Benefits and Challenges of Implementing Autonomous Technology for Sustainable Material Handling in Industrial Processes

Abstract

The transition from traditional production activities to a manufacturing-dominated economy has been a hallmark of industrial evolution, culminating in the advent of the fourth industrial revolution. This phase is characterized by the seamless integration of digital advancements across all sectors of global industry, heralding significant strides in meeting the evolving demands of markets and consumers. The concept of the smart factory stands at the forefront of this transformation, embedding sustainability, which is defined as economic viability, environmental stewardship, and social responsibility, into its core principles. This research focuses on the critical role of autonomous material handling technologies within these smart manufacturing environments, emphasizing their contribution to enhancing industrial productivity. The automation of material handling, propelled by the exigencies of reducing material damage, minimizing human intervention in repetitive tasks, and mitigating errors and service delays, is increasingly viewed as indispensable for achieving sustainable industrial operations. The employment of artificial intelligence (AI) in material handling not only offers substantial benefits in terms of operational efficiency and sustainability but also introduces specific challenges that must be navigated to align with the smart factory paradigm. By examining the integration of autonomous material handling solutions, traditionally epitomized by the utilization of forklifts in industrial settings, this study delineates the essential benchmarks for their implementation, ensuring compatibility with the overarching objectives of smart manufacturing systems. Through this lens, the paper articulates the dual imperative of aligning material handling technologies with environmental and social sustainability criteria, while also ensuring their economic feasibility.