Requirements to describe and analyse Sample Clauses

Requirements to describe and analyse. Better monitoring of critical systems and parameters enables to in advance be able to detect and predict failures avoiding interruptions and damages. Parameters to monitor are for instance effect distributions of system parameters over time (pressure, temperature, rpm, leakage flow, vibrations etc.). After identification of critical parameters, the system will be analyzed and modeled to improve system availability. As an example, an increase in oil temperature in the motor casing or an increase in the loop temperature at the low pressure side port versus high pressure port will indicate an imminent failure. The temperature difference between inlet and outlet oil are at each timestamp initially calculated and evaluated against a predetermined set-point. Whenever the set-point value is exceeded the DSMS will by a sliding window evaluate the slope of the failure sequence and determine if the slope is acceptable or not. First, the slope are determined and set through engineering judgment, once the algorithm within the DSMS is trained with previous monitored fault data and online data the algorithm will improve. Suggested sensors for failure identification can be viewed in the confidential document D1.2A, recommended placements of sensors in the simplified hydraulic scheme in the following picture 12.
Sample 1
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Requirements to describe and analyse. Better monitoring of critical systems and parameters to in advance be able to detect and predict failures avoiding interruptions and damages. Parameters to monitor are for instance effect distributions of system parameters over time (pressure, temperature, rpm, leakage flow, vibrations etc.). After identification of critical parameters, the system will be analyzed and modeled to improve system availability.
Sample 1
Requirements to describe and analyse. How to find unmet customer needs, optimize utilization of products/services How to re-link the product data stream feedback from the market/customers with company ideation and development processes to:  identify consumer needs  monitor the customer‟s key performance indexes regarding the level of capability to utilize the introduced services and product solutions  suggest possible improvements for the customer‟s process and facilitate improvement of the customer‟s process  capture new needs for product upgrading or totally new innovations  quality assure simulation models and optimization methods used in product and service development (needs to be quantified)
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Requirements to describe and analyse. In the project the Use CareTrack and Matris systems is used for demonstrative purposes holding data of every heavy production machine. The data monitored are: performance data, position, service information, and real-time use data from on-board sensors via telematics systems. (Further development of Volvo CE‟s back office systems, to be able to handle all information contributed from the project, will be managed outside of the project. The back office systems will help interpret the results and offer support decision making based on the gathered information).
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Requirements to describe and analyse. To achieve better collaboration and decision making in SmartVortex, we need  to identify and analyze collaboration tools the industry partners generally use in the product lifecycle (see section 3.2.4);  to identify and analyze collaboration activities the industry partners generally use in the product lifecycle;  to identify and analyze data and information the industry partners need for collaboration and decision making;  to identify and analyze rule and policies the industry partners generally use for the exchange of data in a cross-organizational environment;  to identify and analyze rules and policies the industry partners generally use for group formation. As a result out of this analysis we need to define a formal description for a collaboration that can be used to design and adapt a collaboration process;  to define a formal description for relevant information about the employees that can be used for group formation;  to define rules for the use of data out of the data streams for a collaboration process;  to define rules for the adaptation of a collaboration process;  to define rules and policies for group formation;  to define rules and policies for the for the exchange of data in a cross-organizational environment; The collaboration data stream consisting of data generated in collaboration and decision making processes. There are different kinds of data that can be generated out of such interaction, such as: the design decisions of a product that a group takes, documents generated about design decisions and records from group meetings. As collaboration data streams can easily become complex due to a high amount of data around a product, we adapt the data stream computation schema (shown in 4.2.2) to process the collaboration data stream and to filter relevant information that is presented to stakeholders. The framework is not constraint to process only data based on documents, models of decisions, generated by the collaboration among stakeholders. Another goal is to detect the behavior of stakeholders, whenever a collaborative session takes place. This information is particularly important for intelligent applications that are supposed to guide stakeholders during collaborative sessions for achieving effective results. This way, the applications may use the collaboration data stream to analyzing collaboration and project performance according to metrics, such as, commitment, quality, impact, shared understanding, progress and quality ...
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