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Dalpadulo, Enrico, Francesco Gherardini, Fabio Pini, and Francesco Leali. "Integration of Topology Optimisation and Design Variants Selection for Additive Manufacturing-Based Systematic Product Redesign." Applied Sciences 10, no. 21 (November 5, 2020): 7841. http://dx.doi.org/10.3390/app10217841.
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The development of additive manufacturing allows the transformation of technological processes and the redesign of products. Among the most used methods to support additive manufacturing, the design can be optimised through the integration of topology optimisation techniques, allowing for creating complex shapes. However, there are critical issues (i.e., definition of product and process parameters, selection of redesign variants, optimised designs interpretation, file exchange and data management, etc.) in identifying the most appropriate process and set-ups, as well as in selecting the best variant on a functional and morphological level. Therefore, to fully exploit the technological potentials and overcome the drawbacks, this paper proposes a systematic redesign approach based on additive manufacturing technologies that integrate topology optimisation and a tool for selecting design variants based on the optimisation of both product and process features. The method leads to the objective selection of the best redesigned configuration in accordance with the key performance indicators (KPIs) (i.e., functional and production requirements). As a case study, the redesign of a medical assistive device is proposed, previously developed in fused filament fabrication and now optimised for being 3D printed with selective laser melting.
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Kohlgrüber, Michael, Antonius Schröder, Félix Bayón Yusta, and Asier Arteaga Ayarza. "A new innovation paradigm: combining technological and social innovation." Matériaux & Techniques 107, no. 1 (2019): 107. http://dx.doi.org/10.1051/mattech/2018065.
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A new innovation paradigm is needed to answer the societal, economic and environmental challenges the world and companies are facing. The EU funded Horizon 2020 SPIRE Project “Coordinating Optimisation of Complex Industrial Processes” (COCOP) is combining technological and social innovation within a steel company pilot case (Sidenor). The project aims at reducing raw materials consumption (and energy and emissions reduction as well) by plant-wide optimisation of production processes based on a software solution and at the same time changing social practices. Key for COCOP is a methodology integrating technological innovation within a social innovation process of co-creation and co-development by involving (potential) users of the future software system and relevant stakeholders right from the beginning; thereby improving effectiveness and impact of the innovations and the implementation process. This involvement is instructed and measured by social key performance indicators (social KPIs) and operationalised in surveys (questionnaire and interviews) with future users, engineers and external experts (from different industry sectors not involved in the project). The article presents the results of the starting point of COCOP illustrating the future user perspective of the pilot steel company (Sidenor) contrasted by the view of external experts – seriously taking into account the interfaces between technology, human and organisation.
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Redlein, A., C. Baretschneider, and L. Thrainer. "ESG monitoring and optimisation solutions and their return on investment: results of several case studies." IOP Conference Series: Earth and Environmental Science 1176, no. 1 (May 1, 2023): 012029. http://dx.doi.org/10.1088/1755-1315/1176/1/012029.
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Abstract In 2021 the European Union defined the Environmental, Social and Governance (ESG) directive to foster sustainability. As the real estate sector is responsible for around 40% of the CO2 emissions, this industry has to carry out additional sustainability reporting and optimisation activities to prove its assets are fulfilling sustainability goals. Most investors concentrate on energy- and CO2 reduction, but ESG is much more. The Sustainable Development Goals of the United Nations give a perfect overview of the related topics but do not define KPIs. A second challenge is that the market has not honoured the additional tasks by now. Automation is necessary to reduce efforts of the activities The paper provides answers to the following research questions based on several case studies: What are the relevant parameters to prove ESG, focusing especially on the areas of “Environment” and “Social” as parts of the ESG directive? How can an IT support look like to automatise the data gathering efficiently? What is the Return on Investment of the suggested solution? The research focuses on historical buildings as they usually have a low degree of building automation. The solution is to enable efficient, automated optimisation of energy consumption and safeguard the well-being of the tenants with low investment.
