D8.6 OPTIMAI commercialization and exploitation strategy

Deliverable D8.6 OPTIMAI commercialization and exploitation strategy 1 st version is the first version of the OPTIMAI Exploitation Plan. Exploitation aims at ensuring that OPTIMAI becomes sustainable well after the conclusion of the research project period so as to create impact. OPTIMAI intends to develop an industry environment that will optimize production, reducing production line scrap and production time, as well as improving the quality of the products through the use of a variety of technological solutions, such as Smart Instrumentation of sensors network at the shop floor, Metrology, Artificial Intelligence (AI), Digital Twins, Blockchain, and Decision Support via Augmented Reality (AR) interfaces. The innovative aspects: Decision Support Framework for Timely Notifications, Secure and adaptive multi-sensorial network and fog computing framework, Blockchain-enabled ecosystem for securing data exchange, Intelligent Marketplace for AI sharing and scrap re-use, Digital Twin for Simulation and Forecasting, Embedded Cybersecurity for IoT services, On-the-fly reconfiguration of production equipment allows businesses to reconsider quality management to eliminate faults, increase productivity, and reduce scrap. The OPTIMAI exploitation strategy has been drafted and it consists of three phases: Initial Phase, Mid Phase and Final Phase where different activities are carried out. The aim of the Initial phase (M1 to M12), reported in this deliverable, is to have an initial results' definition for OPTIMAI and the setup of the structures to be used during the project lifecycle. In this phase, also each partner's Individual Exploitation commitments and intentions are drafted, and a first analysis of the joint exploitation strategies is being presented. The next steps, leveraging on the outcomes of the preliminary market analysis, will be to update the Key Exploitable Results with a focus on their market value and business potential and to consolidate the IPR Assessment and set up a concrete Exploitation Plan. The result of the next period of activities will be reported in D8.7 OPTIMAI commercialization and exploitation strategy - 2nd version due at month 18 (June 2022

D2.1 - OPTIMAI - User and ethics legal requirements

The purpose of the deliverable D2.1 'User and ethics and legal requirements I' is to gather and analyse the requirements concerning zero defect manufacturing, quality inspection, production re-configuration and other technology needs of the OPTIMAI pilot partners as well as the legal and ethical issues related to the development and implementation of the platform. The analysis of the initial gathered user and ethics and legal requirements kicks off the relevant development and integration activities in the OPTIMAI project. The requirements elicitation and analysis take into account the Description of Action (DoA), the requirements identified from the pilot partners (i.e. manufacturing companies) and the other OPTIMAI partners, based on their knowledge, expertise and more specifically, the needs in the particular domains that the project pursues to address. Additionally, ethics and legal requirements, as well as technological innovation potential requirements are identified and included in this document. The initial identification of requirements is based on questionnaires, online meetings and videos from the pilot sites, while the method used will be re-iterated through each of the project phases. The identified requirements are grouped into functional and non-functional requirements. Functional requirements describe what the system should do and are classified according to the components of the OPTIMAI architecture. Non-functional requirements are grouped into KPIs, ethics, legal and technology innovation potential requirements. In total 127 requirements are identified out of which 81 are prioritised as "Must" (have), 36 as "Should" have and 10 as "Could" have

D2.2 - OPTIMAI - User and ethics and legal requirements II

The purpose of the deliverable D2.2 'User and ethics and legal requirements II' is to identify and analyse the new requirements that have emerged during M7 and M14 and update the previously identified requirements concerning zero defect manufacturing, quality inspection, production re-configuration and other technology needs of the OPTIMAI pilot partners as well as the legal and ethical issues related to the development and implementation of the platform. The analysis of the initial gathered user and ethics and legal requirements is used as the basis of the initial developments and integration activities of the OPTIMAI project. The requirements elicitation and analysis take into account the Description of Action (DoA), the requirements identified and updated from the pilot partners (i.e. manufacturing companies) and the other OPTIMAI partners, based on their knowledge, expertise and more specifically, the needs in the particular domains that the project pursues to address. Additionally, a new set of ethics and legal requirements focusing on the pilot applications is presented. The technological innovation potential requirements identified in the first version of this deliverable, are linked to the stateof-the-art technologies and the identified assets per partner. The update and refinement of the requirements is based on online and shopfloor meetings, videos and photos from the pilot sites, while the method used will be re-iterated through each of the project phases. The identified requirements are grouped into functional and nonfunctional requirements. Functional requirements describe what the system should do and are classified according to the components of the OPTIMAI architecture. Non-functional requirements are grouped into KPIs, ethics, legal and technology innovation potential requirements. In total 192 requirements are identified out of which 34 are updated and 65 are new. 148 are prioritised as "Must" (have), 35 as "Should" (have) and 9 as "Could" (have)

Comparison of superior vena cava and femoroiliac vein pressure according to intra-abdominal pressure.

