9th North American Conference on Industrial Engineering and Operations Management

Business-Driven Digital Transformation in Industry 4.0

Zhongyuan Li & Hamid Parsaei
Publisher: IEOM Society International
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Abstract

Industry 4.0 integrates physical and data technologies such as Internet of Things, Artificial Intelligence, and big data analytics, transforming both manufacturing and service industries. Central to Industry 4.0 is digital transformation, which infuses data technologies throughout businesses, enabling insights into manufacturing processes, identifying areas for improvement, and optimizing operations and services. A key challenge of digital transformation lies in determining who will lead the transformation and maintain digital assets. Organizations may opt to purchase SaaS (Service as a Service) digital products or develop their own. However, maintaining control over digital assets during transformation proves daunting. Digital products, akin to black boxes, are user-friendly yet challenging to control and comprehend. The opacity of production development and unfamiliarity with data technologies often cause organizations to hesitate in their digital transformation decisions. In this paper, we propose a solution that divides digital product development into pure engineering and business configuration components. Each aspect can be concurrently developed by engineers and business owners. This approach allows business owners possessing domain knowledge and requirements to actively engage in digital product development alongside development engineers, comprehensively understanding and controlling their digital assets. With this solution, business owners assume full control of business logic and requirements, while engineers focus solely on engineering products that can be easily extended, upgraded, or replaced. This framework reduces dependencies on data technology and engineering efforts, empowering business owners to drive and lead digital transformation. A data engineering project is presented to illustrate the design of a scalable, plug-and-play framework.

Published in: 9th North American Conference on Industrial Engineering and Operations Management, Washington D.C., United States

Publisher: IEOM Society International
Date of Conference: June 4-6, 2024

ISBN: 979-8-3507-1736-5
ISSN/E-ISSN: 2169-8767