COOPER-framework: A Unified Standard Process for Non-parametric Projects

Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the ‘COOPER-framework’ a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly.DEA, non-parametric efficiency, unified standard process, COOPER-framework.

Surrogate measures: A proposed alternative in human factors assessment of operational measures of performance

Surrogate measures are proposed as an alternative to direct assessment of operational performance for purposes of screening agents who may have to work under unusual stresses or in exotic environments. Such measures are particularly proposed when the surrogate can be empirically validated against the operational criterion. The focus is on cognitive (or throughput) performances in humans as opposed to sensory (input) or motor (output) measures, but the methods should be applicable for development of batteries which will tap input/output functions. A menu of performance tasks is under development for implementation on a battery-operated portable microcomputer, with 21 tests currently available. The tasks are reliable and become stable in minimum amounts of time; appear sensitive to some agents; comprise constructs related to actual job tasks; and are easily administered in most environments. Implications for human factors engineering studies in environmental stress are discussed

Integrating agri-environmental indicators, ecosystem services assessment, life cycle assessment and yield gap analysis to assess the environmental sustainability of agriculture

Agriculture's primary function is the production of food, feed, fibre and fuel for the fast-growing world population. However, it also affects human health and ecosystem integrity. Policymakers make policies in order to avoid harmful impacts. How to assess such policies is a challenge. In this paper, we propose a conceptual framework to help evaluate the impacts of agricultural policies on the environment. Our framework represents the global system as four subsystems and their interactions. These four components are the cells of a 2 by 2 matrix [Agriculture, Rest of the word]; [Socio-eco system, Ecological system]. We then developed a set of indicators for environmental issues and positioned these issues in the framework. To assess these issues, we used four well-known existing approaches: Life Cycle Assessment, Ecosystem Services Analysis, Yield Gap Analysis and Agro-Environmental Indicators. Using these four approaches together provided a more holistic view of the impacts of a given policy on the system. We then applied our framework on existing cover crop policies using an extensive literature survey and analysing the different environmental issues mobilised by the four assessment approaches. This demonstration case shows that our framework may be of help for a full systemic assessment. Despite their differences (aims, scales, standardization, data requirements, etc.), it is possible and profitable to use the four approaches together. This is a significant step forward, though more work is needed to produce a genuinely operational tool. © 2022 The Author

A novel framework for enhancing marine dual fuel engines environmental and safety performance via digital twins

The Internet of Things (IoT) advent and digitalisation has enabled the effective application of the digital twins (DT) in various industries, including shipping, with expected benefits on the systems safety, efficiency and environmental footprint. The present research study establishes a novel framework that aims to optimise the marine DF engines performance-emissions trade-offs and enhance their safety, whilst delineating the involved interactions and their effect on the performance and safety. The framework employs a DT, which integrates a thermodynamic engine model along with control function and safety systems modelling. The DT was developed in GT-ISE© environment. Both the gas and diesel operating modes are investigated under steady state and transient conditions. The engine layout is modified to include Exhaust Gas Recirculation (EGR) and Air Bypass (ABP) systems for ensuring compliance with ‘Tier III’ emissions requirements. The optimal DF engine settings as well as the EGR/ABP systems settings for optimal engine efficiency and reduced emissions are identified in both gas and diesel modes, by employing a combination of optimisation techniques including multi-objective genetic algorithms (MOGA) and Design of Experiments (DoE) parametric runs. This study addresses safety by developing an intelligent engine monitoring and advanced faults/failure diagnostics systems, which evaluates the sensors measurements uncertainty. A Failure Mode Effects and Analysis (FMEA) is employed to identify the engine safety critical components, which are used to specify operating scenarios for detailed investigation with the developed DT. The integrated DT is further expanded, by establishing a Faulty Operation Simulator (FOS) to simulate the FMEA scenarios and assess the engine safety implications. Furthermore, an Engine Diagnostics System (EDS) is developed, which offers intelligent engine monitoring, advanced diagnostics and profound corrective actions. This is accomplished by developing and employing a Data-Driven (DD) model based on Neural Networks (NN), along with logic controls, all incorporated in the EDS. Lastly, the manufacturer’s and proposed engine control systems are combined to form an innovative Unified Digital System (UDS), which is also included in the DT. The analysis of marine (DF) engines with the use of an innovative DT, as presented herein, is paving the way towards smart shipping.The Internet of Things (IoT) advent and digitalisation has enabled the effective application of the digital twins (DT) in various industries, including shipping, with expected benefits on the systems safety, efficiency and environmental footprint. The present research study establishes a novel framework that aims to optimise the marine DF engines performance-emissions trade-offs and enhance their safety, whilst delineating the involved interactions and their effect on the performance and safety. The framework employs a DT, which integrates a thermodynamic engine model along with control function and safety systems modelling. The DT was developed in GT-ISE© environment. Both the gas and diesel operating modes are investigated under steady state and transient conditions. The engine layout is modified to include Exhaust Gas Recirculation (EGR) and Air Bypass (ABP) systems for ensuring compliance with ‘Tier III’ emissions requirements. The optimal DF engine settings as well as the EGR/ABP systems settings for optimal engine efficiency and reduced emissions are identified in both gas and diesel modes, by employing a combination of optimisation techniques including multi-objective genetic algorithms (MOGA) and Design of Experiments (DoE) parametric runs. This study addresses safety by developing an intelligent engine monitoring and advanced faults/failure diagnostics systems, which evaluates the sensors measurements uncertainty. A Failure Mode Effects and Analysis (FMEA) is employed to identify the engine safety critical components, which are used to specify operating scenarios for detailed investigation with the developed DT. The integrated DT is further expanded, by establishing a Faulty Operation Simulator (FOS) to simulate the FMEA scenarios and assess the engine safety implications. Furthermore, an Engine Diagnostics System (EDS) is developed, which offers intelligent engine monitoring, advanced diagnostics and profound corrective actions. This is accomplished by developing and employing a Data-Driven (DD) model based on Neural Networks (NN), along with logic controls, all incorporated in the EDS. Lastly, the manufacturer’s and proposed engine control systems are combined to form an innovative Unified Digital System (UDS), which is also included in the DT. The analysis of marine (DF) engines with the use of an innovative DT, as presented herein, is paving the way towards smart shipping

