advancing methodologies that enhance reliability, performance, and organisational resilience.

Scope

JEMSE welcomes theoretical, empirical, and applied research that advances knowledge at the intersection of engineering management and systems engineering. The journal’s scope spans a wide range of topics, including, but not limited to:

  • Engineering Systems Design and Integration

    Research on modelling, optimisation, and coordination of multi-component engineering systems, emphasising architecture design, interoperability, and system integration across industries.

  • Systems Thinking and Decision Analytics

    Analyses of systems approaches and analytical tools that improve decision-making, adaptability, and organisational performance in engineering environments.

  • Project, Program, and Portfolio Management

    Comprehensive studies on project governance, scheduling, budgeting, risk management, and resource allocation for large-scale and distributed engineering projects.

  • Digital Transformation and Smart Engineering Technologies

    Explorations of how digitalisation, AI, IoT, robotics, and digital twins transform engineering design, monitoring, and control within modern industries.

  • Complex Systems Modelling and Simulation

    Development of computational models, agent-based simulations, and system dynamics frameworks for predicting system behaviour and performance under uncertainty.

  • Sustainability and Life-Cycle Engineering

    Studies focusing on sustainable infrastructure, circular economy integration, environmental impact reduction, and energy-efficient system design throughout the life cycle.

  • Reliability, Quality, and Safety Engineering

    Innovative methodologies for reliability analysis, quality assurance, and risk-based design to improve the robustness and safety of engineering systems.

  • Human Factors, Ergonomics, and Leadership

    Research addressing the human dimension of systems engineering, including cognitive ergonomics, team dynamics, leadership models, and organisational resilience.

  • Industrial Systems, Logistics, and Supply Chain Optimisation

    Investigations into the optimisation of production systems, logistics networks, and supply chains through system modelling, lean principles, and intelligent control.

  • Economic and Policy Dimensions of Engineering Systems

    Studies analysing cost optimisation, financial modelling, and policy frameworks that shape the management and regulation of engineering projects.

  • Cyber-Physical and Socio-Technical Systems

    Examinations of the integration of physical systems with information technologies, emphasising security, adaptability, and human-technology interaction.

  • Education, Training, and Knowledge Management

    Innovative approaches to systems thinking education, professional competency development, and organisational learning in engineering management.

  • Case Studies and Real-World Applications

    Empirical studies demonstrating practical applications, best practices, and lessons learned from the implementation of engineering management and systems methodologies.

Articles
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Abstract

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Construction projects frequently encounter field constraints that affect cost, schedule, and quality performance. When delays arise, contractors often adopt overtime work as an acceleration strategy using the existing workforce. However, such practices may lead to concerns regarding productivity decline. This study investigates the impact of overtime work on construction labor productivity based on the Five-Minute Rating method, focusing on plastering and skim coating activities in a residential project in Palangka Raya, Indonesia. A systematic work sampling approach was employed, comprising 1,296 observations collected over six days, with comparisons made between regular working hours and overtime periods. The results indicate distinct productivity responses across work types. Plastering exhibited only a marginal reduction in Labor Utilization Rate (LUR) of approximately 1%, whereas skim coating showed a more pronounced decline of about 6.5% during overtime. Effective activities decreased by approximately 6% under overtime conditions. In contrast, volume-based analysis suggests that output increased during overtime, with gains of 28% for plastering and 49% for skim coating. Statistical analysis suggested a significant difference in productivity for skim coating (p = 0.031), while no statistically meaningful difference was observed for plastering (p = 0.109) at the 95% confidence level. Despite the observed increase in output, the achieved productivity levels remain below standard unit price analysis benchmarks.

Open Access
Research article
A Decision-Oriented Framework for Risk-Based Maintenance Planning in High-Performance Mechanical Systems Using Entropy-Integrated FMEA–MCDM Approaches
dharmpal deepak ,
sulakshna dwivedi ,
harnam singh farwaha ,
raman kumar ,
željko stević ,
manjunatha chandra ,
rajender kumar ,
anant prakash agrawal ,
vivek john
|
Available online: 04-24-2026

