{"id":93395,"date":"2018-12-15T12:00:00","date_gmt":"2018-12-15T12:00:00","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&#038;p=93395"},"modified":"2024-04-16T16:15:55","modified_gmt":"2024-04-16T14:15:55","slug":"the-appropriate-degree-of-autonomy-in-cyber-physical-production-systems","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/the-appropriate-degree-of-autonomy-in-cyber-physical-production-systems\/","title":{"rendered":"The Appropriate Degree of Autonomy in Cyber-Physical Production Systems"},"content":{"rendered":"<hr>\n<div class=\"gito-pub-content-bibliography\">\n<h2>Bibliography <\/h2>\n[1] ten Hompel, M.; Liekenbrock, D.: Autonome Objekte und selbst organisierende Systeme. Anwendung neuer Steuerungsmethoden in der Intralogistik. In: Industrie Management 21 (2005) 4, S. 15-18.<br \/>\n[2] Veigt, M.: Entwicklung eines Cyber-Physischen LogistiksystemS. In: Industrie Management 29 (2013) 1, S. 15-18.<br \/>\n[3] Gronau, N.: Der Einfluss von Cyber-Physical Systems auf die Gestaltung von Produktionssystemen, Industrie Management 31 (2015) 3, S. 16-20.<br \/>\n[4] acatech (ed.): Cyber-Physische Systeme. Innovationsmotor f\u00fcr Mobilit\u00e4t, Gesundheit, Energie und Produktion (acatech POSITION). Heidelberg 2011.<br \/>\n[5] Gronau, N.: Wandlungsf\u00e4higkeit in Produktion und Logistik, Productivity Management 2 (2014), S. 23-26.<br \/>\n[6] Gronau, N.; Theuer, H.: Determination of the optimal degree of autonomy in a cyber-physical production system. Procedia CIRP 57 (2016), S. 110-115<br \/>\n[7] Gronau, N.: Determinants of an Appropriate Degree of Autonomy in a Cyber-physical Production System. Procedia CIRP 52 (2016), S. 1-5.<br \/>\n[8] Luck, M.; d\u2019Inverno, M.: A Formal Framework for Agency and Autonomy. In: Procs First International Conference on Multi-Agent Systems. AAAI 1995.<br \/>\n[9] van der Vecht, B.: A Dynamic Coordination Mechanism Using Adjustable Autonomy. In: Sichman, J.; Noriega, P.; Padget, J.; Ossowski, S. (Hrsg): International Workshops on Coordination, Organizations, Institutions, and Norms in Agent Systems III, COIN 2007: &#67;&#79;&#73;&#78;&#64;&#65;&#65;&#77;&#65;&#83; 2007 and &#67;&#79;&#73;&#78;&#64;&#77;&#65;&#76;&#76;&#79;&#87; 2007, 3-4 September 2007, Durham., S. 83-96.<br \/>\n[10] Windt, K.: Autonomy in production logistics: Identification, characterization and application. Robot Comput Integr Manuf (2007), doi:10.1016\/j.rcim.2007.07.008.<br \/>\n[11] Gronau, N.; Theuer, H.: Industrie 4.0 in Europa \u2013 Ein Vergleich Europ\u00e4ischer Initiativen In: Industrie Management 5 (2015), S. 31-34.<br \/>\n[12] H\u00fclsmann, M.; Windt, K.: Understanding Autonomous Cooperation and Control in LogisticS. Berlin Heidelberg 2007.<br \/>\n[13] Scholz-Reiter, B., G\u00f6rges, M., &amp; Philipp, T. (2009). Autonomously controlled production systems \u2014 Influence of autonomous control level on logistic performance. CIRP annals 58.1 (2009): 395-398.<br \/>\n[14] Dashkovskiy et al. 2011: Modeling and stability analysis of autonomously controlled production networks. In: Logist. Res. (2011) 3:145\u2013157 DOI 10.1007\/s12159-011-0049-6<br \/>\n[15] Windt K, et al. Autonomy in production logistics: Identification, characterisation and application. Robot Comput Integr Manuf (2007), doi:10.1016\/j.rcim.2007.07.008<br \/>\n[16] Armbruster, D., et al. \u201cAutonomous control of production networks using a pheromone approach.\u201d Physica A: Statistical Mechanics and its applications 363.1 (2006): 104-114.<br \/>\n[17] Karimi, Hamid Reza, Neil A. Duffie, and Sergey Dashkovskiy. \u201cLocal Capacity H\u221eControl for Production Networks of Autonomous Work Systems With Time-Varying Delays.\u201d IEEE Transactions on Automation Science and Engineering 7.4 (2010): 849-857.<br \/>\n[18] Caridi, M. &amp; Cavalieri, S. (2004) Multi-agent systems in production planning and control: an overview, Production Planning and Control, 15:2, 106-118, DOI: 10.1080\/09537280410001662556<br \/>\n[19] Theuer, H.; Gronau, N.; Lass, S.: The Impact of Autonomy on Lean Manufacturing SystemS. In: Proceedings of the 23rd International Conference on Flexible &amp; Intelligent Manufacturing (FAIM 2013). Porto 2013.<br \/>\n[20] Rother, M.; Shook, J.: Learning to See: Value Stream Mapping to Add Value and Eliminate MUDA. Lean Enterprise Institute Cambridge 1999.<br \/>\n[21] Gronau, N.; Grum, M.; Bender, B.: Determining the optimal level of autonomy in cyber-physical production systemS. Industrial Informatics (INDIN), 2016 IEEE 14th International Conference on. IEEE 2016.<br \/>\n[22] Lass, S.; Theuer, H.; Gronau, N.: A New Approach for Simulation and Modeling of Autonomous Production ProcesseS. In: Proceedings of the 45th Hawaii International Conference on System Sciences (HICSS 2012). Maui, Hawaii 2012.