Sustainable R&D portfolio assessment.

Research and development portfolio management is traditionally technologically and financially dominated, with little or no attention to the sustainable focus, which represents the triple bottom line: not only financial (and technical) issues but also human and environmental values. This is mainly due to the lack of quantified and reliable data on the human aspects of product/service development: usability, ecology, ethics, product experience, perceived quality etc. Even if these data are available, then consistent decision support tools are not ready available. Based on the findings from an industry review, we developed a DEA model that permits to support strategic R&D portfolio management. We underscore the usability of this approach with real life examples from two different industries: consumables and materials manufacturing (polymers).R&D portfolio management; Data envelopment analysis; Sustainable R&D;

Organizational life cycle assessment: suitability for higher education institutions with environmental management systems

[EN] Purpose The purpose of this study is to analyze the suitability of organizational life cycle assessments (O-LCAs) for higher education institutions (HEIs) with special attention to the benefits and particularities of those adopting environmental management systems (EMSs) verified according to Environmental Management and Audit Scheme (EMAS). Methods A thorough analysis following ISO/TS 14072 and UNEP Guidance was carried out using the Universitat Politècnica de València (UPV) EMS verified by the EMAS for guiding principles to develop the methodological proposal. The self-sufficiency of UPV EMS for developing an O-LCA was tested at the university pilot unit. The four steps of the O-LCA were applied to the pilot. Results and discussion A reporting organization, the organization to be studied (boundaries and scope), was defined in consideration of the environmental units (EU) of the EMS. Operational control was selected as a consolidation method. Reporting flows and system boundaries are also discussed. A three-scope scheme of the GHG protocol is introduced and combined with the ISO 14072 boundary definition to support better alignment with the HEI structure. For the life cycle inventory analysis, a mechanism for identifying activities and processes as well as their material and energy flows is proposed in consideration of the particularities of HEIs. A procedure for the prioritization of data collection efforts and cutoffs was developed. The procedure integrates current EMAS actions based on the significance of environmental aspects combined with the influence of reporting organizations under their control. Impact categories focus on midpoint indicators along with an additional inventory level indicator as part of the life cycle impact assessment (LCIA). Unfortunately, due to a lack of quality data available, LCIA can only be assessed in part with little interest in outcomes. Partial results are presented. Conclusions An EMS verified by EMAS is proven to be useful in the assessment of O-LCA for HEIs. However, EMAS requirements do not ensure the availability of all data needed to develop an O-LCA. An accounting system should complement a lack of data if it is properly structured. Considerable efforts are required to obtain an accurate result. EMS and the accounting system may be able to provide information that supports an O-LCA approach based on a coherent prioritization of data collection efforts and cutoff procedures along with a set of justified impact category indicators. Overall, organization managers must be in favor of such an assessment to meet the requirements of successful implementation.Lo-Iacono-Ferreira, VG.; Torregrosa López, JI.; Capuz-Rizo, SF. (2017). Organizational life cycle assessment: suitability for higher education institutions with environmental management systems. International Journal of Life Cycle Assessment. 