Search Results (268)

Insulation-material manufacturers face increasing pressure to improve productivity, cost efficiency, energy performance and worker safety while maintaining stable quality in highly constrained production environments. Existing lean and smart-manufacturing studies often examine isolated tools, individual monitoring technologies or material-level sustainability, but fewer studies provide conservative plant-level validation of an integrated intervention in insulation-material production. This study therefore examines the optimization of insulation-material production in a human-supervised cyber–physical manufacturing system through an industrial before–after intervention. The framework combines bottleneck identification, value stream mapping, SMED, selective automation, preventive maintenance and KPI-based digital monitoring. The baseline system was constrained by manual crusher loading, long changeovers, inefficient pallet transport, repeated breakdowns, scrap and limited real-time visibility. After implementation, productivity increased from 7864 to 9000 kg/day (+14.5%), monthly production costs decreased from EUR 200,000 to EUR 180,000 (−10%), breakdown frequency fell from 5 to 3 events/month (−40%), scrap decreased from 5% to 3% (−40%), crusher loading time fell from 30 to 10 min/pallet (−66%), annual energy use dropped from 500 to 450 MWh (−10%) and reported safety incidents decreased to zero during the 12-month post-implementation observation period. An OEE-based surrogate model yielded pre- and post-state theoretical capacity estimates differing by less than 1%, supporting internal consistency. The results are interpreted as descriptive and practically meaningful before–after differences because the full raw monthly dataset is commercially sensitive and classical inferential testing was not performed. The study contributes by presenting a reproducible, conservative and human-supervised CPS-oriented plant-intervention protocol rather than by claiming a fully autonomous closed-loop CPS. Full article

Rapid urbanization in Saudi Arabia puts increasing pressure on energy, water, mobility, and waste-management systems, strengthening the need for evidence-based smart-city policy under Vision 2030. Rather than offering a descriptive inventory of projects, this paper develops a verification-oriented framework for assessing smart-city initiatives in the Kingdom. The framework is built on four principles: (i) distinguishing national contextual indicators from city-level evidence, (ii) separating stated ambitions from observed outcomes, (iii) applying an evidence-grading rubric that prioritizes publicly verifiable mechanisms and performance indicators over anecdotal or promotional claims, and (iv) introducing a readiness–impact matrix adapted to Saudi climatic, infrastructural, and institutional conditions. The framework is applied to major Saudi smart-city cases, including NEOM, KAEC, Riyadh, Jeddah, Makkah, and Madinah. The analysis shows that the strongest publicly documented evidence is concentrated in selected sectoral applications, particularly demand response and smart-building control in electricity systems, leak detection and pressure management in water networks, and intelligent traffic management in urban transport. These cases indicate plausible pathways for improving service efficiency and reducing resource waste; however, publicly verifiable city-level outcome data remain limited, fragmented, and uneven across cases. In response, the paper proposes a policy playbook centered on KPI transparency, interoperable data governance, cybersecurity safeguards, and public–private partnership templates to improve the measurability, comparability, and scalability of smart-city outcomes. By formalizing verification and cross-case assessment, the study contributes a reproducible methodological basis for evaluating smart-city progress and prioritizing future investments in Saudi Arabia. Full article

This paper analyses seven project deliverables from the Interreg Euro-MED “MAST” project to examine its sustainability protocol as a sociotechnical boundary object facilitating ISO 21401:2018 adoption among Mediterranean tourism SMEs. Using Science and Technology Studies (STS) and boundary object theory, we conducted qualitative content analysis (QCA) to map how the protocol translates global standards into SME roadmaps addressing implementation costs, skill gaps, and legitimacy barriers. Results reveal a tension between managerial scripting (actionable tables and KPIs) and relational openings (peer learning and stakeholder prompts). While enabling SME access to certification, the protocol risks “smart compliance” by prioritising formal verification over substantive transformation. Universities emerge as key boundary brokers, potentially translating technical standards into entrepreneurial competencies and curricula. Limited to pre-implementation project documents, the analysis identifies discursive conditions under which standardised tools could support regenerative governance. Findings suggest university–SME partnerships as promising mechanisms for aligning certification with Mediterranean socio-ecological priorities, warranting empirical testing through SME implementation studies. Full article