<br \/>\n[23] Gronau, N.; Theuer, H.; Lass, S.: Evaluation of Production Processes using Hybrid Simulation. In: Windt, K. (Hrsg): Robust Manufacturing Control, Lecture Notes in Production Engineering. Berlin Heidelberg 2013.<br \/>\n[24] Lass, S.: Simulationskonzept zur Nutzenvalidierung cyber-physischer Systeme in komplexen Fabrikumgebungen. PhD thesis Potsdam University 2017.<\/div>\n<div id=\"download-section\" class=\"gito-pub-download-section\" style=\"text-align:center;margin:20px;\">\n<h2>Your downloads<\/h2>\n<p><button style=\"font-size:14px;margin-right:15px;\" class=\"button gito-pub-cpt-download-button\" data-postid=\"93395\" data-userid =\"0\" data-filename=\"gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6.pdf\"><span style=\"margin-top:5px !important;\" class=\"dashicons dashicons-download\"><\/span>&nbsp;&nbsp;PDF<\/button><\/div>\n<div class=\"gito-pub-tags-social-share\" style=\"display:flex;justify-content:space-between;\"><div>Tags: <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/simulation-en\/\">Simulation<\/a><\/span> <\/div><div><div class=\"social-icons share-icons share-row relative\" ><a href=\"whatsapp:\/\/send?text=The%20Appropriate%20Degree%20of%20Autonomy%20in%20Cyber-Physical%20Production%20Systems - https:\/\/industry-science.com\/en\/articles\/the-appropriate-degree-of-autonomy-in-cyber-physical-production-systems\/\" data-action=\"share\/whatsapp\/share\" class=\"icon button circle is-outline tooltip whatsapp show-for-medium\" title=\"Share on WhatsApp\" aria-label=\"Share on WhatsApp\"><i class=\"icon-whatsapp\" aria-hidden=\"true\"><\/i><\/a><a href=\"https:\/\/www.facebook.com\/sharer.php?u=https:\/\/industry-science.com\/en\/articles\/the-appropriate-degree-of-autonomy-in-cyber-physical-production-systems\/\" data-label=\"Facebook\" onclick=\"window.open(this.href,this.title,'width=500,height=500,top=300px,left=300px'); 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return false;\" target=\"_blank\" class=\"icon button circle is-outline tooltip linkedin\" title=\"Share on LinkedIn\" aria-label=\"Share on LinkedIn\" rel=\"noopener nofollow\"><i class=\"icon-linkedin\" aria-hidden=\"true\"><\/i><\/a><\/div><\/div><\/div><hr style=\"margin-top:0px;\">\n<h2 class=\"gito-pub-frontend-post-headline\">You might also be interested in<\/h2>\n<!-- GITO_PUB_POST start flex-container -->\n<div class=\"gito-pub-flex-container\">\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/automotive-body-manufacturing\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/09\/richter_AdobeStock_1887518115_Andrey-Popov-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/09\/richter_AdobeStock_1887518115_Andrey-Popov-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/09\/richter_AdobeStock_1887518115_Andrey-Popov-196x180.webp\" alt=\"Interoperable Data Access in Automotive Body Manufacturing\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Interoperable Data Access in Automotive Body Manufacturing\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Interoperable Data Access in Automotive Body Manufacturing<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Deterministic integration of structured target parameters into tact-time production<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/tim-richter\/\">Tim Richter<\/a> <a href=\"https:\/\/orcid.org\/0009-0007-9110-0187\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/robert-weidner\/\">Robert Weidner<\/a> <a href=\"https:\/\/orcid.org\/0000-0002-1449-3796\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     AI has long been capable of analyzing production processes, yet why is it still so difficult to bring its insights back into production without intermediate steps? In automotive body-in-white mass production, the challenge is less a lack of data than the absence of holistic integration concepts that extend all the way to the machines. This paper demonstrates why bidirectionally communicative information systems are critical to addressing this challenge and identifies the design principles required to effectively integrate AI-generated results into production processes in the future.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 34-42 | DOI <a style=\"font-weight:bold !important;\" href=\"https:\/\/doi.org\/10.30844\/I4SE.26.5.4\" target=\"_blank\" rel=\"noopener\">10.30844\/I4SE.26.5.4<\/a><\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/continuing-vocational-education\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/09\/beichter_AdobeStock_1885327612_master1305-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/09\/beichter_AdobeStock_1885327612_master1305-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/09\/beichter_AdobeStock_1885327612_master1305-196x180.webp\" alt=\"Audio-Immersive Learning in Continuing Vocational Education\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Audio-Immersive Learning in Continuing Vocational Education\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Audio-Immersive