2021 · 16 citations · 28 references
Artificial IntelligenceEngineeringIndustrial EngineeringDigital ManufacturingSoftware EngineeringManufacturing Systems EngineeringBusiness Process ModelingIntelligent SystemsAutomated ManufacturingInformation ModelSystems EngineeringEnterprise ModellingIndustry 4.0Industry 5.0Industrial InformaticsExpressive PowerDesignManufacturing SystemsComputer ScienceInformation ManagementDomain-specific LanguageSoftware DesignIndustrial DesignAutomationSpecial Session 1Industrial Artificial IntelligenceIndustrial AutomationHuman-computer InteractionTechnologyDomain-specific Modeling
The Industry 4.0 trend speeds up the adoption of a variety of technologies. In modern manufacturing, system data are collected both from the field through sensors and by exploiting complex simulations. Data analysis techniques became crucial to build and maintain any efficient production line, while autonomous systems and robots are the main focus of researchers and practitioners. This pervasive use of artificial intelligence derived technologies pushed humans to the border of production systems. Industry 5.0 aims at bringing the attention back to humans in production lines while magnifying their interactions with intelligent systems. This new trend will impact the design of future manufacturing infrastructures, increasing their complexity. Engineers will need modeling and developing tools able to capture this complexity. In this paper, we analyze the modeling languages and tools being used, identifying their strengths and weaknesses. Then, we propose some possible directions to provide engineers with the expressive power needed to tackle the challenges posed by Industry 5.0.
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