<![CDATA[Optimization techniques are one of the important materials that need to be understood well by Industrial Engineering students at all levels. One form of development of optimization techniques is manifested in scheduling machines on the production floor in the real industrial world, which of course requires more advanced methods than those generally studied in class. Student literacy regarding advanced optimization techniques needs to continue to be sharpened, especially at the master's level. This community service (PkM) activity aims to share knowledge with master students majoring in Industrial Engineering at Mapua University, Philippines regarding advanced optimization engineering material by highlighting real case studies. The method applied in this activity is in the form of a lecture via web seminar (webinar) via Zoom, followed by discussion and questions and answers. At the end of the session, participants were asked to provide feedback regarding the continuity of the seminar, which would then be analyzed and used as material for future improvements. The dissemination of material related to intelligent production scheduling in an all-digital industrial environment took place smoothly, demonstrated through active participation and interactive questions and answers. In the satisfaction survey, some information was obtained regarding the suitability of the theme to the participants' needs regarding the lectures taken, the accuracy of seminar time management, the mastery of the presenter in the discussion presented, and the suitability of the material to the participants' needs. From the analysis carried out, it was discovered that the theme raised was following the needs of the participants, and the timing of the seminar was also appropriate. Apart from that, it is also known that there has been an increase in webinar participants' knowledge regarding the topics raised. Professional development seminars have shown a positive impact on the development of participant's abilities and knowledge, especially those related to exposure to scheduling and production optimization.]]>
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