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How AI can transform a burdensome and complex manufacturing environment

June 15, 2024
As manufacturers adopt AI, they can expect enhanced efficiency and output and the ability to make more informed decisions and adapt swiftly to market changes.

The manufacturing sector, known for its intricate processes and high demands for precision, is on the brink of a revolution driven by, you guessed it, AI. This transformation represents more than just a technological upgrade; it signifies a comprehensive overhaul that aims to rectify long-standing inefficiencies, streamline operations, and significantly boost productivity.

AI's integration into manufacturing processes enables real-time data analysis, predictive maintenance, and automation of repetitive tasks, leading to reduced operational costs and minimized human error.

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Every day, professionals devote a significant portion of their time to handling documents and upkeeping tasks, such as finding the location of paper, ensuring the final version of documents, saving the documents/structuring the documents, and reviewing and correcting data

As manufacturers adopt AI, they can expect enhanced efficiency and output and the ability to make more informed decisions and adapt swiftly to market changes, thereby securing a competitive edge in an increasingly dynamic industry.

The current state of manufacturing

A recent study by SME, involving over 300 manufacturing professionals, highlighted a critical issue: Frequent work delays across various operational processes. About one-third of the respondents reported experiencing these delays several times a week. Such interruptions not only waste valuable time but also impact productivity and profitability. The study underscores the pressing need for solutions to alleviate these operational bottlenecks.

AI's potential in streamlining operations

AI has the potential to revolutionize essential manufacturing functions, from sales and supply chain management to quality control and inventory management. By integrating AI, manufacturers can predict potential disruptions, optimize resource allocation, and ensure timely deliveries.

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For example, AI algorithms can analyze both historical and current data to forecast demand accurately, thereby aligning inventory levels with market needs and reducing the risk of overproduction or stockouts. This capability represents a critical revolution for manufacturing, as it enables decisions to be based not just on outdated data but on real-time analysis of both past and present information.

Addressing workforce challenges

The manufacturing industry is also grappling with a shortage of STEM professionals and a lack of standardized processes. However, AI technology offers a promising solution by automating complex tasks that traditionally do not require specialized skills to perform such as managing inventory data, job order, inspection, and customer service documentation that require manual administrative responsibilities.

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AI can streamline rule-based processes, relieving process experts and employees of repetitive administrative tasks and allowing them to focus on more strategic and value-added activities to perform areas that require technical knowledge. By leveraging AI to automate these tasks, manufacturers can address the shortage of skilled professionals and also enhance the capabilities of their existing workforce.

While there are concerns about AI leading to job displacement, the reality is that AI will augment the human workforce. By automating traditional processes in manufacturing, AI frees employees to engage in higher-level activities that require creativity and problem-solving that involve more of human nature and expertise.

See also: Survey: 90% of manufacturers are using AI, but many feel they lag behind competitors

This shift enhances job satisfaction and drives innovation within the organization. As AI becomes more integrated into manufacturing, the demand for workers skilled in AI implementation and human-machine collaboration will increase, necessitating upskilling and reskilling initiatives, to the benefit of the workers who go through these processes. Ultimately, creating a better ecosystem with operational resilience and efficiency.

Enhancing interoperability

One significant hurdle in modern manufacturing is interoperability among different software systems. AI can solve this by enabling seamless communication between disparate platforms and teams. Through machine learning algorithms, AI can facilitate the exchange of information across systems, creating a cohesive and integrated operational environment. This interoperability is crucial for real-time decision-making and efficient process management.

Improving data accuracy and reducing errors

AI-capture tools are at the forefront of transforming how manufacturers handle data. These tools can streamline vast amounts of content, extract relevant information, and automatically organize it. This capability is particularly valuable in managing compliance documentation, which is often complex and time-consuming. By automating data capture and classification, AI ensures that all documents are easily searchable and retrievable, significantly reducing the time spent on administrative tasks.

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Manual data entry and processing are prone to human errors, which can lead to costly and time-consuming mistakes that can cause delays across an organization. With its advanced recognition capabilities, AI can accurately extract data from documents, minimizing the risk of errors. This improves data accuracy and enhances the reliability of the information used for decision-making. AI can automatically classify metadata, making managing and retrieving documents easier, thereby streamlining records management.

Scaling operations seamlessly

AI offers unparalleled scalability, allowing manufacturers to expand their operations without a corresponding increase in complexity. AI transforms records management, data/information governance to ensure organization positions themselves to protect their critical assets, and process automation by connecting various enterprise applications. This seamless scalability ensures that as manufacturing operations grow, AI systems can efficiently handle the increased data volumes and operational demands.

Improving compliance management

Compliance with industry regulations is a significant concern for manufacturers. AI simplifies compliance management by automating data capture and document management. AI-powered document management systems streamline the organization, retrieval, and updating of compliance-related documents, minimizing errors and facilitating timely audits. By reducing the burden of endless numbers of compliance requirements, AI allows manufacturers to focus on core operations and strategic initiatives.

Real-world benefits of AI in manufacturing

Implementing AI in manufacturing offers tangible benefits such as reduced operational costs, improved productivity, and enhanced data management. By automating tedious tasks, AI lowers labor costs and minimizes human error. It also eliminates bottlenecks and delays, fostering a more productive workforce by automating daily step-by-step tasks whether they are rule-based or decision-driven. Additionally, real-time data capture and analysis provide valuable insights for better decision-making and future planning.

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AI promises to transform the manufacturing sector by addressing existing challenges and unlocking new opportunities for efficiency and growth. As the recent study by SME illuminated, approximately one-third of manufacturing professionals are experiencing delays several times a week.

Leveraging AI to mitigate these delays and optimize operational processes can significantly enhance productivity and reduce costs.

This not only streamlines operations but also increases contributions toward organizational savings and drives higher revenue, whether through intentional revenue growth strategies or simply by operating more efficiently.

By embracing AI, manufacturers can navigate the complexities of their environment and pave the way for a more innovative and resilient future.

About the Author

Grace Nam

Grace Nam is the strategic solutions manager at Laserfiche. She performs market research to revamp processes in the most highly regulated industries—health care and manufacturing. Over the course of her career, Nam has experienced firsthand the challenges in adopting new technologies that the health care and manufacturing industries face. Prior to Laserfiche, Nam drove strategy as part of the marketing teams at Legrande Health and Crane ChemParma & Energy, among other organizations.