Learning in Continuing Vocational Education<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">From linear audio playback to AI-supported conversational learning companions<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/tim-beichter\/\">Tim Beichter<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/vanessa-hartmann\/\">Vanessa Hartmann<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/katharina-hoelzle\/\">Katharina H\u00f6lzle<\/a> <a href=\"https:\/\/orcid.org\/0000-0002-9733-4650\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/manuel-kaiser\/\">Manuel Kaiser<\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     Artificial intelligence is increasingly shaping continuing vocational education and training by enabling the personalization of individual learning experiences. At the same time, audio-based learning formats are attracting growing interest among learners because of their flexibility and suitability for workplace learning. However, a conceptual framework for AI-supported audio learning, as well as the potential of combining artificial intelligence with audio-based learning, has received little attention to date. This paper therefore presents a conceptual perspective on the design possibilities and educational potential of AI-supported audio learning formats.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 102-108 | DOI <a style=\"font-weight:bold !important;\" href=\"https:\/\/doi.org\/10.30844\/I4SE.26.5.12\" target=\"_blank\" rel=\"noopener\">10.30844\/I4SE.26.5.12<\/a><\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/ai-demonstrators-manufacturing\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/link_AdobeStock_311608924_Gorodenkoff-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/link_AdobeStock_311608924_Gorodenkoff-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/link_AdobeStock_311608924_Gorodenkoff-196x180.webp\" alt=\"Explaining AI in Industrial Production in an Accessible Way\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Explaining AI in Industrial Production in an Accessible Way\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Explaining AI in Industrial Production in an Accessible Way<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Requirements for AI demonstrators to promote acceptance<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/jennifer-link-en\/\">Jennifer Link<\/a> <a href=\"https:\/\/orcid.org\/0009-0005-2407-3495\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/markus-harlacher-en\/\">Markus Harlacher<\/a> <a href=\"https:\/\/orcid.org\/0009-0007-5817-2920\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/colin-srebny\/\">Colin Srebny<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/sascha-stowasser-en\/\">Sascha Stowasser<\/a> <a href=\"https:\/\/orcid.org\/0009-0006-2725-5793\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     Artificial intelligence (AI) offers a wide range of possibilities in industrial production, but it also presents challenges regarding employee acceptance. AI demonstrators are therefore of central importance, as they enable hands-on experience with AI. However, there has been a lack of systematically identified requirements for demonstrators that specifically promote acceptance and address negative emotions. Using a multi-stage research design, 69 requirements were identified, structured into functional requirements, quality requirements, and boundary conditions.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 6-14 | DOI <a style=\"font-weight:bold !important;\" href=\"https:\/\/doi.org\/10.30844\/I4SE.26.5.1\" target=\"_blank\" rel=\"noopener\">10.30844\/I4SE.26.5.1<\/a><\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/ai-based-building-inspection\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/sender_AdobeStock_227079093_Aisyaqilumar-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/sender_AdobeStock_227079093_Aisyaqilumar-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/sender_AdobeStock_227079093_Aisyaqilumar-196x180.webp\" alt=\"AI-Based Building Inspection for Large Structures\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"AI-Based Building Inspection for Large Structures\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">AI-Based Building Inspection for Large Structures<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">A new approach to construction progress monitoring<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/jan-sender-en\/\">Jan Sender<\/a> <a href=\"https:\/\/orcid.org\/0009-0003-9697-5709\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/konrad-jagusch-en\/\">Konrad Jagusch<\/a> <a href=\"https:\/\/orcid.org\/0009-0001-7454-1657\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/michael-geist\/\">Michael Geist<\/a> <a