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Shariat, Mehrdad, Ömer Bulakci, Antonio De Domenico, Christian Mannweiler, Marco Gramaglia, Qing Wei, Aravinthan Gopalasingham, et al. "A Flexible Network Architecture for 5G Systems." Wireless Communications and Mobile Computing 2019 (February 11, 2019): 1–19. http://dx.doi.org/10.1155/2019/5264012.
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In this paper, we define a flexible, adaptable, and programmable architecture for 5G mobile networks, taking into consideration the requirements, KPIs, and the current gaps in the literature, based on three design fundamentals: (i) split of user and control plane, (ii) service-based architecture within the core network (in line with recent industry and standard consensus), and (iii) fully flexible support of E2E slicing via per-domain and cross-domain optimisation, devising inter-slice control and management functions, and refining the behavioural models via experiment-driven optimisation. The proposed architecture model further facilitates the realisation of slices providing specific functionality, such as network resilience, security functions, and network elasticity. The proposed architecture consists of four different layers identified as network layer, controller layer, management and orchestration layer, and service layer. A key contribution of this paper is the definition of the role of each layer, the relationship between layers, and the identification of the required internal modules within each of the layers. In particular, the proposed architecture extends the reference architectures proposed in the Standards Developing Organisations like 3GPP and ETSI, by building on these while addressing several gaps identified within the corresponding baseline models. We additionally present findings, the design guidelines, and evaluation studies on a selected set of key concepts identified to enable flexible cloudification of the protocol stack, adaptive network slicing, and inter-slice control and management.
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Vavallo, Michele, Marco Arnesano, Gian Marco Revel, Asier Mediavilla, Ane Ferreiro Sistiaga, Alessandro Pracucci, Sara Magnani, and Oscar Casadei. "Accelerating Energy Renovation Solution for Zero Energy Buildings and Neighbourhoods—The Experience of the RenoZEB Project." Proceedings 20, no. 1 (July 18, 2019): 1. http://dx.doi.org/10.3390/proceedings2019020001.
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Buildings are the key factor to transform cities and to contribute to recent European energy efficiency objectives for 2030 and long-term 2050. New buildings account to only 1–2% annually. Yet, ninety percent of the existing building stock in Europe was built before 1990, it is therefore necessary to promote their energy renovation to achieve the set objectives. Renovation solutions are available on the market, yet a wrong implementation and integration due to a lack of knowledge neither maximizes the energy performance of the post-retrofitting nor the financial optimisation and viability of the projects. This paper presents research on a plug & play, modular, easy installable façade and ICT decision making technologies to provide affordable solutions in order to overcome those deep renovation barriers. The paper sets out by defining a value framework that can be applied by real estate investors for making better retrofitting decisions for residential buildings, through mapping targeted building typologies and investigating new building revalorisation strategies, new renovation concepts and KPIs for evaluation. Thereafter the paper presents the modular and easy-to-install façade system that is replicable and scalable at European level.
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Branca, Teresa Annunziata, Ismael Matino, Valentina Colla, Alice Petrucciani, Amarjit Kuor Maria Singh, Antonella Zaccara, Teresa Beone, et al. "Paving the way for the optimization of water consumption in the steelmaking processes: barriers, analysis and KPIs definition." Matériaux & Techniques 108, no. 5-6 (2020): 510. http://dx.doi.org/10.1051/mattech/2021006.
