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684 West College St. Sun City, United States America, 064781.

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info@corpkit.com

UC2: SEW USOCOME

This pilot will materialize the concepts of modularity and re-configurability by developing flexible production lines enabled by the capacity to simulate and optimize operations, while incorporating production module self-awareness capabilities, predictive maintenance needs as well as the human factor which is very crucial in the corresponding setting due to extremely increased customer needs for production customization (i.e., single lot production). In order to guarantee a very short delivery time regardless of the customization ordered, there is a need to assess the convertibility of processes, and accordingly to re-design and implement a new modular production setting that enables smooth execution of standard and specific modularized operations with respect to the WIP inventory. The new production setting will enable flexible reconfiguration of each one of the process steps as well as of the process as a whole. In particular, line balancing and reconfiguration, automatic line set up, personnel allocation, and real-time routing of products through the intralogistics system are of major interest. The pilot targets the production of a specific type of gear motors including 7 process steps, currently produced via monolithic production lines. Hence, there is the need for supporting re-design and re-configuration decisions through simulation. Then, after the development of the new modular production scheme, there is the need of supporting its operation via optimized production scheduling that enables line balancing, while also incorporating predictive maintenance needs, as well as production re-scheduling and production routing between the different production modules to alleviate the effects of machine failure (actual or predicted via self-awareness capabilities) and to increase the stability of the flow rate in the assembly lines.

The Pilot project will compare the performance between identic modules to analyze the local parameters with the production results and will propose optimization concerning this analyses