Given challenges with standardization, workforce, and compliance, manufacturers turn to AI to streamline workflow, enhance collaboration, and drive efficiency.
As the manufacturing world turns digital, AI has become an essential tool for transforming traditionally complex processes from sales and supply chain management to quality checks and inventory management. Faced with challenges such as lack of standardization, workforce issues, and compliance demands, manufacturers are embracing AI to streamline workflow processes, enhance collaboration, and drive overall efficiency. Countless hours are wasted with administrative tasks that could be easily supported by digitalized systems.
AI has become essential to manufacturers for enhancing efficiency, quality, and innovation. It optimizes production processes, reduces downtime through predictive maintenance, and improves supply chain management. AI-driven quality control detects defects early, ensures higher product standards, and reduces waste. Customization and flexibility are also improved, enabling efficient production of personalized products.
AI also enhances human-robot collaboration, positioning robots to perform complex tasks and work alongside humans, boosting productivity. AI optimizes energy consumption, lowers costs, and reduces environmental impact. AI accelerates innovation by simulating and modeling new products and processes, making it indispensable in modern manufacturing.
On the side or improving processes, AI can transform a burdensome and complex manufacturing environment by:
- Streamlining key functions such as sales, supply chain, quality checks, and inventory management
- Solving challenges brought forth by STEM job shortages and a lack of infrastructure or standardization
Resolving interoperability issues, enabling software to exchange and make use of information across platforms
We caught up with Grace Nam, strategic solutions manager at Laserfiche—a company that provides enterprise content management and business process automation—to hear her thoughts on how AI can transform burdensome and complex processes.
How can AI help to streamline key manufacturing functions?
Grace Nam: AI will play an increasingly critical role in the manufacturing industry by streamlining a variety of key functions. In vast and highly complex manufacturing environments, using AI to manage multi-level approval processes can better support the production floor by integrating systems seamlessly. Additionally, AI can automate cumbersome and time-consuming administrative tasks, freeing manufacturing professionals to focus on more value-driven projects and, ultimately, mitigate delays and disruptions.
In a recent SME study that surveyed over 300 manufacturing professionals, one-third of respondents experienced work delays a few times a week across various operational processes. Countless hours are wasted with administrative tasks that could be easily supported by digitalized systems.
How can AI help to address STEM job shortages?
Grace Nam: AI will help address STEM job shortages as well as cultural shifts happening with the next workforce generation. As AI takes ownership of more tasks, it will enable existing employees to fulfill roles that have been previously unaccounted for due to staff shortages. By restructuring these existing jobs and taking care of burdensome and manual processes, AI will ensure more timely and smooth operations overall and reduce worker burnout. Additionally, the rise of AI is redefining the way humans work and will demand new skill sets for employees. For the next generation of naturally tech-savvy workers, AI will present exciting opportunities and garner greater interest in technology roles.
How can AI overcome the lack of standardization?
Grace Nam: With the employment of AI algorithms, manufacturers can tackle inconsistencies in documentation and processes, thus ensuring standardization across various aspects of operations. This enables manufacturers to streamline and eliminate repetitive tasks like data processing and support compliance manners.
How can AI resolve interoperability issues?
Grace Nam: AI-driven digitization is crucial in addressing manufacturing hurdles such as interoperability issues and fragmented systems. By digitizing their operations with AI, manufacturers can streamline processes, improve system compatibility, and ensure better data flow, thus enhancing the effectiveness of their digital technology investments and achieving a higher ROI.