International audienceUNLABELLED: ABSTRACT: BACKGROUND: Previous studies have shown a good agreement between central venous pressure (CVP) measurements from catheters placed in superior vena cava and catheters placed in the abdominal cava/common iliac vein. However, the influence of intra-abdominal pressure on such measurements remains unknown. METHODS: We conducted a prospective, observational study in a tertiary teaching hospital. We enrolled patients who had indwelling catheters in both superior vena cava (double lumen catheter) and femoroiliac veins (dialysis catheter) and into the bladder. Pressures were measured from all the sites, CVP, femoroiliac venous pressure (FIVP), and intra-abdominal pressure. RESULTS: A total of 30 patients were enrolled (age 62 ± 14 years; SAPS II 62 (52-76)). Fifty complete sets of measurements were performed. All of the studied patients were mechanically ventilated (PEP 3 cmH20 (2-5)). We observed that the concordance between CVP and FIVP decreased when intra-abdominal pressure increased. We identified 14 mmHg as the best intra-abdominal pressure cutoff, and we found that CVP and FIVP were significantly more in agreement below this threshold than above (94% versus 50%, P = 0.002). CONCLUSIONS: We reported that intra-abdominal pressure affected agreement between CVP measurements from catheter placed in superior vena cava and catheters placed in the femoroiliac vein. Agreement was excellent when intra-abdominal pressure was below 14 mmHg

Alteration of skin perfusion in mottling area during septic shock.

International audienceBACKGROUND: Mottling score has been reported to be a strong predictive factor during septic shock. However, the pathophysiology of mottling remains unclear. METHODS: In patients admitted in ICU for septic shock, we measured on the same area the mean skin perfusion by laser Doppler, the mottling score, and variations of both indices between T1 (6 hours after vasopressors were started) and T2 (24 hours later). RESULTS: Fourteen patients were included, SAPS II was 56 [37--71] and SOFA score at T1 was 10 [7--12]. The mean skin surface area analyzed was 4108 +/- 740 mm2; 1184 +/- 141 measurements were performed over each defined skin surface area. Skin perfusion was significantly different according to mottling score and decreased from 37 [31--42] perfusion units (PUs) for a mottling score of [0--1] to 22 [20--32] PUs for a mottling score of [2--3] and 23 [16--28] for a score of [4--5] (Kruskal-Wallis test, P = 0.05). We analyzed skin perfusion changes during resuscitation in each patient and together with mottling score variations between T1 and T2 using a Wilcoxon signed-rank test. Among the 14 patients included, mottling score increased (worsened) in 5 patients, decreased (improved) in 5 patients, and remained stable in 4 patients. Baseline skin perfusion at T1 was arbitrarily scored 100%. Mean skin perfusion significantly decreased in all the patients whose mottling score worsened from 100% baseline to 63.2 +/- 10.7% (P = 0.001), mean skin perfusion significantly increased in all patients whose mottling score improved from 100% baseline to 172.6 +/- 46.8% (P = 0.001), and remained stable in patients whose mottling score did not change (100.5 +/- 6.8%, P = 0.95). CONCLUSIONS: We have shown that mottling score variations and skin perfusion changes during septic shock resuscitation were correlated, providing additional evidence that mottling reflects skin hypoperfusion

Open Access Alteration of skin perfusion in mottling area during septic shock

Background: Mottling score has been reported to be a strong predictive factor during septic shock. However, the pathophysiology of mottling remains unclear. Methods: In patients admitted in ICU for septic shock, we measured on the same area the mean skin perfusion by laser Doppler, the mottling score, and variations of both indices between T1 (6 hours after vasopressors were started) and T2 (24 hours later). Results: Fourteen patients were included, SAPS II was 56 [37–71] and SOFA score at T1 was 10 [7–12]. The mean skin surface area analyzed was 4108 ± 740 mm 2; 1184 ± 141 measurements were performed over each defined skin surface area. Skin perfusion was significantly different according to mottling score and decreased from 37 [31–42] perfusion units (PUs) for a mottling score of [0–1] to 22 [20–32] PUs for a mottling score of [2–3] and 23 [16–28] for a score of [4–5] (Kruskal-Wallis test, P = 0.05). We analyzed skin perfusion changes during resuscitation in each patient and together with mottling score variations between T1 and T2 using a Wilcoxon signed-rank test. Amon

Extended-spectrum beta-lactamase − producing enterobacteriaceae in the intensive care unit: acquisition does not mean cross-transmission

