Difference between revisions of "Project Descriptions"

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<td><font size="3" style="color:blue; font-weight: bold">Project structure</font></td></tr>
<td><font size="4" style="color:blue; font-weight: bold">Project structure</font></td></tr>

Latest revision as of 17:32, 24 March 2020

Project Objectives

In this section each participants Technical Objectives are represented in alignment with main project objec-tive. Some of partners are end-users where they will directly apply results on their current infrastructures:

  • TO-TR: SYM and INOSENS, as Turkish consortium, has been working on Industrial IoT Data Analyt-ics since 2014. The main Technical Objective of developing INGENISENSE concept is to create a end-to-end IoT Data Analytics platform. SYM and INOSENS will focus on data flow and analytics aspects of Industrial IoT systems. …)
  • INGENISENSE Industrial IoT Data Analytics platform will provide both batch and stream processing of data. Therefore, almost all kind of industrial sensor data could be processed on the platform.
  • Another goal is to provide a secure and reliable computing platform where data analytics could be done on cloud computing. This is crucial for SME adoption since data analytics infrastructures are costly to build and maintain.
  • TO-KR: KOREAN consortium has an expertise on IoT platform and Big data based MES (Manufac-turing Execution System) based smart factory. The major technical objective is to diagnose a failure of manufacturing equipment of electronic components in a mass production line located in different countries using IoT sensors through multiple sensor devices. The platform based on big data and ML/DL technology will enhance the capability of its diagnosis.
  • Further, this environment will predict the problematic situation in advance to optimize the well-defined manufacturing capability of MES based smart factory. The AI and big data based platform will support the capabilities to analyze all kinds of data from sensors in real time or historical infor-mation and takes actions of prediction, diagnosis, detection, report of any malfunction of equip-ment in globally dispersed factories.
  • In INGENISENSE project, data interoperability in syntactic and semantic framework will be dis-cussed and tried to resolve few issues. almost all kind of multiple industrial sensor data could be processed on our platform.
Added value of the co-operation

Partners Korean and Turkey consortium have large competence in the fields of smart factory environment development and systems integration. The consortium will provide access to complementary skilled part-ners like SYM and CBNU in the fields of big data, cloud platforms, security and machine learning which will allow all of us to gain experience in interfacing with these systems. This will prepare us better for our future customer demands.

  • Cooperation can provide national projects a new dimension, since these types of projects are a novel op-portunity to solve problems in an innovative way. Moreover, implementing a project with international part-ners from other markets may provide access to new business opportunities. Cooperation enables partners to take advantage of complementarities and to benefit from each other.
  • Thus, the cooperation within the consortium partners will enable the project to achieve a greater critical mass, since the total benefits are much greater than the sum of individual achievements (1+1=11). Pooling re-sources and expertise will result in economies of scale and synergies, which are favorable to help achieving project objectives (such as costs for technical equipment/technologies, training, marketing, etc.). Moreover, cooperation will provide access to new business opportunities, hence generating a potential for: increased product sales; a complementary business partner to improve a product or process; and additional know-how.
  • In technology point of view, since there is many different equipment, conditions, and environments in mass production lines of a factory, it is needed to take as many technical specialties as possible into account to implement the project objectives to the end-user companies. In the consortium are involved companies which have specialties in the technologies from manufacturing sensors, networking HW, potential end-users, to big data based SW platform, so that definite advantages of complementary work can be expected.
  • In the cooperation with potential end-user companies like Haechitech of Korean consortium or use-cases like DLIT the partners taking charge of HW preparation like KMU have to investigate where and how to install the project output, in which very specific technologies can be needed to cope with difficulties depending on the different conditions and environments. Partners taking charge of SW platform produce the expected output of project taking into account the whole circumstance and cooperation with all participants.
  • In marketing point of view, the cooperative work by partners from 5 countries can make definite advantage of finding demands and customers which are already diffused into the global area during the progress of project. The end-user companies in Europe and Asia which have been in cooperation with project partners will not only take benefits of project results but also play a role of marketing agents.

Project structure

The work in the INGENISENSE is divided in seven different SPs. The detailed relationship of inputs and outputs of the SPs is shown in the following Figure