Abstract

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Effective maintenance planning in high-performance mechanical systems requires a structured approach to identifying and prioritizing potential failure modes under multiple, often conflicting criteria. Conventional Failure Mode and Effects Analysis (FMEA) relies heavily on subjective judgment, which can limit consistency and transparency in decision-making. To address this limitation, this study develops a decision-oriented framework that integrates Shannon entropy-based weighting with three Multi-Criteria Decision-Making (MCDM) methods, namely SAW, TOPSIS, and VIKOR. The framework is applied to a representative high-performance mechanical system, in which maintenance-related factors, including failure probability, detection capability, economic impact, repair time, and resource availability, are evaluated in a unified structure. Entropy weighting is employed to derive criterion importance directly from data, reducing reliance on expert bias. The combined use of multiple MCDM techniques enables cross-validation of ranking outcomes and improves the robustness of the prioritization process. The results show a high degree of consistency among the three methods (Spearman’s $\rho>0.80$), indicating stable identification of critical failure modes. The proposed framework provides a transparent basis for risk-informed maintenance planning and supports more effective allocation of inspection and repair resources. From an engineering management perspective, the approach facilitates the transition from experience-driven decisions to data-supported strategies, contributing to improved system reliability and operational efficiency. Although demonstrated in a specific application context, the framework can be extended to other engineering systems where structured failure prioritization is required.

Abstract

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Compliance management in business operations is often addressed through fragmented procedures that are difficult to coordinate and evaluate in a consistent manner. This study develops a structured compliance management framework grounded in a system engineering perspective, with the aim of linking regulatory requirements to operational processes in a coherent way. The framework is constructed by organizing compliance activities into a set of interrelated components, including regulatory interpretation, process integration, monitoring mechanisms, and feedback loops. On this basis, an evaluation scheme is established to examine the consistency and effectiveness of compliance implementation across operational stages. Particular attention is given to the identification of critical control points and the interaction between compliance measures and routine business processes. The proposed framework is examined through its application to typical organizational settings, where it allows a more transparent mapping between compliance requirements and operational execution. The analysis shows that a system-based structure supports clearer identification of process dependencies and facilitates more consistent evaluation outcomes. The study provides a structured basis for understanding compliance as an integrated operational system rather than a set of isolated practices, and offers a foundation for more informed decision-making in compliance management.

Abstract

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Hospital infrastructure systems represent one of the most complex categories of engineered systems, characterized by the tight integration of system configuration, technical subsystems, operational processes, and governance structures. Despite their structural durability, such systems—particularly in institutionally unstable environments—are prone to early functional and operational obsolescence, leading to performance degradation over the lifecycle. This challenge highlights the need to conceptualize hospitals not as static built assets, but as dynamic socio-technical systems requiring systematic performance-oriented management. This study develops a system-level analytical framework to examine future-proofing as an emergent outcome of interactions among institutional and contextual drivers, planning mechanisms, innovation, and design capabilities. The empirical analysis is conducted using data collected from professionals engaged in hospital infrastructure projects in Iraq. A Partial Least Squares Structural Equation Modeling (PLS-SEM) approach is employed to evaluate both direct and indirect relationships within the proposed system model. The results demonstrate that institutional and contextual drivers significantly influence planning mechanisms, which in turn act as a central structuring layer affecting both innovation and design capabilities. Innovation does not exhibit a statistically significant direct effect on long-term system adaptability, indicating that technological advancement alone is insufficient to ensure sustained performance. In contrast, design capabilities constitute the primary determinant of future-proofing, with a strong mediating effect on lifecycle system performance. The findings provide important implications for engineering management by emphasizing that long-term adaptability in hospital infrastructure systems depends on the alignment between planning structures and implementation-oriented design capabilities, rather than on innovation intensity alone.

Abstract

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Electronics and mechatronics have transformed railway vehicles into complex cyber–physical systems integrating mechanical assemblies, electrical architectures, and embedded software across multi-decade lifecycles. Maintaining configuration integrity across these domains is particularly challenging under phased retrofits, supplier substitutions, and stringent safety requirements. This paper presents a structured narrative review of Product Lifecycle Management (PLM)-enabled approaches for governing electronics and mechatronics lifecycle data in railway manufacturing. Guided by explicit research questions, the review synthesizes literature from 2010–2025 using transparent search and inclusion criteria aligned with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting principles. Drawing on systems engineering, lifecycle management, and configuration management theory, the analysis examines multi-domain BOM governance, hardware–software traceability, variant and effectivity control, digital thread continuity, and supplier collaboration. Cross-industry implementation archetypes are evaluated to clarify contextual boundary conditions and transferability limits. The findings indicate that configuration-centric governance—rather than tool integration alone—is the primary determinant of PLM effectiveness in long-lifecycle, safety-regulated environments. A structured future research agenda and explicit engineering management implications are proposed to strengthen digital continuity, fleet-level effectivity discipline, and safety-aligned lifecycle governance.