Intelligent manufacturing requires strategic performance indicators that link shop-floor performance with productivity and sustainability goals. This study examines Overall Equipment Effectiveness (OEE) as a strategic key performance indicator and applies it to a hydraulic plastic injection-moulding machine producing an automotive component. Production data captured through a PLC-and-SQL-integrated digital monitoring system over 14 months were used to calculate monthly Availability, Performance, Quality, and OEE values and to identify the main sources of efficiency loss. The baseline period showed low OEE, driven mainly by unplanned downtime, minor stoppages, and cycle times above the 45 s target, whereas Quality remained consistently close to 100%. A diagnostic analysis combining production logs, downtime stratification, cycle-time records, and consultations with plant personnel was then used to define improvement actions. The implemented measures included preventive and predictive maintenance, process-parameter optimisation, operator training, and wider use of digital monitoring and analytics. In the post-improvement period, OEE increased markedly, downtime decreased, and cycle-time stability improved, reaching values close to world-class performance. The results confirm that OEE can function as a unifying KPI for intelligent manufacturing, supporting data-driven decision-making, continuous improvement, and more sustainable production. Full article

Despite the growing importance of Environmental, Social, and Governance (ESG) performance in shaping brand perception and consumer trust, limited empirical evidence exists on how ESG indicators translate into measurable digital consumer engagement outcomes, particularly in ethically driven markets such as the vegan food sector. This study addresses this gap by examining how ESG performance translates into digitally observable consumer engagement and frames this relationship as a strategic performance measurement and decision-support problem. Building on the sector’s reliance on ethical positioning, trust, and online visibility, we integrate ESG indicators with digital marketing and web analytics metrics (e.g., traffic and engagement proxies) for a panel of five leading vegan food firms [Nestlé SA (Vevey, Switzerland), Kellanova (Chicago, IL, USA), Beyond Meat Inc. (El Segundo, CA, USA), Danone SA (Paris, France), and Conagra Brands Inc. (Chicago, IL, USA)], using data from the Semrush web analytics platform and the Eikon Refinitiv ESG database for the period January–December 2024. We employ a mixed-method design combining descriptive analytics with correlation analysis and simple linear regression to estimate the direction and strength of ESG–digital performance links, and we extend inference through Fuzzy Cognitive Mapping (FCM) using the MentalModeler platform to simulate “what-if” scenarios that support managerial foresight under digital uncertainty. Results indicate that stronger ESG profiles are associated with more favorable digital outcomes, with specific ESG mechanisms (e.g., human-capital and environmental initiatives) aligning with deeper engagement signals. The FCM scenarios further suggest that coordinated ESG improvements can amplify digital traction and reinforce sustainable brand growth. The proposed framework contributes to strategic management by operationalizing an ESG-enabled digital performance measurement system and a lightweight Decision Support System (DSS) that can guide resource allocation, KPI monitoring, and risk-aware positioning in sustainability-oriented markets. Full article

