Development of the framework of data quality management for vitalization of iot products - a case of gas turbines

If smart, connected products (scps) produce, and exchange data with inadequate levels of quality , then organization can fail to achieve their business goals. Dqiot project will supply organizations with results to efficiently manage the data quality in scp operations.

It is the time of Internet of Things (IoT), and day by day more and more organizations are relying on the growing capabilities of physical devices, vehicles, buildings and some other items embedded with electronics, software, sensors, actuators to collect and exchange data. All this products embodying the concept of IoT are called Smart, Connected Products (SCP). SCPs are to support specific operations in different context like smart manufacturing, smart cities, smart driving, smart e-health, and so on. SCP operations might fail if generated and exchanged data has not adequate levels of quality(DQ). If this happens, organizations will not take advantage of the IoT from the use of SCP. Therefore, DQ Management (DQM) is required to improve the utilization of SCP operations. Consequently, the utilization rate of the SCP product may be lowered due to various reasons, such as malfunction, maintenance delay, data error, and so on. It is often the case that the operation is interrupted or the function is not performed due to low data quality (or data errors).Typical examples of these data errors are: 1) Bad data due to sensor malfunction or noise 2) Data nonconformity problem caused by change management failure 3) Repeated occurrence of the same data error 4) Data inconsistency between product cloud and business system in SCP environment Therefore, in order to avoid such data errors, and to prevent the waste of money from the low utilization rate, we propose the DQIoT project which could generate some results to alleviate or at least to minimize the impact of such data errors on business. The objective of the DQIoT project is to develop a data quality management framework that vitalize the operation of SCP products based on the ISO 8000-60 series, i.e., data quality management process assessment model. In this project, discrete manufacturing products are taken into account as target SCP products. In order to achieve this objective, we will develop: 1) a DQM assessment model to improve DQ when operating SCP products 2) core functions required for DQM as part of a software platform for monitoring and control The following will be within the scope of the project 1) Define SCP operation processes: Identify operating environments, and the type and causes of data errors that occur during SCP operations. Define the best practices for SCP operations that causes data errors. 2) Develop reference processes and corresponding maturity model 3) Develop algorithms for sensor data analysis, diagnosis, and improvement 4) Develop indicators used to measure process capability 5) Develop the software platform for DQM including data analysis, diagnosis, and improvement 6) Apply and complement the framework and platform on site To face up with this list of goals, we have brought together into a strong consortium of four active partners (from Korea and Spain) with a solid background and expertise in the field of data quality management, big data analytics, software development and SCP operations: - GTONE, with a deep knowledge in software development of data governance tools. - Myongji University, with a long time experience in standardization of DQM Processes-currently leading development of ISO 8000-61. - IE, with a deep knowledge in the assessment (audit certification) and improvement of Software Processes. IE will subcontract UCLM that has a long time experience in standardization of DQM Processes-currently leading development of ISO 8000-62. - Lucentia Lab, with large expertise in development of assessment indicator for monitoring, and big data analytics and tool development. A case of gas turbines will be benchmarked to develop the data quality management framework and platform for SCP operations.
Project ID: 
11 737
Start date: 
Project Duration: 
Project costs: 
1 720 000.00€
Technological Area: 
Market Area: 
Data processing, analysis and input services

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