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The efficient use of water resources is one of the main challenges of the steel sector, according to the European Union water policy. On this subject, monitoring and optimization systems, linked to the innovative water treatments, represent important tools to improve water management and the related energy use. The present paper describes a part of the work developed in the early stage of the project entitled “Water and related energy Hub Advanced Management system in steelworks – WHAM”, which is co-funded by the Research Fund for Coal and Steel. The project aims at optimizing water consumption in the steelworks through a holistic combination of on-line monitoring and optimisation and innovative water treatment technologies. As different aspects affect water use in the steelmaking processes, in the first part of the paper, the main technical barriers and factors, that can impact on reuse and recirculation of wastewater and energy efficiency, are analysed. The main constraints on water management in the steel sector, such as fresh water availability, its quality and local legal requirements, were considered in order to maximise the water reuse and recycling. Furthermore, the main barriers, such as environmental issues and several costs, were investigated. In the second part of the paper, a set of Key Performance Indicators are listed. They aim at assessing and monitoring the water management sustainability in a holistic way, both in terms of environmental and economic performances, as well as of new water treatments efficiency and their economic viability. Key Performance Indicators will be used to monitor the efficiency of water management, aiming at achieving significant increase of performances. On the other hand, some of these indicators will be used as objective functions for problems optimization. The computation of the selected Key Performance Indicators will take into account both industrial data and results from simulations that will be carried out after the development of suitable tools in order to assess the feasibility of some relevant process modifications or the applications of new technologies.
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Kassen, Stefan, Holger Tammen, Maximilian Zarte, and Agnes Pechmann. "Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation." Processes 9, no. 8 (August 3, 2021): 1362. http://dx.doi.org/10.3390/pr9081362.
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Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for production optimisation and can be used to simulate production systems, which reduce necessary physical test runs and related costs. While most companies are not able to create digital twins yet, companies using enterprise resource planning (ERP) systems have the general capability to create digital shadows. This paper presents a concept and a case study for a generic simulation of production systems in AnyLogic™ to create digital shadows as the first step towards a full digital twin. The generic simulation visualises production systems automatically and displays key performance indicators (KPIs) for the planned production program, using representational state transfer (REST) interfaces to extract product and production data from an ERP system. The case study has been applied in a learning factory of the University of Applied Life Sciences Emden/Leer. The results prove the presented concept of the generic simulation and show the limits and challenges of working with generic simulation models.
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Stora, T., C. Duchemin, W. Andreazza, E. Aubert, C. Bernerd, T. Cocolios, M. Deschamps, et al. "CERN-MEDICIS: Operational indicators to support the production of new medical radionuclides by mass-separation." Journal of Physics: Conference Series 2687, no. 8 (January 1, 2024): 082039. http://dx.doi.org/10.1088/1742-6596/2687/8/082039.
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Abstract CERN-MEDICIS is an isotope mass separation facility dedicated to biomedical research located in a type A work sector, receiving on average 50% of the 1.4 GeV protons delivered by the Proton Synchrotron Booster (PSB). It was commissioned with Radioactive Ion Beams (RIB’s) in 2017. MEDICIS has operated for the past 5 years in batch mode, with targets irradiated in a station located at the HRS beam dump, and with external sources provided by MEDICIS cyclotrons and nuclear reactors partners, notably during the Long Shutdown (LS2). Additional features of the facility include the MELISSA laser ion source, radiochemistry on implanted radionuclides and an online gamma-ray spectroscopy implantation monitoring. In 2022, we introduced Key Performance Indicators (KPI’s) to monitor the operation of the facility for collected efficiencies, the optimisation of the radiological risks and evaluate impact of possible modifications of the station, paralleling for instance LHC’s integrated luminosity. Defined KPI’s cover aspects in the operation cycle, e.g. planning in CERN schedule, target irradiations, duration of the process, radiological risk mitigation, facility up-time, developments and maintenance. MEDICIS KPI’s can help distinguish which of the operation and infrastructure life cycle requires immediate intervention, developments or consolidation. Those are related to the irradiation stations and irradiation possibilities, the beamlines (parallel collections), target and ion sources (reliability), robot handling and infrastructure, or the separation process itself.
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Jurczak, Marcin, Grzegorz Miebs, and Rafał A. Bachorz. "Multi-criteria human resources planning optimisation using genetic algorithms enhanced with MCDA." Operations Research and Decisions 32, no. 4 (2022). http://dx.doi.org/10.37190/ord220404.
