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        <title>Production Engineering Archives Feed</title>
        <link>https://sciendo.com/journal/PEA</link>
        <description>Sciendo RSS Feed for Production Engineering Archives</description>
        <lastBuildDate>Sun, 10 May 2026 14:05:15 GMT</lastBuildDate>
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            <title>Production Engineering Archives Feed</title>
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            <link>https://sciendo.com/journal/PEA</link>
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        <copyright>All rights reserved 2026, Quality and Production Managers Association</copyright>
        <item>
            <title><![CDATA[Structural performance of repaired reinforced concrete beams with damaged compression zones: an experimental study using digital image correlation]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.22</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.22</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

This study investigates the repair effectiveness of reinforced concrete (RC) beams with crushed compression zones and reduced tensile reinforcement. The aim was to evaluate the restoration of load-bearing capacity and flexural performance after repair using polymer-modified mortar. The experimental program included four-point bending tests, high-precision displacement monitoring, and digital image correlation (DIC). Experimental results were compared with predictions obtained from a nonlinear sectional deformation model and with reference beams having reduced reinforcement but no damaged compression zone. The repaired beams reached a reinforcement yield moment of 8.62-8.97 kNm and an ultimate bending moment of 9.5 kNm. The strain in the repaired compression zone remained below the ultimate strain capacity of the repair mortar, indicating stable composite action between the original concrete and the repair material. The repair method increased the reinforcement yield moment by approximately 35%, confirming effective restoration of the compression zone and improved structural performance. The results demonstrate the usefulness of DIC for assessing repaired RC beams and support the application of polymer-modified repair systems for beams with damaged compression zones.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[An Efficient Tree Search Algorithm for Solving Robotic Assembly Line Balancing Problems]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.26</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.26</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Traditional assembly line balancing problems (ALBP) aim to assign tasks to stations to meet specific production targets, but in practice, the problems can be extremely complex because of the additional factors, such as robot or automated equipment alternatives. The robotic assembly line problem is a broad and challenging variant of traditional lines. Designing and balancing robotic assembly lines are crucial in manufacturing to optimize productivity, efficiency, and flexibility. In this study, we propose a heuristic algorithm that provides practical and effective solutions for robotic assembly line balancing problems (RALB). We aim to assign robot and task combinations to workstations simultaneously with the objective of minimizing the system cost, including the cost of installing new robots and opening new workstations. We evaluate the algorithm’s performance on a large set of random problem instances by using statistical methods. We conclude that feasible and good solutions can be found easily, even for large-scale problems, in short processing times.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Household Solid Waste Eco-Efficiency in Slovak NUTS-3 Regions: A Two-Stage DEA Analysis]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.23</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.23</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

The study assesses the waste-related eco-efficiency across Slovakia’s eight regions at the NUTS-3 level. The study examines time trends and efficiency changes between 2018 and 2023. The Data Envelopment Analysis method is used to measure efficiency, specifically a model assuming variable returns to scale. Three specific models were created for different types of household solid waste. These efficiencies are then bias-corrected using a double-bootstrap approach and subjected to a closer analysis of the effects of selected environmental variables, including population density, median age, and the age dependency index. The results indicated a negative impact of a higher share of the economically inactive population on the efficiency of generating all types of household solid waste. In terms of population density, the effects differed, with statistical significance less pronounced. Median age, i.e., the population’s maturity, positively impacted household solid waste generation efficiency. The paper’s conclusions include recommendations for policies focused on regional disparities, age management, and support for the education of selected population groups. The results of this study can also help identify factors for training AI models for predictive waste management.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Using simulation modelling to support decision-making in warehouse internal logistics]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.14</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.14</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Manufacturing and logistics companies increasingly rely on warehouse automation and data-driven planning; however practical tools for evaluating how structural decisions influence outbound performance remain limited. This paper addresses this gap by developing a discrete-event simulation model of a warehouse system in which forklifts execute pallet transport tasks according to predefined shipment schedules. The model integrates real inventory data, structured storage addressing (alley-bay-level-slot), forklift routing logic and dock-capacity constraints within a unified ProcessFlow architecture. The experimental study focuses on assessing the impact of dock capacity on outbound operational performance. Three scenarios with varying numbers of docks were analysed while maintaining constant order structure, inventory distribution and transport logic. The evaluation is based on two key performance indicators: forklift utilization and average dock occupancy level. Statistical analysis was conducted using multiple replications and 95% confidence intervals to verify the significance of observed differences. The findings confirm that discrete-event simulation provides a robust decision-support tool for analysing structural modifications in warehouse systems and supports data-driven configuration of outbound logistics processes within Industry 4.0 environments.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[A Digital Sustainability Maturity Framework for Assessing Industry 4.0 and ESG Integration]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.21</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.21</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