href=\"https:\/\/orcid.org\/0009-0005-2780-7538\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/david-jericho\/\">David Jericho<\/a> <a href=\"https:\/\/orcid.org\/0009-0001-8932-8701\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/christian-scharr\/\">Christian Scharr<\/a> <a href=\"https:\/\/orcid.org\/0009-0003-6300-4682\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     Monitoring construction progress, as required in the one-off production of large structures, is very time- and labor-intensive due to a high level of complexity and individuality. The goal of this article is to develop a sensor-based approach for capturing and evaluating multiple inspection characteristics. The use of machine learning models to detect objects and derive relevant information forms the basis for linking current condition to construction schedule. This enables a significant increase in efficiency during construction progress monitoring and a well-founded assessment of progress.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 78-84 | DOI <a style=\"font-weight:bold !important;\" href=\"https:\/\/doi.org\/10.30844\/I4SE.26.5.9\" target=\"_blank\" rel=\"noopener\">10.30844\/I4SE.26.5.9<\/a><\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/inclusive-work-system-design\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/schlund_AdobeStock_2046886237_InfiniteFlow-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/schlund_AdobeStock_2046886237_InfiniteFlow-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/schlund_AdobeStock_2046886237_InfiniteFlow-196x180.webp\" alt=\"Inclusive Work System Design\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Inclusive Work System Design\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Inclusive Work System Design<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Automation, standardization, and adaptability<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/sebastian-schlund-en\/\">Sebastian Schlund<\/a> <a href=\"https:\/\/orcid.org\/0000-0002-8142-0255\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     The design of inclusive work systems is gaining importance due to demographic change and the increasing digital penetration of value creation processes. While traditional ergonomic approaches are based primarily on percentile logic and thus address only a portion of the user population, the integration of digital technologies opens up new possibilities for the dynamic and individualized adaptation of work systems. This article presents a conceptual framework for inclusive work system design that integrates standardization, automation, and adaptability. Methodologically, the article is based on a conceptual analysis of existing approaches from ergonomics and human-centered design. The article makes a theoretical contribution to the systematization of inclusive work system design and identifies areas of focus for further research and industrial practice.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 70-76 | DOI <a style=\"font-weight:bold !important;\" href=\"https:\/\/doi.org\/10.30844\/I4SE.26.5.8\" target=\"_blank\" rel=\"noopener\">10.30844\/I4SE.26.5.8<\/a><\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/work-design-autonomous-systems\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/AdobeStock_484184873_Ivan-Traimak-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/AdobeStock_484184873_Ivan-Traimak-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/08\/AdobeStock_484184873_Ivan-Traimak-196x180.webp\" alt=\"Work Design in the Use of Autonomous Systems\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Work Design in the Use of Autonomous Systems\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Work Design in the Use of Autonomous Systems<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Addressing the shortage of skilled workers<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/tim-jeske-en\/\">Tim Jeske<\/a> <a href=\"https:\/\/orcid.org\/0000-0001-8778-6824\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/sascha-stowasser-en\/\">Sascha Stowasser<\/a> <a href=\"https:\/\/orcid.org\/0009-0006-2725-5793\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/nicole-ottersboeck-en\/\">Nicole Ottersb\u00f6ck<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/sebastian-terstegen-en\/\">Sebastian Terstegen<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/rasmus-adler\/\">Rasmus Adler<\/a> <a href=\"https:\/\/orcid.org\/0000-0002-7482-7102\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     Companies are increasingly challenged to address shortages of skilled workers while meeting rising demands for productivity, flexibility, and innovation. Because labor supply can only be expanded to a limited extent, there is a growing focus on designing work systems with productivity in mind. Autonomous systems offer significant potential in this regard. Their implementation requires not only technical adjustments but, above all, changes in organization, skills, and work design. This article analyzes empirically grounded change requirements in existing work systems as well as associated economic potential.