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The main objective of this paper is to present an example of the IT system implementation with advanced mathematical optimisation for job scheduling. The proposed genetic procedure leads to the Pareto front, and the application of the multiple criteria decision aiding (MCDA) approach allows extraction of the final solution. Definition of the key performance indicator (KPI) reflecting relevant features of the solutions, and the efficiency of the genetic procedure provide the Pareto front comprising the representative set of feasible solutions. The application of chosen MCDA, namely elimination et choix traduisant la réalité (ELECTRE) method, allows for the elicitation of the decision maker (DM) preferences and subsequently leads to the final solution. This solution fulfils all of the DM expectations and constitutes the best trade-off between considered KPIs. The proposed method is an efficient combination of genetic optimisation and the MCDA method.
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Rison, S. C. G., I. Dostal, Z. Ahmed, Z. Raisi-Estabragh, C. Carvalho, M. Lobo, R. Patel, et al. "Protocol design and preliminary evaluation of the REAL-Health Triple Aim, an open-cohort CVD-care optimisation initiative." European Heart Journal 42, Supplement_1 (October 1, 2021). http://dx.doi.org/10.1093/eurheartj/ehab724.3170.
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Abstract Introduction Effective treatment of cardiovascular disease (CVD) in primary care could be improved. We aim to assess the efficacy of a scalable treatment optimisation programme in unselected community populations in South East England, with the triple aim of improved blood pressure control in people with hypertension, increased high-intensity statin use in people with CVD and reduced gastrointestinal bleeding in patients on antithrombotic medication. Method This observational study comprises an open cohort of approximately 200,000 adults at high cardiovascular risk registered with general practitioners in five South East England Clinical Commissioning Groups (CCGs). An intervention programme is planned in four of these CCGs with a further non-intervention CCG acting as a control group. The intervention will consist of: clinical guidelines and educational outreach; virtual patient-reviews software; peer-performance “dashboards” and, where available, financial incentives. The study will examine 3 primary outcomes: 1. Diagnosed hypertension with a blood pressure <140/90mmHg; 2. Diagnosed CVD on a high-intensity statin; 3. A cardiovascular indication for antithrombotic therapy with one or more factors for increased risk of gastrointestinal bleeding (e.g. age ≥65) on gastroprotection. A further 17 secondary outcomes related to these three aims will be assessed. Analysis We will use an interrupted time series analysis over 18 months, representing the pre-implementation, implementation and the post-implementation phases with comparison to the control CCG and applicable national Quality and Outcomes Framework and national prescribing statistics (e.g. OpenPrescribing). Secondary outcomes include an equity impact analysis with results stratified by age, gender, ethnic group and index of deprivation. Preliminary data We present preliminary data on Key Performance Indicators (KPIs) collected from 191 GP practices including [percentage achievement on 01/09/2019, on 01/09/2020]: 1. Patients with hypertension and most recent blood pressure ≤140/90mmHg [68.7%, 60.6%]. 2. Patients eligible for treatment with a high-intensity statin on such treatment [53.8%, 55.8%]. 3. Patients on antithrombotics with ≥1 risk factors for gastrointestinal bleeding on gastroprotection [59.0%, 60.1%]. We also present our virtual patient-review software tool and outcome visualisation dashboard. Conclusion The REAL-Health Triple Aim initiative is a large-scale primary care cardiovascular risk reduction initiative which was launched almost contemporaneously with the United Kingdom's first SARS-CoV-2 related lockdown. Preliminary data justify the need for the Triple Aim initiative and give us an insight on the impact of the pandemic on its implementation. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): Barts CharityBritish Heart Foundation
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Treanor, C., J. Smith, and M. McCabe. "124 AN INTERDISCIPLINARY PREHABILITATION PILOT FOR FRAIL ADULTS UNDERGOING ELECTIVE ANTERIOR RESECTION AND HARTMANN’S REVERSAL SURGERIES IN AN IRISH ACUTE HOSPITAL." Age and Ageing 51, Supplement_3 (October 25, 2022). http://dx.doi.org/10.1093/ageing/afac218.103.