The growing convergence of digital transformation and sustainability requirements necessitates the development of integrated analytical frameworks that enable the simultaneous assessment of an organization’s technological maturity and its ESG maturity. Existing Industry 4.0 maturity models predominantly focus on technological aspects, while ESG frameworks emphasize reporting and regulatory compliance, often overlooking the organizational and technological conditions required to achieve higher levels of maturity. Although prior research provides growing evidence on the relationships between digital transformation and sustainability, it still lacks integrated frameworks that systematically combine technological maturity, organizational capabilities, ESG maturity, and sustainability performance outcomes within a single analytical structure. The aim of this article is to address this gap by proposing the Digital Sustainability Maturity Framework (DSMF), an integrated maturity model that combines Industry 4.0 maturity, digital enablement factors, ESG maturity, and sustainability performance outcomes within a coherent cause-and-effect structure. The model is based on hypothesized relationships that digital maturity influences the development of ESG maturity both directly and indirectly through organizational capabilities related to data management, digital competencies, and process integration. This article is conceptual and methodological in nature and proposes a theoretically grounded framework for future empirical validation. It develops a theoretical framework and proposes a structured measurement instrument intended for future empirical validation. Based on a literature review, the structure of the model and a set of research hypotheses describing the relationships between its key dimensions were developed. The DSMF model was subsequently operationalized in the form of a survey instrument designed to assess an organization’s maturity level across four model dimensions. Conceptual validation and instrument development of the model was conducted, and a procedure for its empirical verification using Partial Least Squares Structural Equation Modeling (PLSSEM) was outlined. The proposed model contributes to the literature by integrating the perspectives of digital transformation and sustainability within a single maturity framework, treating ESG maturity as a data-driven organizational capability supported by Industry 4.0 technologies. From a practical perspective, the DSMF is proposed as a potential diagnostic tool that may support managers in assessing the alignment between digitalization and ESG performance and in identifying areas requiring further development, subject to future empirical validation.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Exploring the linkage between digital transformation, green innovation, and carbon neutrality: Implications for business sustainability]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.15</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.15</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Achieving business sustainability progressively depends on alignment of digital transformation, green innovation and carbon neutrality initiatives. This study aims to identify and prioritize the key factors to achieve green innovation and carbon neutrality. Based on the Technology–Organization–Environment (TOE) framework, the Grey Ordinal Priority Approach (G-OPA) is applied to evaluate the relative importance of factors under uncertainty using insights from 14 industry experts. The results highlight 16 critical factors, with “Digital orientation”, “Innovation capability” and “Optimizing energy consumption structure” as three most influential factors that businesses must address to effectively integrate digital transformation strategies with sustainability initiatives. The study contributes a structured understanding of how digital transformation drives sustainability and provides practical guidance for managers and policymakers pursuing carbon-neutral strategies.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Renewable energy transition in Poland: scenario-based analysis of solar and wind integration in the power system]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.20</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.20</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

