Citation :

Sankarshana Madhavarao, "Manufacturing: “Lights-Out” Factories—Using AI To Run Fully Autonomous Production Lines with IoT Integration," International Journal of Computer Trends and Technology (IJCTT), vol. 74, no. 5, pp. 36-49, 2026. Crossref, https://doi.org/10.14445/22312803/IJCTT-V74I5P105

Abstract

The ultimate goal of automating industrial processes is lights-out manufacturing in which manufacturing systems operate independently with either minimal or no human operator involvement. The research paper is a challenge to the technological assumptions, supply chain processes, and strategic requirements that enable the implementation of entirely autonomous factories. It analyzes the role that digitally advanced robotics, AI, the Industrial Internet of Things (IIoT), and digital twins play in the development of self-optimising and resilient manufacturing spaces. The focal attention is put on digital twins as virtual replicas, which are real-time and synchronized, and provide an opportunity to simulate, optimize, and train AI. The paper also outlines an overall operational process that is an overview of the receipt, planning, execution, monitoring, and fulfillment of orders in a lights-out factory. These are material management, autonomous production, in-line quality control, exception management, and inventory management. It is suggested to use an implementation roadmap, covering a gradual development implementation starting with the feasibility analysis, up to the integration of the enterprise system. The study, based on empirical case studies of the industry, points out the success factors and widespread failure modes in lights-out implementations. The article summarizes that, despite the technological choices to consider at any given time, lights-out manufacturing is a method that will be successful when applied in a disciplined way, with strong data-based grounds and a balance between technical independence and the ultimate strategy of the business organizations.

Keywords

Artificial intelligence, Autonomous systems, Digital twins, Edge computing, Industrial IoT, Predictive maintenance.

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