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Q&A: Upskilling Manufacturing Factory Workers With AI

June 13, 2024
Could the reach and value of human-centric generative AI become a ubiquitous tool on factory floors?

The quest to shape our understanding of AI is occurring at the same time that we’re experimenting with its potential applications, from designing through integration of products and processes. Oftentimes, that means not only inventing but also right-sizing an AI playbook for bringing people, process and technology together.  

The applications of AI on the factory floor are vastly different and manufacturers may not be doing enough to set up their employees on the ground for success, argues Diwakar Singhal, global business leader of manufacturing at Genpact, a professional services firm that employs generative AI to integrate controls and governance metrics to future-proof AI investments.  

In the Q&A below, Singhal answers foundational questions about integrating AI into factory floor operations, as well as the role AI will play in predictive maintenance, quality assurance and process optimization. 

Machine Design: How do the applications of AI differ between workers on the factory floor and those in the back office within manufacturing? 

Diwakar Singhal: In manufacturing, AI serves distinct roles for workers on the factory floor versus those in the back office. While back-office employees primarily interact with AI for tasks such as data analysis and decision-making, factory floor workers directly engage with AI-powered machinery or robots to execute production tasks.

This demands a unique skill set and level of training, with factory workers needing to collaborate with AI systems, troubleshoot issues and act on recommendations for optimizing production efficiency and quality. Unlike back-office functions where AI operates in the background, its integration on the factory floor transforms workers into active users, necessitating tailored training programs to maximize its impact on manufacturing outcomes. 

READ MORE: Generative AI’s Transformative Impact on Manufacturing: Unleashing the Power of Industrial Data 

Moreover, the nature of AI utilization in manufacturing extends beyond mere task automation. It entails leveraging AI-driven insights to optimize processes, enhance product quality and minimize downtime. Factory floor workers serve as the frontline users of AI, translating its potential into tangible improvements in manufacturing operations. They require specialized training and ongoing support to effectively harness the capabilities of AI technologies and maximize their impact on production outcomes. 

While AI serves as a behind-the-scenes facilitator in back-office operations, its integration on the factory floor transforms workers into active collaborators with intelligent technologies. This paradigm shift necessitates a reevaluation of training programs and skill development initiatives to equip factory floor workers with the expertise required to leverage AI effectively in manufacturing settings. By empowering workers with the necessary knowledge and tools, organizations can unleash the full potential of AI to drive innovation and competitiveness in the manufacturing sector. 

MD: What’s the foremost priority for manufacturers when integrating AI into factory floor operations? 

DS: It’s imperative that factory floor workers undergo training tailored to the AI employed in their functional areas, such as machinery operation, production line monitoring and quality inspections. These training modules should be customized to align with job roles, safety requirements and practical familiarity with AI technologies in the manufacturing environment. 

READ MORE: Generative Design, Artificial Intelligence and Manufacturing 

Beyond role-specific training, all workers should receive specialized safety training to mitigate accidents and uphold workplace safety standards when interacting with AI-driven equipment. Practical, hands-on training enables them to develop confidence and proficiency in leveraging AI effectively to optimize manufacturing processes and attain production objectives goals in a secure environment. 

Moreover, in the long term, training initiatives should expose workers to the potential AI holds for streamlining tasks, enhancing product quality and fostering innovation. Establishing a robust training program from the outset is not only instrumental in prioritizing safety but can also inspire employees to identify additional opportunities where AI can augment their day-to-day activities. 

MD: Can you share a few examples of areas where AI may be implemented to support manufacturers over the coming years? 

DS: In the foreseeable future, the integration of AI holds tremendous promise for various facets of manufacturing. In the back office, AI implementation is poised to revolutionize knowledge management and customer contracts management. By harnessing AI capabilities, organizations can expect a significant enhancement in customer experience and a notable reduction in procurement timelines.

AI-driven systems can efficiently organize, analyze and extract insights from vast repositories of data, enabling businesses to make informed decisions swiftly and effectively. Moreover, AI-powered contract management platforms can streamline the entire contract lifecycle, from creation to negotiation to execution, ensuring compliance, minimizing risks and optimizing resource allocation. 

On the factory floor, AI algorithms are set to play a pivotal role in predictive maintenance, quality assurance, and process optimization. One of the most promising applications is the use of AI to forecast machine failures. By leveraging historical data, real-time sensor inputs and advanced analytics, AI models can predict potential equipment malfunctions before they occur, enabling proactive maintenance interventions to prevent costly downtime and production delays.

Additionally, AI-driven quality control systems can detect defects and anomalies during the product development phase, ensuring that only products meeting stringent quality standards reach the market. This not only safeguards brand reputation but also enhances customer satisfaction and loyalty. 

READ MORE: Data, AI and the Generative Design Revolution 

Furthermore, AI-powered visual inspection technologies, such as computer vision, are poised to revolutionize manufacturing processes. These systems can automatically analyze images and videos captured by cameras installed along production lines, identifying defects, irregularities or deviations from specifications with unparalleled speed and accuracy.

By automating tedious and error-prone manual inspection tasks, AI-driven visual inspection systems free up human workers to focus on more complex and value-added activities, thereby increasing overall productivity and efficiency. 

In summary, the future of manufacturing is intricately linked with the widespread adoption and integration of AI technologies. By embracing AI in both the back office and on the factory floor, organizations can unlock new levels of operational efficiency, productivity and competitiveness.

However, successful AI implementation requires careful planning, investment in talent development and a commitment to continuous innovation and improvement. As manufacturers navigate the complexities of the digital age, those who embrace AI as a strategic enabler stand to reap substantial rewards in terms of cost savings, quality improvement and sustainable growth.   

Editor’s Note: Machine Design’s WISE (Workers in Science and Engineering) hub compiles our coverage of workplace issues affecting the engineering field, in addition to contributions from equity seeking groups and subject matter experts within various subdisciplines. 

About the Author

Rehana Begg | Editor-in-Chief, Machine Design

As Machine Design’s content lead, Rehana Begg is tasked with elevating the voice of the design and multi-disciplinary engineer in the face of digital transformation and engineering innovation. Begg has more than 24 years of editorial experience and has spent the past decade in the trenches of industrial manufacturing, focusing on new technologies, manufacturing innovation and business. Her B2B career has taken her from corporate boardrooms to plant floors and underground mining stopes, covering everything from automation & IIoT, robotics, mechanical design and additive manufacturing to plant operations, maintenance, reliability and continuous improvement. Begg holds an MBA, a Master of Journalism degree, and a BA (Hons.) in Political Science. She is committed to lifelong learning and feeds her passion for innovation in publishing, transparent science and clear communication by attending relevant conferences and seminars/workshops. 

Follow Rehana Begg via the following social media handles:

X: @rehanabegg

LinkedIn: @rehanabegg and @MachineDesign

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