This article examines the current status and development prospects of renewable energy sources (RES) in Poland in the context of the national energy transition and European climate objectives. The study addresses three research questions concerning the role of RES in Poland’s energy mix, their development potential, and the main opportunities and barriers to increasing their share. The research combines a literature and data review with scenario-based simulations using the Polish Power System Simulator, based on real weather data from 2015–2023 and electricity demand from 2023. Four scenarios were analysed: the current state, PV-based, wind-based, and combined PV + wind. The results show that RES already play a significant role in Poland’s energy sector. In 2023, their share reached 27%, with total installed capacity of 28.6 GW, increasing to 33.3 GW in 2024, dominated by photo-voltaics and wind. Despite this growth, coal still accounted for 60.5% of electricity generation in 2023, indicating continued dependence on conventional sources. The analysis identifies solar and wind energy as the main drivers of future RES development. However, further expansion is limited by grid constraints, connection refusals, curtailment, regulatory barriers (including the 700 m rule for wind farms), and insufficient storage and flexibility resources. Simulation results indicate that the combined PV + wind scenario provides the most balanced and resilient system configuration due to complementary generation profiles. Nevertheless, dispatchable backup capacity remains necessary. Achieving a higher RES share is technically feasible but requires diversification, grid modernisation, expanded storage, and stable regulatory conditions.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[The Evolution of Quality Management Towards Quality 5.0: A Maturity Model Perspective]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.18</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.18</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Six main stages can be distinguished in the evolution of quality management concepts. Initially, attention focused on quality inspection and quality control, aimed at detecting errors and nonconformities in finished products. The next stage was quality assurance, which introduced preventive actions designed to eliminate defects during production processes. A major breakthrough occurred with the development of Total Quality Management (TQM), which expanded quality management to the entire organization and emphasized continuous improvement, employee involvement and customer orientation. More recently, the concept of Quality 4.0 has emerged, driven by digitalization, automation and the application of advanced technologies in quality management systems. The latest stage, Quality 5.0, integrates technological innovation with human-centric values such as ethics, sustainability and social responsibility. The aim of this study is to analyse the evolution of quality management concepts and to identify the relationships between successive approaches. The study is based on a structured literature review of scientific publications related to quality management development. As a result of the analysis, an Integrated Evolutionary Quality Management Model (IEQMM) is proposed, which conceptually links traditional quality management practices with digital transformation and human-centred sustainability principles. The findings highlight the complementary nature of successive quality paradigms and emphasize the importance of integrating technological capabilities with social and sustainability-oriented perspectives in modern quality management.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Methods for Assembly line balancing and worker allocation problem: an Overview]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.16</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.16</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

This paper presents a comprehensive tertiary-level review of solution methods for Assembly Line Balancing Problems (ALBP) and Worker Allocation Problems (WAP), synthesizing insights from 25 literature reviews published between 2006 and 2024. Unlike prior reviews, this study critically evaluates methodological trends, practical relevance, and the alignment between academic proposals and industrial implementation. Metaheuristic approaches, especially Genetic Algorithms, dominate literature, yet their adoption in real-world settings remains limited. The review also highlights the emergence of hybrid and AI-enhanced strategies, the growing attention to explainability and adaptability, and the methodological shortcomings of existing reviews regarding transparency and contextual analysis. This work contributes a structured taxonomy of methods, assesses their suitability across problem dimensions, and identifies future directions emphasizing industry integration, real-time responsiveness, and robust evaluation frameworks.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[A unified MILP framework for integrated serial-parallel production batching and inter-factory delivery in multi-factory environments]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.17</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.17</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

This study addresses the integrated serial–parallel production batching and inter-factory delivery scheduling problem in multi-factory environments – an operational configuration that has been largely overlooked in existing research. The challenge arises because upstream serial batching, downstream parallel batching, and inter-factory delivery batching are strongly interdependent, yet prior studies model them separately. To fill this gap, a unified mixed-integer linear programming (MILP) formulation is developed to jointly determine batch formation, batch sequencing, and inter-factory release timing. The model internalizes production–delivery trade-offs and captures all major cost components, including tardiness, holding, transportation, and production. Using Gurobi, 27 OFAT-designed instances are solved to proven optimality, with solution times ranging from 427 seconds (median) to 30.8 hours for the largest cases. Sensitivity analysis reveals that unit production cost is the primary driver of total cost, while tardiness penalties have the strongest impact on batch allocation behaviour. Delivery fees moderately affect outsourcing decisions, while holding costs have a negligible impact on operations. The results provide actionable managerial insights by identifying when inter-factory delivery batching becomes economically advantageous and how batch-formation rules shape downstream workload synchronization. Overall, this study provides a unified analytical framework that explicitly links batch-based production decisions across stages with inter-factory delivery timing and shipment frequency in a multi-factory environment.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Causes of automotive recalls and classification of product and process failures: evidence from Brazil, the European Union and the United States]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.25</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.25</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

