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The injection molding process yields many possibilities to create innovative plastic part solutions. Based on extensive research in distinct subject areas and the cross-disciplinary interconnection between different academic disciplines lately an interesting new approach for the efficient and effective attainment of flame retardancy could be identified: Multi component injection molding, where two or more plastic melts are injected next to or within each other during one cycle, can be used to produce innovative flame retardant plastic parts. These parts have an optimized skin/core structure with the core part consisting of the pristine polymer while the flame retardant polymer system is located in the skin. Such a structure proves to be ideal, because it allows for a faster protection dynamic.This broadening of the field of application of standard injection molding machines is made possible by the use of intermediate plates with individually suitable modular technological inserts. The modular inserts required for this kind of application comprise hot runners including shut off and control functions to separate and join melt flows from different injection units into one cavity. These modules make for the combination of the sequential and simultaneous injection of melts. In that account first trials which prove the concept to be viable have been conducted. Promising results will be shown as well as the principles of laboratory and industrial scale implementation of the underlying production process, while further research still is ongoing. In conclusion the paper will point out the advantages, possibilities and application potential given by this new approach. Cost savings will be given by the supersession of costly special machinery as well as achieved material savings and increased part quality and process stability.

Data-driven methods based on artificial intelligence (AI) are powerful yet flexible tools for gathering knowledge and automating complex tasks in many areas of science and practice. Despite the rapid development of the field, the existing potential of AI methods to solve recent industrial, corporate and social challenges has not yet been fully exploited. Research shows the insufficient practicality of AI in domain-specific contexts as one of the main application hurdles. Focusing on industrial demands, this publication introduces a new paradigm in terms of applicability of AI methods, called Usable AI (UAI). Aspects of easily accessible, domain-specific AI methods are derived, which address essential user-oriented AI services within the UAI paradigm: usability, suitability, integrability and interoperability. The relevance of UAI is clarified by describing challenges, hurdles and peculiarities of AI applications in the production area, whereby the following user roles have been abstracted: developers of cyber–physical production systems (CPPS), developers of processes and operators of processes. The analysis shows that target artifacts, motivation, knowledge horizon and challenges differ for the user roles. Therefore, UAI shall enable domain- and user-role-specific adaptation of affordances accompanied by adaptive support of vertical and horizontal integration across the domains and user roles.

Production of plastics parts with partially or fully metallic surfaces using the in-mould-metal-spraying ( Development of a highly segmented temperature control in injection moulding for reduced warpage and increased process stability

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