Artificial lighting accounts for roughly 30% of total electricity use in supermarkets and significantly affects product perception, customer experience, and purchasing behavior. Increasing the availability of natural light, combined with appropriate architectural energy retrofitting strategies, offers a major opportunity to reduce electricity demand. This study proposes a data-driven framework for evaluating energy retrofit strategies in commercial buildings, integrating Building Information Modeling (BIM) and Building Energy Modeling (BEM). A parametric methodology is used to evaluate multiple architectural retrofitting scenarios aimed at enhancing daylighting and reducing artificial lighting demand, while improving energy efficiency and environmental performance. The scenarios investigated include variations in skylight geometry and orientation, glazing type, photovoltaic integration, and advanced lighting controls. Three Key Performance Indicators (KPIs)—real energy effectiveness, lighting control performance, and environmental impact—are used to assess how design modifications influence energy use, indoor lighting quality, and environmental performance. The methodology is applied to three real food-retail buildings in Italy. Results show that lighting energy consumption can be reduced by up to 60% in scenarios combining LED technology with smart control systems, while total building electricity savings vary across case studies depending on building characteristics and usage patterns. Environmental impact reductions of approximately 15–20% are achieved, reflecting both operational and life-cycle improvements. The study demonstrates the potential of parametric architectural retrofitting to support multi-criteria decision-making for sustainable refurbishment of food-retail environments. Full article

This paper proposes a human-centric digital twin (DT) framework balancing energy efficiency with occupant well-being in existing buildings, addressing the lack of actionable insights in data-driven facility management and comfort issues common in fully automated systems. A “Human-in-the-loop” approach using dual-KPIs integrates real-time IoT data and visualization to evaluate sustainable energy use via Indoor Environmental Quality (IEQ). A novel occupancy-inference method tracks efficiency in legacy buildings without granular metering, implemented through a case study of 26 office rooms. Results indicate that the framework successfully identifies significant energy wastage and comfort anomalies without compromising well-being. Integrating real-time analytics with human oversight enables more resilient management than fully automated alternatives, particularly for detecting non-operational heating waste. The occupancy inference method was validated against ground truth, achieving 81% accuracy, with limitations regarding decay lag discussed. This research offers a cost-effective diagnostic tool for legacy buildings lacking sub-metering, lowering DT adoption barriers, and shifting maintenance from reactive to data-driven strategies. The framework leverages human expertise and infers occupancy-normalized energy metrics from standard IEQ sensors, proposing a human-centric DT framework to bridge the gap between raw sensor data and actionable facility management insights. Full article

The aggregation of flexible resources contributes to sustainability because it impacts on CO₂ emissions, enables renewable energy integration, improves network efficiency and makes the electric power system more resilient. The research project DEMAND has tested the potential of bottom-up aggregation of smart prosumers with no intermediation by a third-party balancing service provider. The present work analyzes the electrical and environmental effects of this new type of aggregation in different scenarios, taking into account both simulated data and data obtained from four pilot sites where the DEMAND system has been implemented. The effectiveness of the proposed aggregation method is evaluated through the calculation of some KPIs: power peaks, grid losses, voltage drops and CO₂ emissions. Full article

The increasing demand for energy, rising electricity costs, and the growing need to reduce carbon emissions have driven industries toward the adoption of Renewable Energy Sources (RES) and Energy Storage Systems (ESS). However, selecting the most suitable ESS for industrial peak-shaving applications remains a complex decision involving technical, economic, and operational considerations. This paper proposes a practical and structured methodology for ESS selection that integrates conventional performance criteria with Industry 5.0 (I5.0) requirements, emphasizing sustainability, resilience, and human-centric industrial operation. Unlike existing multi-criteria decision-making approaches, the proposed framework reduces reliance on expert-based weighting, improving transparency and reproducibility. The methodology is implemented in two stages: initial KPI-based shortlisting of technologies, followed by detailed comparative performance analysis. A case study conducted in a European tire manufacturing plant compares lithium-ion batteries and flywheel energy storage systems under different peak-shaving strategies. Lithium-ion batteries demonstrated superior performance, covering approximately 80% of demand peaks compared with the 73% achieved by the flywheel system, confirming the effectiveness of the proposed methodology for practical industrial ESS selection. Full article