There is growing international concern regarding product quality failures that compromise public safety, as evidenced by the increasing number of automotive recalls and the scale of affected vehicles. This study examines the phenomenon, evaluates potential responses and analyses regulatory frameworks in Brazil (BR), the European Union (EU) and the United States of America (USA). Where data were not readily available, they were obtained from official databases and via web-scraping, enabling the analysis and classification of 12,466 automotive recalls for the period 2011 to 2019. The results indicate that recall effectiveness is shaped by region-specific policy priorities and systemic factors. For Brazil, it is recommended that regulatory agencies be strengthened, nationwide periodic inspections be implemented, and advanced safety technologies be incentivised. For the United States of America, it is recommended that litigation-driven incentives be balanced, predictive analytics be expanded, and supply-chain oversight be reinforced. For the European Union, it is recommended that data reporting be harmonised, certification protocols for embedded software be developed, and cross-border enforcement mechanisms be strengthened. Across jurisdictions, the exchange of best practices is likely to improve product quality, reduce warranty costs, and mitigate risks to public safety. The findings indicate the absence of global standardisation in recall data, the greater severity of product recalls relative to process recalls, and the urgent need for coordinated strategies to reduce systemic failures. This research represents a comprehensive effort to classify and compare recall data from over 428,754,988 vehicles by cause, distinguishing between product and process recalls. Finally, the validation of web-scraping as a methodological tool demonstrates its potential applicability for future studies across diverse fields.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Root Cause Assessment of Welded Satellite Gear Carrier Failure in a Bucket Wheel Excavator]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.19</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.19</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

In this study was investigated the fracture of the welded supporting structure of a satellite carrier of a bucket wheel excavator drive reducer. The research was aimed at identifying the root causes of the failure through an integrated failure analysis combining theoretical calculations, numerical modelling and experimental investigations. The loading analysis included digging resistance, natural and forced oscillations of the excavator structure, and verification of the support strength under variable operating conditions. Finite element analysis was used to determine the stress state in the critical regions of the carrier, while the field measurements were performed to assess operational stresses and vibration behavior under different excavation regimes. In addition, metallographic and scanning electron microscopy examinations were carried out to identify the fracture features and weld imperfections. The results showed that the critical sections of the support structure operated under stresses close to the yield limit, while impact loads and low-frequency oscillations significantly increased the risk of failure. Fractographic observations revealed lamellar tearing, low-cycle fatigue features and a heterogeneous weld structure containing cracks, inclusions and gas porosity. The fracture was therefore caused by the combined effect of excessive service loads, dynamic excitation, stress concentration and imperfections in welded joints, which should be more comprehensively considered in the design and assessment of such structures.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Operation-oriented numerical analysis of dynamic loads occurring in drive units of armoured face conveyors with an innovative highly flexible coupling]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.24</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.24</guid>
            <pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

For many years, the hard coal mining industry has been searching for engineering solutions ensuring greater reliability of the machines operating in difficult underground conditions. The foregoing applies in particular to the scraper conveyors used in longwall systems, started up very frequently and exposed to variable dynamic loads, leading to accelerated wear of powertrain components. The authors of this study have developed a longwall scraper conveyor equipped with a torsionally flexible metal clutch of novel design. The article provides a description of a mathematical model of a conveyor featuring two centrally arranged chains along with a main (discharge) and auxiliary (return) drive, as well as results of the computer simulations performed for two variants of the drive system setup analysed: one with a typical flexible clutch and the other with the innovative torsionally flexible clutch. Analysis of these results has revealed that the solution proposed significantly reduces the amplitude of dynamic loads, which contributes to increased durability and reliability of conveyors under mining conditions.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Utilization of municipal solid waste incineration bottom ash and cement kiln bypass dust in modified cement mortars]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.6</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.6</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