Abstract

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Assessing sustainable development performance is essential for understanding national progress. This study evaluates the sustainable development performance of G20 member countries (excluding the EU) using an integrated set of economic, social, and environmental indicators. Economic performance is captured by GDP per capita and the unemployment rate, while social performance is assessed through the education index, health expenditure, and income inequality (Gini coefficient). Environmental performance is represented by CO$_2$ emissions and the share of renewable energy in total energy consumption. Objective, data-driven weights were derived using the Criteria Importance Through Intercriteria Correlation (CRITIC) method, and countries were subsequently ranked using two multi-criteria decision-making (MCDM) approaches: Additive Ratio Assessment (ARAS) and Grey Relational Analysis (GRA). Correlation analysis (Spearman, Kendall, and Pearson) was conducted to examine the consistency and reliability of the rankings. The findings provide a comparative assessment of sustainability performance across G20 countries, highlighting relative strengths and weaknesses across economic, social, and environmental dimensions. The results offer a structured reference for decision-makers in engineering management and policy design in formulating evidence-based strategies.

Abstract

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This study proposes a fuzzy-based adaptive temperature management system for hydroponic cultivation in tropical climates. Unlike conventional fixed-setpoint controllers, the proposed Mamdani fuzzy system utilizes pH and electrical conductivity (EC) as contextual inputs to dynamically adjust temperature control strategies. The underlying hypothesis is that maintaining lower root-zone temperatures (RZTs) during suboptimal pH/EC conditions may increase dissolved oxygen availability, partially compensating for nutrient stress. The Internet of Things (IoT)-enabled system employs Long Range wireless protocol (LoRa) communication for long-range, low-power data transmission, with fuzzy inference executed at the gateway for offline resilience. A five-month field validation (April–August 2024) in Ho Chi Minh City demonstrated effective temperature regulation, maintaining solution temperature within the 18–28 °C operational target range for 88.7% of the trial period, with zero exceedance of the 35 °C critical threshold. The system maintained pH at 5.72 ± 0.32 (86.4% time in optimal range) and EC at 1.87 ± 0.28 mS/cm (81.3% time in optimal range). Retrospective simulation comparing the proposed controller against On/Off, proportional-integral (PI) baselines, and temperature-only FLC baselines, demonstrated a 15–16% reduction in chiller runtime while maintaining equivalent thermal safety. Operational crop assessment across three cultivation cycles indicated commercially viable lettuce production. A dedicated system engineering analysis addresses architecture trade-offs, reliability, scalability, and cost-effectiveness for practical deployment in tropical commercial operations.

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This study explores the macroeconomic impact of the Zero Over-Dimension Over-Load (ODOL) policy in Indonesia, especially its influence on logistics costs, inflation, and economic growth. The policy is not discussed here only as a matter of transport compliance, but also as a structural change in logistics governance that may affect the wider economy. A mixed-methods approach was used, based on primary survey data collected in 2025 from logistics stakeholders in DKI Jakarta and West Java. For the analysis, the Leontief Price Model was applied to estimate price transmission effects, while the dynamic Computable General Equilibrium (CGE) IndoTERM model was used to simulate cost shocks, investment adjustment, and fiscal reallocation. The findings show that the policy increases national logistics costs by 4.58% in the short term, which raises the logistics cost-to-GDP ratio to 14.94%. However, the longer-term results are more positive. The simulation suggests a 0.05% increase in GDP, equivalent to a net output gain of IDR 14.3 trillion. This result is associated with a 6.74% increase in fleet investment, estimated at IDR 42.4 trillion, as well as fiscal savings caused by lower infrastructure damage. These results suggest that stricter logistics regulation may bring broader economic benefits when the analysis goes beyond the immediate rise in transport costs. In practical terms, the policy should be supported by fiscal incentives for fleet modernization and by careful timing of enforcement, especially to limit inflationary pressure in food and construction-related sectors.

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Remote sensing plays a crucial role in disaster management. Moreover, its effectiveness is severely limited due to operational, technological and environmental challenges. Data acquisition can be disrupted by sensor limitations and by extreme events or natural factors, such as cloud cover. In fact, high-resolution imagery often requires significant processing time, specialized expertise and expensive infrastructure. Therefore, ensuring timely, accurate and accessible remote sensing data at all stages—preparedness, response, recovery and mitigation—is a major challenge. This study explores the application of multi-criteria decision making (MCDM) techniques using bipolar fuzzy numbers (BFNs) to evaluate this. We apply the weighted and ranking MCDM method, i.e., Method Based on the Removal Effects of Criteria (MEREC) and Multi-Attributive Border Approximation Area Comparison (MABAC), respectively, in this paper. The decisions of multiple decision makers (DMs) are considered when collecting this problem related data and BFNs are utilised as mathematical tools to handle uncertainty. In order to address the ambiguity and inconsistency of the system, we finally conclude to conduct the comparative and sensitivity analyses here with the final result.
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