The Emergence of New Business and Operating Models Under the Industrial Digital Paradigm Industrial Internet of Things (IIoT), Platforms, and Artificial Intelligence/Machine Learning (AI/ML)

EasyChair Preprint 4703

Abstract

This paper pretends to approach and analyse opportunities and risks that arises under the Industrial digital paradigm. Known by different names like Industry 4.0, Smart Manufacturing, or Production 4.0, among other terms digitalization in industry is advancing at a tremendous speed, and is pushing stablished firms to change and adopt new tools. Besides it opens opportunities to technological startups to deliver new products and services to the industrial market. As an example of opportunities in operating models, it is clear that digitalization under the model Industry 4.0 and the advantages of Industrial Internet of the Things (IIoT), allows faster response to customer demands, increase flexibility allowing the adaptability to manufacturing processes, and provides a tremendous amount of tools for quality improvement in the processes, among other ad-vantages. This article addresses the data driven organization as digitalization evolves and the progress of Artificial Intelligence (AI) and Machine Learning (ML) solutions for industry, such as those presented by new companies like LLamasoft, which provides AI for supply chain management (SCM), and Canvass Analytics, which provides an AI/ML platform to optimize processes, among a fresh bunch of startups that are evolving exploiting opportunities in this field.

Keyphrases: Artificial Intelligence, Big Data, Change Management, Data Analytic, Data driven management, Industrial AI/ML, Industry 4.0, business model, industrial environment

@booklet{EasyChair:4703,
  author    = {Federico Walas Mateo and Andres Redchuk},
  title     = {The Emergence of New Business and Operating Models Under the Industrial Digital Paradigm Industrial Internet of Things (IIoT), Platforms, and Artificial Intelligence/Machine Learning (AI/ML)},
  howpublished = {EasyChair Preprint 4703},
  year      = {EasyChair, 2020}}