The study evaluated the feasibility of using two industrial by-products: municipal solid waste incineration bottom ash (MSWI-BA) and cement kiln bypass dust (CBPD), as partial replacements of conventional constituents in cement mortars. MSWI-BA was used as a replacement for standard sand (5, 10, 15, and 20%, introducing a volumetric adjustment to the weight of the norm sand), while CBPD was used as a replacement for cement (2.5 and 5.0%); both materials were introduced either individually or in combination. The flow of fresh mortars, water absorption and dry bulk density, flexural and compressive strengths at 7 and 28 days, and resistance to freeze - thaw cycling (25 cycles) were investigated. The incorporation of the by-products reduced consistency (from 2.2 to 30.6%) and increased water absorption by 11.1 - 18.5% relative to the reference mix. All modified series showed lower mechanical strength than the reference mortar; among the mixes incorporating a single by-product, the highest 28-day compressive strength was obtained for 5% MSWI-BA (≈44 MPa), whereas the combined mix MIX 5/2.5 reached 37.1 MPa. After freeze - thaw cycling, the modified mortars exhibited lower mass loss (0.07 - 0.36%) than the reference series (0.82%). The results suggest that incorporating MSWI-BA and CBPD at low substitution levels can be a practical step towards more sustainable, circular-economy-oriented mortar production, combining reduced landfilling of waste materials with a lower demand for virgin raw materials.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Comparison of deep feature extraction for quality prediction in injection molding]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.8</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.8</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

In the context of Industry 4.0, multi-sensor data plays a pivotal role in monitoring, analyzing, and optimizing product quality in real time. The ability to capture and process data from various sensors allows manufacturers to identify deviations, detect anomalies, and improve overall production efficiency. However, raw data collected during the injection molding process often contains redundant, irrelevant, or highly correlated features that can introduce noise and reduce the efficiency of predictive models. Without proper preprocessing, such data can lead to increased computational complexity and diminished model performance. To address these challenges, effective feature extraction techniques are essential for refining the dataset, minimizing prediction errors, and enhancing the interpretability of machine learning models. In this study, we compare two widely used feature extraction methods: Principal Component Analysis (PCA) and an Autoencoder (AE). The primary objective of this research is to assess the effectiveness of these feature extraction methods in monitoring the injection molding process and predicting product quality on an advanced machine learning model LSSVM. The experimental results presented in this study are useful in determining the suitability and disadvantages of each method, with the prediction accuracy of up to 99.62% for the extracted deep feature.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[A simulation model for optimizing component placement in an assembly process]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.3</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.3</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