Advancing environmental monitoring through coordinated autonomous systems is central to sustainable smart region governance and data-driven territorial management. The article presents an engineering-oriented architecture and deployment methodology for an integrated wildfire monitoring and response system that combines unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and stationary sensor networks (SNs). We formalise hub-and-spoke infrastructure placement as a mixed-integer optimisation problem that accounts for platform types, endurance, travel times and logistical constraints, and propose a practical pre-processing pipeline (confidence scoring, resampling, Kalman/median filtering, strategy fusion) for heterogeneous telemetry and imagery. The system couples multimodal neural network processing (image backbones, clustering and time-series models) with online resource-allocation and mission-planning mechanisms to prioritise UAV/UGV sorties and dynamically select launch sites. The article describes scenario-driven operational modes (early warning, alarm verification, autonomous local extinguishing, post-fire recovery, sensor-gap compensation, and inter-hub reinforcement), defines validation protocols (synthetic experiments, precision/recall/F1, and hardware-in-the-loop testing), and proposes KPIs to assess environmental, social, and economic impacts for smart regions. The contribution is a reproducible, deployment-focused blueprint that bridges conceptual UAV–UGV–SN research and practical implementation, highlighting trade-offs in reliability, communication redundancy, and sustainability, and outlining directions for simulation, field pilots and algorithmic refinement. Full article

Urban areas are increasingly exposed to water-related challenges, including flood risk and water scarcity, amplified by climate change, population growth, and extensive soil sealing. Addressing these pressures requires integrated stormwater management (SWM) strategies that balance hydraulic, environmental, and social objectives. This study introduces a novel, replicable Key Performance Indicator (KPI)-based assessment framework for 36 green–blue and grey sustainable stormwater management systems (SWMSs), designed to enable cross-typology, multiscale comparison. Six KPIs, encompassing flood regulation, water consumption, water quality, air quality, environmental amenity, and biodiversity potential, are derived through a critical synthesis and harmonisation of the literature and complemented with new parameters and sub-parameters to address existing methodological gaps. The framework structures evaluations into six analytical tables and one summary table, ensuring transparent, systematic, and comparative assessment of heterogeneous solutions. Application to a pilot project in Rome demonstrates how integrating KPI evaluation with parametric hydraulic modelling provides actionable insights for solution selection. It also facilitates identification of potential synergies between performance dimensions, enhancing its value as a decision-support tool in preliminary design. Overall, the study demonstrates the research value of multi-scalar, performance-based approaches for urban water planning, highlights the transferability of resilient stormwater strategies in climate-sensitive contexts, and identifies promising avenues for future research, including multi-sectoral integration, trade-off analysis, and cross-platform application. Full article

This study presents a comparative analysis of five gender equality certification schemes alongside the ISO 53800 standard with the aim of distilling shared conceptual foundations and design principles that can inform progress toward Sustainable Development Goal (SDG) 5 on gender equality. The comparative analysis reveals marked heterogeneity in scope, design architecture, indicators, and transparency. Methodologically, the study draws on the relevant literature, documentary evidence, and semi-structured consultations with five experts in gender equality, diversity management, auditing, and ESG reporting. Building on the most effective and robust features across gender equality schemes, the study proposes a universal framework for gender equality certification. Under this framework, an ideal universal certification model should apply the same core requirements to both public and private organizations, while including simplified procedures tailored to small- and medium-sized enterprises (SMEs). Moreover, the model should rely on a limited set of key performance indicators (KPIs), focusing on the most material dimensions and prioritizing quantitative measures. It should also strengthen employee feedback mechanisms and enhance accountability in corporate governance. The framework should also pay attention to intersectional dimensions, extend responsibility across the value chain, and address the gender-related implications of artificial intelligence (AI). Importantly, an ideal universal gender equality certification should ensure a high level of transparency through the public disclosure of certified organizations, assessment criteria, KPIs, and levels or scores achieved. Furthermore, it should be supported by a free digital self-assessment tool and robust auditing arrangements, underpinned by a sufficiently large pool of accredited certification bodies and gender-balanced audit teams. Finally, it should undergo periodic review and align with Environmental, Social, and Governance (ESG) principles and other related SDGs. Full article

