ai and learning systems – industrial applications and future directions
Under de senaste åren har intresset för industriella tillämpningar av AI och inlärningssystem ökat. Boken AI and Learning Systems täcker den senaste utvecklingen och ger ett brett perspektiv på de viktigaste utmaningarna som kännetecknar området Industri 4.0 med fokus på tillämpningar av AI.
Målgruppen för den här boken inkluderar ingenjörer som är involverade i automationssystemdesign, operativ planering och beslutsstöd. Datavetenskapliga utövare och utvecklare av industriell automatiseringsplattform kommer också att dra nytta av den aktuella och korrekta informationen i detta arbete.
Bokens författare skapar tillsammans en imponerande sammansättning av kunskap där bland annat Blue Institutes Örjan Larsson skrivit två kapitel: AI & Digital Platforms: The Market [Part 1] och AI & Digital Platforms: The Technology [Part 2].
This essay aims to describe the dynamics at play in the field of industrial AI, where the significant efficiency potential is driving demand. There are rapid technological development and increasing use of AI technology within the industry. Meanwhile, practical applications rather than technical development itself are creating value. The primary purpose of the article is to spread knowledge to industry. It is also intended to form the basis of the Swedish innovation program PiiAs ongoing work around open calls and targeted strategic innovation projects. The basic approach taken is to investigate both industry demand for AI and how the supply of technology is developing. AI takes in a broad and dynamic range of concepts, but it should also be considered in the even broader context of industrial digitalisation. It is not just a question of technology development, but equally about application knowledge. Realising the full potential of AI requires the ability for change within individual companies, but also to handle exchanges and interactions in changing ecosystems. The article has been divided into two sections: The Market, in which we assess the development and the consequences on the factory floor; and The Technology, which provides a more in-depth understanding of the structures of industrial IT and machine-learning technology. The article concludes with four practical examples from the industry.