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 5 | Pages 44-50 | DOI <a style=\"font-weight:bold !important;\" href=\"https:\/\/doi.org\/10.30844\/I4SE.26.5.5\" target=\"_blank\" rel=\"noopener\">10.30844\/I4SE.26.5.5<\/a><\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n<\/div>\n<!-- GITO_PUB_POST end flex-container -->\n","protected":false},"excerpt":{"rendered":"<p>Existing factories face multiple problems due to their hierarchical structure of decision making and control. Cyber-physical systems principally allow to increase the degree of autonomy to new heights. But which degree of autonomy is really useful and beneficiary? This paper differentiates diverse definitions of autonomy and approaches to determine them. Some experimental findings in a lab environment help to answer the question raised in this paper.<\/p>\n","protected":false},"featured_media":96619,"menu_order":0,"template":"","categories":[79167,79168,79298],"tags":[80214],"product_cat":[],"topic":[67617,67701],"technology":[67717],"knowhow":[],"industry":[],"writer":[80397],"content-type":[],"potential":[],"solution":[],"glossary":[],"class_list":["post-93395","article","type-article","status-publish","has-post-thumbnail","category-design-en","category-translate-en","category-typeset","tag-simulation-en","topic-adaptability","topic-production-system","technology-simulation-en","writer-norbert-gronau-en","product","first","instock","downloadable","virtual","sold-individually","taxable","purchasable","product-type-article"],"uagb_featured_image_src":{"full":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788.jpg",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-150x150.jpg",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-666x375.jpg",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-768x432.jpg",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-1024x576.jpg",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-1032x320.jpg",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-764x376.jpg",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-392x320.jpg",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-608x496.jpg",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-640x325.jpg",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-274x376.jpg",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-514x292.jpg",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-320x440.jpg",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-514x289.jpg",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-196x180.jpg",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788.jpg",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788.jpg",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-510x510.jpg",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-510x287.jpg",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemessene-Grad-von-Autonomie-in-Cyber-Physischen-Produktionssystemen_IM-2018-6-1400x788-100x100.jpg",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2024\/03\/gronau_Der-angemess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Brocks","author_link":"https:\/\/industry-science.com\/en\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Existing factories face multiple problems due to their hierarchical structure of decision making and control. Cyber-physical systems principally allow to increase the degree of autonomy to new heights. But which degree of autonomy is really useful and beneficiary? This paper differentiates diverse definitions of autonomy and approaches to determine them. Some experimental findings in a&hellip;","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/93395","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/types\/article"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media\/96619"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=93395"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=93395"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=93395"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=93395"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=93395"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=93395"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=93395"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=93395"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=93395"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=93395"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=93395"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=93395"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=93395"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}