The main objective of this study is to produce a systematic literature review that analyses key performance indicators (KPI) in the context of efficient and sustainable building renovation. Efficiency and sustainability, in combination with building renovation, are important themes due to the increasing need for creating sustainable renovations worldwide. The identification and monitoring of KPIs is fundamental in decision-making processes, but also in the monitoring of short-term and long-term project goals. In the current academic literature, existing research gaps, especially in the social aspects of sustainability and research, have also been analyzed in terms of regional differences in the approach to each KPI. The systematic literature review examined 29 studies published between 2014 and 2024, based on a literature search conducted in 2024, using databases such as Scopus and Web of Science, with the final search performed in June 2024. The inclusion criteria focused on peer-reviewed studies addressing KPIs in sustainable building renovation, while studies not directly related to renovation processes or lacking KPI analysis were excluded. The research results show that the majority of studies focus on economic and environmental factors, which are the most commonly addressed, while research on other KPIs is significantly behind. The results were synthesized using a qualitative comparative analysis of identified KPI categories. This study also highlights the importance of addressing effective and sustainable renovation for historic buildings with a focus on heritage preservation and the need to further analyze the use of KPIs with a focus on historic buildings. The limitations include the limited number of studies and the underrepresentation of social sustainability aspects. Full article

In increasingly complex information technology (IT) environments, the sustainable governance of business processes requires systematic alignment between strategic intent, operational performance and long-term organizational resilience. Business Process Model and Notation (BPMN) provides a structured foundation for modeling IT workflows, while Service Level Agreements (SLAs) and key performance indicators (KPIs) formalize performance accountability. However, escalating process interdependencies and performance constraints challenge traditional managerial oversight. This study proposes a simulation-based analytical framework for SLA-aware BPMN process governance aimed at enhancing sustainable digital operations. In this context, sustainability is operationally defined as the capacity of IT business processes to consistently meet SLA-defined performance thresholds—including availability and response times—under varying workload conditions, while remaining adaptable to role reconfigurations and resilient to performance degradation over time. The methodology extends an established MATLAB/Octave modeling foundation through a MATLAB Simulink simulation tool that enables scenario testing, performance analysis and structured evaluation of role configurations under varying workload conditions. Within this framework, Artificial Intelligence (AI) is also examined as an enabling mechanism that supports performance role transformation, either augmenting human actors or operating as autonomous process agents. Rather than positioning AI as a standalone solution, the study evaluates its contribution to process responsiveness and governance efficiency within a controlled simulation context. By integrating simulation-driven decision support with performance-oriented process management, the proposed approach advances sustainable digital governance through improved reliability, adaptability and role reconfiguration. The framework provides IT managers with a structured methodology for safeguarding long-term process sustainability. The developed simulation environment is provided as Supplementary Material. Full article

Shipping is urgently exploring alternative vessel energy sources across a wide range of options—from other fossil fuels to renewables—with a view to more sustainable ship propulsion. Based on processing of publicly available data, the authors discuss the prospects of the supply chains for 16 vessel power sources alternative to oil, comparing descriptive statistics across respective fuel supply chain key performance indicators (KPIs) to evaluate potentiality along with hidden vulnerabilities. While finding marked differences across calculated mean, standard deviation and coefficient of variation values, the authors do not preclude the development of parallel ship fuel supply chains, unlike the case of previous fuel transitions in shipping. To support this scenario, already formed in practice, they emphasize the enabling attributes of today’s world fleet in terms of total capacity and of size of each of the main shipping sectors which could eventually sustain nowadays multiple fuel supply chains. Concluding on limitations and challenges that such an energy-source multitude can create, the authors underline the need to consider in the Life-Cycle Assessment (LCA) of shipping fuels their total impact, including necessary ship hardware changes for a more thorough assessment of fuels’ impact across the entire shipping services’ supply chain. Full article