22(12):1928-1943. doi:10.1007/s11367-017-1289-8S192819432212Braunschweig A (2014) GHG-balances and LCA: applying the concept of scopes in organisational LCAs. E2 Management Consulting http://www.e2mc.com Accessed 1 July 2016Clift R, Wright L (2000) Relationships between environmental impacts and added value along the supply chain. Technol Forecast Soc 65(3):281–295Cortese AD (2003) The critical role of higher education in creating a sustainable future. Planning for higher education. Retrived from http://www.aashe.org/documents/resources/pdf/Cortese_PHE.pdf . Accessed 1 June 2016Curran MA (2017) Goal and scope definition in life cycle assessment. Springer. doi: 10.1007/978—94-024-0855-3Disterheft A, da Silva Caeiro SSF, Ramos MR, de Miranda Azeiteiro UM (2012) Environmental Management Systems (EMS) implementation processes and practices in European higher education institutions—top-down versus participatory approaches. J Clean Prod 31:80–90Draucker L (2013) GHG Protocol: moving Corporate Accounting Beyond GHGs. Abstract Book: SETAC North American 34th Annual Meeting, Nashville, USAEC (2013) European Commission Organization Environmental Footprint Guide. European Commission-Joint Research Centre-Institute for Environment and Sustainability http://eur-lex.europa.eu/JOHtml.do?uri=OJ:L:2013:124:SOM:EN:HTML Accessed 1 June 2016EC (2016) European Commission Environment. Eco-Management and Audit Scheme http://ec.europa.eu/environment/emas/ Accessed 1 June 2016Finkbeiner M, Wiedemann M, Saur K (1998) A comprehensive approach towards product and organisation related environmental management tools. Int J Life Cycle Assess 3(3):169–178Fleischer G, Gerner K, Kunst H, Lichtenvort K, Rebitzer G (2001) A semi-quantitative method for the impact assessment of emissions within a simplified life cycle assessment. Int J Life Cycle Assess 6(3):149–156GRI (2005) GRI Boundary Protocol. Global Reporting Initiative. https://www.globalreporting.org/resourcelibrary/GRI-Boundary-Protocol.pdf Accessed 1 June 2016Hauschild MZ, Huijbregts MA (2015) Introducing life cycle impact assessment. In: Hauschild MZ, Huijbregts MAJ (eds) Life cycle impact assessment, LCA compendium—the complete world of life cycle assessment. Springer Science+Business Media, Dordrecht 2015. doi: 10.1007/978-94-017-9744-3_1Hellweg S, Milà i Canals L (2014) Emerging approaches, challenges and opportunities in life cycle assessment. Science 344(6188):1109–1113Hochschorner E, Finnveden G (2003) Evaluation of two simplified life cycle assessment methods. Int J Life Cycle Assess 8(3):119–128Huang YA, Lenzen M, Weber CL, Murray J, Matthews HS (2009) The role of input-output analysis for the screening of corporate carbon footprints. Econ Systems Res 21(3):217–242ISO (2004) Environmental management systems—requirements with guidance for use ISO 14001: 2004. 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Environ Sci Technol 29(9):420A–426ALife Cycle Initiative (2016) http://www.lifecycleinitiative.org/ Accessed 22 June 2016Lo-Iacono-Ferreira V, Torregrosa-López JI, Lora García J, Bastante-Ceca MJ, Capuz-Rizo SF (2011) Study of the inclusion of life cycle assessment impact categories in ecological footprint. XV International Congress of Project Engineering. ISBN: 978-84-615-4543-8Lo-Iacono-Ferreira VG, Torregrosa-López JI, Capuz-Rizo SF (2016a) Use of life cycle assessment methodology in the analysis of ecological footprint assessment results to evaluate the environmental performance of universities. J Clean Prod 133:43–53Lo-Iacono-Ferreira VG, Capuz-Rizo SF, Torregrosa-López JI (2016b) Ecological Footprint Assessment of Higher Education applying Life Cycle Assessment framework. Case study: Universitat Politència de València. 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Carbon Footprint Management In Austrian SMEs: Strategies, Mitigation Measures, Challenges And Case Studies

The term Anthropocene describes the dawn of an epoch in which human activities have become the dominant force destructing the ecosystem and causing climate change. By contributing at least one fifth to global greenhouse gas (GHG) emissions, industry has a significant environmental impact. Reducing these emissions requires coordinated action along the value chains building on transnational agreements and regulations. Based on the European Green Deal, EU-countries and their industrial companies see themselves forced to react to emerging regulations considering their cooperate carbon footprint and mitigation strategies as well as the assessment and improvement of their carbon footprints. In this paper we report findings of case studies in Austrian SMEs that show how such companies can react to these challenges. We illustrate an approach to identify existing reduction potentials by engineering optimization and product life-cycle-design to reduce corporate and product carbon footprints and prepare for future reporting regulations and to achieve market advantages

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version