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Abstract Background Frailty affects 21.5% of individuals aged 65 and over in Ireland (TILDA, 2017).Timely interventions can limit or reverse the impacts of frailty. Local HIPE data from 2016-2020 highlighted correlations between increased average Length of Stay (aLOS) and median age (>65 years) for those undergoing elective Anterior Resections and Hartmann’s reversal surgeries. Prehabilitation aims to identify and manage modifiable risk factors that may impact on LOS, as well as optimise patients’ resilience and physiological reserves to reduce postoperative complications. Modifiable factors include pre-operative function, co-morbidities and post-operative delirium. In the Republic of Ireland, surgical interdisciplinary Prehabilitation services exist only in one hospital. Methods An interdisciplinary prehabilitation pilot for individuals undergoing elective colorectal surgeries was developed. Patients are referred from surgical clinics to Physiotherapy, Occupational Therapy or Dietitian preoperatively. Interventions include respiratory optimisation, exercise prescription, discharge planning, equipment provision and pre-operative nutritional reviews. Results Three elective patients have completed the first phase of the pilot. Two underwent anterior resections and one underwent a Hartmann’s reversal. The LOS for each individual was 4 days respectively, 4 days under the KPIs. Patients received virtual assessment and individualised interventions including an interdisciplinary educational booklet. Interventions included: exercise programmes, nutritional support, discharge planning discussion and equipment as indicated. No post-operative complications were identified and no interim beds or home supports were required. Qualitative feedback surveys were completed by all participants. Subjective feedback from patients has been overwhelmingly positive. Conclusion Patients report feeling physically and psychologically better prepared for surgery with better knowledge of post-operative expectations. Patients are more proactive in their postoperative recovery meaning they can return home sooner. This pilot enhances evidence-based ERAS practice, improving the quality and safety of patients journey. Participants also had a 12 day cumulative reduction in aLOS with financial savings of €12000.
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Samal, Arnada Prasad. "Use of Data Analytics for Power Plant Operation Optimization." Power Research - A Journal of CPRI, March 1, 2024, 185–94. http://dx.doi.org/10.33686/pwj.v19i2.1149.
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Optimized operation and maintenance of a power plant to improve the KPIs is the key to success. Forced outages not only make the unit unavailable but also increase the number of start-ups and hence high cost and deteriorated plant life. Fault diagnostics and prediction of future behavior of equipment by data analytic techniques will be very handy in improving reliability. On the other hand, the cost of generation depends upon how efficiently the plants are operated. Any deviation from the optimized design point, results in losses and hence as far as possible the deviations should be minimized. However, the deviations are unavoidable due to various reasons. Along with efficient operation, Environmental compliance, and flexibility is also to be ensured to meet the statutory requirements. With the advancement of computing techniques, data analytics, and Artificial Intelligence are being used for the optimization of many industrial processes. Given the background, the objective of this paper is to study and suggest how Data Analytics can be utilized for the optimization of power plant operations to improve reliability, efficiency, and flexibility, and minimize the impact on the environment. Many statistical methods are available to identify the hidden pattern in the data which can be used for optimisation of processes. AI is used for process control, diagnosing faults, and predicting of future behaviors so that advanced action can be taken to avoid surprises. The domain expertise along with data analytic methods can be utilized to find solutions to a variety of problems. In this paper, a comprehensive data analytic tool with four modules i.e., “Efficiency optimization”, “Plant Health monitoring and reporting”, “Optimization of life consumption” and “Environment protection” has been conceived for application. These Modules work in an integrated manner and shall monitor, optimize, control, and report/advise. The tool shall have a digital replica of the individual equipment for simulation individually as well as in combination with other related equipment for whole plant performance prediction and diagnosis. The replica shall use its database for machine learning and for running of diagnostic process.
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Ashcroft, Julie. "Optimising metal content in PGM ammonia oxidation catalysts." Johnson Matthey Technology Review, 2020. http://dx.doi.org/10.1595/205651321x16012842414480.