This article presents a simulation-based approach to optimizing the placement of components and semi-finished products within an assembly area of a production hall. The developed model focuses on minimizing the total distance traveled by internal transport vehicles – such as AGVs – during the execution of production tasks. A key constraint of the model is the fixed layout of transport routes, which reflects common spatial limitations in real production systems. Therefore, the optimization is limited to the allocation of components in relation to the assembly stations. The simulation model was developed using the FlexSim environment and has a design-oriented character, utilizing hypothetical data. This enables flexible testing of multiple layout scenarios without relying on real-world operational inputs. The proposed approach offers a practical tool for supporting layout planning and internal logistics design in the early phases of manufacturing system development. Additionally, it facilitates comparative analysis of alternative material handling strategies under varying transport capacities and system configurations.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[The Integration of RFID and Blockchain Technology for the Supply Chain Traceability of Durians]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.13</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.13</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Traceability is an essential practice to ensure transparency, authenticity, and regulatory compliance in modern agricultural supply chains, especially high-value agricultural products. Regarded as the king of fruits in Southeast Asia for its unique taste, texture, and aroma, durian dominates the market of exported fruit commodities. However, recurring issues such as fraudulent GAP numbers, mislabelled origins, premature harvesting, and product tampering undermine consumer trust and export credibility. To address these challenges, this study presents an integrated traceability architecture combining RFID, a MySQL database, an automated Node.js backend, and Ethereum-compatible smart contracts. The developed system enables automated ingestion of physical RFID data, secure on-chain recording via immutable ledger functions, and optional generation of ERC-721 NFTs as digital certificates. Empirical validation includes RFID read-rate testing, blockchain performance measurement, and gas usage analysis. Carton-level tagging, wherein a single RFID tag is attached to a carton rather than each individual fruit, significantly reduces per-durian blockchain cost. The results demonstrate that the proposed architecture is technically robust, flexible, economically scalable, and suitable for SME use in high-value or ultra-premium fresh-produce chains.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Value Stream Mapping: some Pragmatic Aspects]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.10</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.10</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Value Stream Mapping (VSM) is a widely used industrial tool to represent material and information flows, helping to identify improvement opportunities and define the desired future state. However, its construction often raises difficulties that can lead to mapping errors. This paper draws on the authors’ experience of more than three decades, in academic and industrial contexts, to systematise recurrent misunderstandings observed in VSM construction. The study focuses on six problem areas: (1) distinctions between value-added time, processing time, and cycle time; (2) process lead time and inventory lead time; (3) inventory quantification; (4) representation of multiple material flows; (5) treatment of shared processes; and (6) system balancing and bottleneck identification. Several of these issues are absent from the literature, while others, although mentioned, continue to be misapplied. For each, the paper provides clarification and/or a corrective approach, thereby contributing to a more rigorous and consistent use of VSM.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Exploring Lean Manufacturing Integration and Performance Evaluation for Process Optimization in the Food Processing Industry]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.7</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.7</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

Lean manufacturing has proven effective across many industries, yet its application in food processing remains constrained by product perishability and process variability. This study develops a hybrid Lean–Simulation framework that integrates Gemba walks, check sheets, Pareto analysis, Fishbone diagrams, and Value Stream Mapping (VSM) with Monte Carlo simulation to capture both deterministic inefficiencies and stochastic variability. Results show an average processing time of 354.98 minutes, with the 95th percentile at 378.96 minutes, confirming that Thawing and Packing are the dominant bottlenecks. By incorporating probabilistic analysis, the framework extends beyond conventional Lean tools and provides managers with actionable insights to enhance stability, allocate resources strategically, and improve responsiveness in food processing operations.
]]></description>
            <category>ARTICLE</category>
        </item>
        <item>
            <title><![CDATA[Study of the operating process of a salt premix component mixer with a combined working unit and the influence of mixing degree on product quality]]></title>
            <link>https://sciendo.com/article/10.30657/pea.2026.32.1</link>
            <guid>https://sciendo.com/article/10.30657/pea.2026.32.1</guid>
            <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[

This article examines the effect of the mixing degree of feed mixture components on its homogeneity, mixing quality, and the uniform distribution of microcomponents and vitamins within the volume of the mixture. Additionally, the study evaluates the suitability of the mixture for the molding and pressing processes involved in the production of salt lick bricks (SLB). The research is conducted using a novel energy-efficient combined mixer. The study presents an analysis of the impact of mixing intensity on the quality of SLB under prolonged storage in various environmental conditions. The kinetics of the mixing process for salt premix components is investigated. A mechanical-mathematical model describing the mixing behavior of components in a combined mixer is developed. Based on experimental data, correlations are established between the physical characteristics of the final salt lick premixes – including shape, composition, and hardness – and the homogeneity of the initial mixture. Furthermore, the study assesses the stability of SLB premixes under adverse environmental conditions, including exposure to humidity and temperature fluctuations. A methodology for determining the optimal rotor rotation frequency in the combined mixer is developed, and its influence on mixture homogeneity is quantified.
The findings of experimental studies on a prototype combined mixer confirm the theoretical predictions. The results substantiate the efficiency and feasibility of thorough and intensive mixing of components in SLB production, which contributes to a reduction in material consumption for manufacturing equipment and a decrease in overall energy costs.
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            <category>ARTICLE</category>
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