{"id":96832,"date":"2024-10-31T12:03:02","date_gmt":"2024-10-31T11:03:02","guid":{"rendered":"https:\/\/packaging-journal.de\/?p=96832"},"modified":"2024-10-31T12:03:02","modified_gmt":"2024-10-31T11:03:02","slug":"mosca-receives-award-for-ki-solution","status":"publish","type":"post","link":"https:\/\/packaging-journal.de\/en\/mosca-erhaelt-award-fuer-ki-loesung\/","title":{"rendered":"AI solution from Mosca honoured"},"content":{"rendered":"

Artificial intelligence optimises the order sequence in production - and employees work through it more efficiently. Mosca recently received the \u201eWinner\u201c award from the Baden-W\u00fcrttemberg Industry 4.0 Alliance for this AI solution. <\/strong>With the award-winning solution, factors such as set-up time and order priority can be taken into account, their optimum sequence calculated and displayed directly on the respective machine.\u00a0<\/strong><\/p>\n

Mosca GmbH in Waldbrunn processes its individual work orders particularly efficiently in production. The reason: The end-of-line expert uses an AI solution to optimise the sequence of the numerous orders<\/strong> and weighs up factors such as set-up time, delay and priority of the individual items against each other. The employees are shown this optimised sequence directly at their workstations, for example during bending, turning or laser cutting, and can process it efficiently. In this way, Mosca successfully reduces set-up and throughput times while increasing production productivity. For this, the company received the Industry 4.0 Baden-W\u00fcrttemberg Alliance award in the \u201eWinner\u201c category. The network initiated and supported by the Baden-W\u00fcrttemberg Ministry of Economic Affairs.<\/strong> supports industrial SMEs on their way to Industry 4.0.<\/p>\n

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\u201eWhen teaching the algorithm, we prioritised adherence to deadlines and shortening throughput times and trained the AI accordingly. Other important parameters were the occupancy of the workstations and the set-up times.\u201c<\/p>\n

Joachim Dencker<\/strong>, Plant Manager and Vice President Mosca Machinery & Equipment GmbH & Co. KG<\/p>\n<\/blockquote>\n

The status of the individual orders, for example as warehouse, assembly or spare parts orders, and the associated urgency are also part of the AI's calculation. Based on this, it determines the optimum sequence of work orders for the next two weeks<\/strong>. If the order situation is higher, this period can be adjusted so that the optimised order sequence is available more quickly.<\/p>

\"\"<\/a><\/div><\/div>\n

Solution successfully in use for a year<\/strong><\/h2>\n

Mosca made the first step towards this solution in the development together with the company One Thousand at a hackathon<\/strong> with Mosca employees. \u201eThis made the topic of AI directly tangible and the potential applications and the goal of an optimised production process visible,\u201c explains Joachim Dencker. The application has since become an integral part of Mosca's system landscape and in use for a year with 40 integrated workstations in production<\/strong> - where it also receives positive feedback from the workforce. The results are already visible: the AI solution further increases the delivery reliability of the machines manufactured by Mosca and minimises idle times for individual parts. Now Mosca optimises the AI algorithm with a training loop<\/strong>, The experts review what they have learnt, expand the parameters and integrate new tools into the solution.<\/p>\n

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\u201eFor us, automation and AI already offer an efficient solution to specific challenges. In particular, where a suitable data basis coincides with a corresponding potential for improvement, we can use AI to optimise or make things more efficient with significantly less effort than before.\u201c<\/p>\n

Gregor Karmowski<\/strong>, Group Vice President IT & Digitalisation<\/p>\n<\/blockquote>\n

The award from the Industry 4.0 Alliance reinforces Mosca's course: \u201eThe award confirms to the expert jury that we are on the right track with our solutions. into a future in which AI increasingly facilitates resource-efficient, digitalised production<\/strong>\u201c, summarises Karmowski. Accordingly, Mosca is already planning and testing several AI projects, for example for the automated creation of quotations.<\/p>\n

Source<\/em>: Mosca<\/a><\/p>","protected":false},"excerpt":{"rendered":"Artificial intelligence optimises the order sequence in production - and employees work through it more efficiently. Mosca recently received the \u201eWinner\u201c award from the Baden-W\u00fcrttemberg Industry 4.0 Alliance for this AI solution.","protected":false},"author":20,"featured_media":96833,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"__cvm_playback_settings":[],"__cvm_video_id":"","rank_math_description":"Mosca wurde von der Allianz Industrie 4.0 Baden-W\u00fcrttemberg f\u00fcr eine KI-L\u00f6sung zur Optimierung der Auftragsreihenfolge in der Produktion ausgezeichnet.\n","rank_math_focus_keyword":"KI-L\u00f6sung","rank_math_title":"","csco_display_header_overlay":false,"csco_singular_sidebar":"","csco_page_header_type":"","csco_page_load_nextpost":"","csco_post_video_location":[],"csco_post_video_location_hash":"","csco_post_video_url":"","csco_post_video_bg_start_time":0,"csco_post_video_bg_end_time":0,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[21],"tags":[43,58923,35,59],"class_list":{"0":"post-96832","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-verpackungstechnik","8":"tag-aus-den-unternehmen","9":"tag-mosca","10":"tag-praemiert","11":"tag-software-und-steuern","12":"cs-entry","13":"cs-video-wrap"},"acf":[],"vimeo_video":null,"_links":{"self":[{"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/posts\/96832","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/comments?post=96832"}],"version-history":[{"count":0,"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/posts\/96832\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/media\/96833"}],"wp:attachment":[{"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/media?parent=96832"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/categories?post=96832"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/packaging-journal.de\/en\/wp-json\/wp\/v2\/tags?post=96832"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}