International audienceBackgroundIn intensive care unit (ICU), infection and colonization by resistant Gram-negative bacteria increase costs, length of stay and mortality. Extended-spectrum beta-lactamase − producing Enterobacteriaceae (ESBL-E) is a group of pathogens increasingly encountered in ICU setting. Conditions that promote ESBL-E acquisition are not completely understood. The increasing incidence of infections related to ESBL-E and the unsolved issues related to ESBL-E cross-transmission, prompted us to assess the rates of referred and acquired cases of ESBL-E in ICU and to assess patient-to-patient cross-transmission of ESBL-E using a multimodal microbiological analysis.MethodsDuring a 5-month period, all patients admitted to a medical ICU were tested for ESBL-E carriage. A rectal swab was performed at admission and then twice a week until discharge or death. ESBL-E strains were analyzed according to antibiotic susceptibility pattern, rep-PCR (repetitive-element Polymerase chain reaction) chromosomal analysis, and plasmid PCR (Polymerase chain reaction) analysis of ESBL genes. Patient-to-patient transmission was deemed likely when 2 identical strains were found in 2 patients hospitalized simultaneously in the ICU.ResultsAmong the 309 patients assessed for ESBL-E carriage on admission, 25 were found to carry ESBL-E (importation rate: 8 %). During follow-up, acquisition was observed among 19 of them (acquisition rate: 6.5 %). Using the multimodal microbiological approach, we found only one case of likely patient-to-patient ESBL-E transmission.ConclusionsIn unselected ICU patients, we found rather low rates of ESBL-E referred and acquired cases. Only 5 % of acquisitions appeared to be related to patient-to-patient transmission. These data highlight the importance of jointly analyzing phenotypic profile and molecular data to discriminate strains of ESBL-E

D2.3 - OPTIMAI - State of the art survey

This report is in fulfilment of requirements for Deliverable D2.3 of OPTIMAI. The document reports the State-of-the-Art in related scientific fields and identifies relevant research initiatives. Information contained herein is the result of activities performed in Task 2.2 (State of the art analysis, existing and past research initiatives). The key activities performed in this task are summarized in the following list: - Short introduction to Industry 4.0 to support the relevance and necessity of artificial intelligence in modern industry. - Assessment of the state-of-the-art within existing results coming from related projects, to identify which ones are relevant to OPTIMAI. This assessment was performed in terms of functionality provided, innovation capacity, technology, license, status, etc. - Assessment of the state-of-the-art within relevant scientific domains, including Artificial Intelligence (AI) for Industry, Metrology, AI-enhanced Digital Twins, Internet of Things (IoT) sensors, Computer Vision and Augmented Reality. - For the sake of completeness, a survey on ethical aspects is also performed. This is kept short since it is subject to other Deliverables of OPTIMAI. The review methodology is described in detail, in terms of sources, search keys, criteria for selection/exclusion etc., so that this work is repeatable. 269 articles were finally considered for inclusion in this report. Upon review of all relevant works, findings are summarized and discussed. The use of artificial intelligence technologies in various industrial fields is explored and investigated; enlightening graphs are produced to visualize the distribution and popularity of each AI-tech, implying its suitability for different purposes

D2.4 - OPTIMAI - The OPTIMAI architecture specifications

This document contains the preliminary description of the OPTIMAI smart manufacturing solution architecture based on the elicited stakeholders' requirements and use case scenario definitions that preceded it. This first version architecture (M12) is the outcome of a three-step design methodology which started with relevant technology exploration in the context of D2.3. This process was followedup through a closer examination of the most prominent reference architectural models provisioned for smart manufacturing and industrial Internet of Things applications. A top-down design approach was then carried out using the original OPTIMAI architecture proposition as a starting point so as to identify the various components and subsystems that deliver on the specified needs and requirements of the end-users. Through this exercise, the architecture was broken down into 36 basal components. Each one of those base elements was then elaborated by project partners responsible for their implementation through a bottom-up functional specification. Through this process, three architectural viewpoints are defined for the OPTIMAI envisioned solution in this document, namely the functional, information and deployment view. The functional view delivers a high-level overview of the envisioned system functionality broken down into the identified subsystems and individual components, all of whom are described in terms of their foreseen roles and responsibilities within the runtime operation of the system. Aspects related to integration, such as the interrelationships among platform components are presented, in order to guide the development of the necessary intercommunication mechanisms between components. This process is complemented by means of aligning the resulting architectural components to prominent Industry 4.0 reference architecture models and principles. The Information view then elaborates on the flow of information through the system, highlighting how components create, communicate and consume information during envisioned system operation to deliver on the use cases' goals. Finally, the deployment view presents topological considerations in terms of defining the execution environment for the various system components at a later stage during the project lifetime. The contents of this deliverable are provided as a first version documentation of the envisioned system's shape and structure, and are expected to be updated upon completion of the architecture and system specification activities in M18 of the project lifetime

Additional file 1: of Extended-spectrum beta-lactamase − producing enterobacteriaceae in the intensive care unit: acquisition does not mean cross-transmission

Characterization of ESBL-E. (DOCX 92 kb