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Platinum based knitted gauzes are the most efficient catalysts for the production of nitric oxide (NO), as a precursor to the manufacture of nitric acid and caprolactam. Decades of research and optimisation have resulted in a greater understanding of ammonia oxidation kinetics and associated metal movement within these catalyst packs, along with the development of beneficial binary and ternary alloys. The design of a pack has evolved from the simple addition or removal of metal to modelling the optimal installed metal content and distribution. This review discusses the fundamental kinetics and in-situ metal loss for ammonia oxidation catalysts in nitric acid applications and outlines how they can, in conjunction with prevailing PGM market conditions and plant KPI’s, influence the optimal catalyst design.
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Khakyzadeh, Vahid, Hadi Rezaei-Vahidian, Sahra Sheikhaleslami, and Seyedeh Bahareh Azimi. "Modelling and optimisation of p-nitrophenol removal process using homogeneous photo-periodate (UV/KPI) advanced oxidation process." International Journal of Environmental Analytical Chemistry, June 28, 2021, 1–12. http://dx.doi.org/10.1080/03067319.2021.1938022.
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Chaudhuri, K. Ray, Per Odin, Joaquim J. Ferreira, Angelo Antonini, Olivier Rascol, Mónica M. Kurtis, Alexander Storch, et al. "Opicapone versus placebo in the treatment of Parkinson’s disease patients with end-of-dose motor fluctuation-associated pain: rationale and design of the randomised, double-blind OCEAN (OpiCapone Effect on motor fluctuations and pAiN) trial." BMC Neurology 22, no. 1 (March 12, 2022). http://dx.doi.org/10.1186/s12883-022-02602-8.
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Abstract Background Optimisation of dopaminergic therapy may alleviate fluctuation-related pain in Parkinson’s disease (PD). Opicapone (OPC) is a third-generation, once-daily catechol-O-methyltransferase inhibitor shown to be generally well tolerated and efficacious in reducing OFF-time in two pivotal trials in patients with PD and end-of-dose motor fluctuations. The OpiCapone Effect on motor fluctuations and pAiN (OCEAN) trial aims to investigate the efficacy of OPC 50 mg in PD patients with end-of-dose motor fluctuations and associated pain, when administered as adjunctive therapy to existing treatment with levodopa/dopa decarboxylase inhibitor (DDCi). Methods OCEAN is a Phase IV, international, multicentre, randomised, double-blind, placebo-controlled, parallel-group, interventional trial in PD patients with end-of-dose motor fluctuations and associated pain. It consists of a 1-week screening period, 24-week double-blind treatment period and 2-week follow-up period. Eligible patients will be randomised 1:1 to OPC 50 mg or placebo once daily while continuing current treatment with levodopa/DDCi and other chronic, stable anti-PD and/or analgesic treatments. The primary efficacy endpoint is change from baseline in Domain 3 (fluctuation-related pain) of the King’s Parkinson’s disease Pain Scale (KPPS). The key secondary efficacy endpoint is change from baseline in Domain B (anxiety) of the Movement Disorder Society-sponsored Non-Motor rating Scale (MDS-NMS). Additional secondary efficacy assessments include other domains and total scores of the KPPS and MDS-NMS, the Parkinson’s Disease Questionnaire (PDQ-8), the MDS-sponsored Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Parts III and IV, Clinical and Patient’s Global Impressions of Change, and change in functional status via Hauser’s diary. Safety assessments include the incidence of treatment-emergent adverse events. The study will be conducted in approximately 140 patients from 50 clinical sites in Germany, Italy, Portugal, Spain and the United Kingdom. Recruitment started in February 2021 and the last patient is expected to complete the study by late 2022. Discussion The OCEAN trial will help determine whether the use of adjunctive OPC 50 mg treatment can improve fluctuation-associated pain in PD patients with end-of-dose motor fluctuations. The robust design of OCEAN will address the current lack of reliable evidence for dopaminergic-based therapy in the treatment of PD-associated pain. Trial registration EudraCT number 2020–001175-32; registered on 2020-08-07.