Smart manufacturing - iSLM the 'smart' data management platform
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In the era of Industry 4.0, where nowadays more and more data is available and the flow of information has not only increased accordingly, but also speed up through the organizations, the companies strive for the integration of all their data and the tools used their product development. iSLM gives a very clear answer to this challenge. iSLM is a central platform that provides the data in a structured database and unifies all stake holders along the entire development and production of injection molded parts and tools.
In the traditional enterprise structure, data is managed differently by different teams, departments and individuals. However, this data has different revisions when it is stored in different places, leading to inconsistencies in a company's internal data. Moreover, since such data is difficult to share, it leads to problems in a continuous product development and resolving known development issues. The divergent data can also be a major obstacle on the journey to the digital twin. Therefore, it is a critical issue to manage well-organized & visualized information and make it available to everyone with the required rights and duties.
iSLM solves exactly this situation with its network-based collaboration platform for data, information and task management along the entire injection molding process. It is fully configurable and can be customized according to the process of the organization and project teams. It can start from the creation of an injection molded part concept or focus only on the mold development and mold try out sub-process.
iSLM Solution Management is available for solution administration during development. All possible part-, mold-related data or reports are immediately available in the system and are efficiently used at any time according to their purpose within the concerned teams. Design for Manufacturing (DFM) reports created in the system for adjustments or optimizations of the designs are jointly edited and documented on the basis of the current simulation reports. Furthermore, with the help of the module, users are able to upload the Moldex3D projects and use them as a primary data simulation system. The simulation data and results can be displayed in the system by any concerned colleague, which saves time of file transfer, reduces conflict situations and creates a performant communication workflow.
Another module is the Mold Try-Out Management. This module is mainly tailored to the mold try outs in the production and the interaction with the development & quality department. All possible data can be entered live and on-site during production using a mobile device. It includes a link to the Moldex3D simulation results and task distribution. Thus, process parameters, test data and product defects can be uploaded and compared with the corresponding simulation results and provided for next step. Users can perform online comparisons of flow front and short shots, for example, and the system generates respective comparison reports. Team members of the quality control department can use the module to generate or upload product quality inspection data and reports created by the system. The required inspection plans with the corresponding criteria can be configured appropriately.
Finally, the Knowledge Management module is available for searching and comparing older solutions. The classified historical solutions can be searched using filters. This data can be visualized by statistical diagrams or list items. Not only virtual CAE data can be compared, but also the mold try out data. Thus, iSLM becomes the perfect knowledge management system for the projects in the organization.
iSLM can configure with the help of the content management module the data, process and task management structures adapted to the needs of the organization. Furthermore, different roles with appropriate rights to the data can be set and connected to your email system.
Through the iSLM platform, companies can manage all relevant data for the part and/or tool development process more efficiently and integrate the data from DFM, CAE and mold testing. As a result, the rapidly collected data can then help to achieve the digital integration of the virtual and digital twin. In addition, the visualized data can enable better workflow and thus more efficient teamwork. In future, the Big Data collected in iSLM can be used even more effectively through machine learning and deep learning cloud systems.
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