Page 47 - Plastics News Issue September2025
P. 47
FEATURE NEWS
making sense of massive data dumps or assess- cording to the Industry Week article, “Easing into
ing the pros and cons of many combinations, it AI and Machine Learning,” 5 it is a good idea to
also can be a useful tool for identifying opera- start an exploration of AI by applying it to edge
tions and process improvements. Writer Srinath rather than cloud processes. “Implementing AI
goud Vanga points to some use cases for manu- and machine learning on edge devices closer to
facturers to consider in the article “Harnessing factory or fulfillment operations,” writes Eliza-
AI to Streamline Manufacturing Processes.” 4 beth Samara-Rubio, “could provide solutions for
Quality control and demand forecasting are just the pressures manufacturers face with real-time
two of the areas that the author cites as strong computing and insights. By starting with target-
use cases for AI.To improve quality control on ed use cases to address decade-long innovation
the factory floor, AI-powered computer vision challenges, manufacturers can quickly demon-
stands out as a natural choice. “Human involve- strate and gain value.” Samara-Rubio points out
ment in quality control can introduce inconsisten- that AI and ML can help manufacturers optimize
cies,” writes goud Vanga. “AI-powered comput- production scheduling, reduce waste and iden-
er vision systems bring an objective eye to the tify operation bottlenecks.4. AI Attracts Work-
process. These systems can meticulously detect force Talent
even the most subtle flaws, ensuring uniform
quality standards across factories and reducing AI can conjure up novel images, make sense of
the burden on human inspectors.” Companies feedback data overload or pinpoint production
might choose either to assist or to replace qual- problems, but it can’t make job applicants line up
ity control workers with AI. “These models can at the door. Or maybe it can. In “AI Is the Key to
be deployed in two ways:” the author writes, “as Unlocking Manufacturing’s Future Workforce,”
a co-pilot to a human quality assessor, provid- Author Berk Birand promotes the value of AI in a
ing real-time feedback and highlighting potential manufacturer’s operations as a recruitment tool.
issues; or as an independent system for highly “AI is transforming manufacturing from tradition-
repetitive and well-defined tasks.”In demand al, labor-intensive processes to high-tech, data-
forecasting, companies can turn to structured driven operations,” Birand writes. “This shift is
machine learning (ML) data and unstructured crucial in attracting technically savvy college
text for insights into future demand. Structured graduates who might otherwise overlook manu-
ML data is quite manageable, but companies facturing as a career path. By integrating AI into
“often struggle to incorporate insights from the manufacturing processes, companies can offer
vast world of unstructured text,” writes the au- exciting opportunities in areas such as machine
thor. “This unstructured information that exists in learning, data analytics and robotics, aligning
the form of social media conversations, product with the interests of tech-oriented graduates.”
reviews and online trends have tremendous pre- Today’s young, bright workers also are interest-
dictive power. The latest large language models ed in sustainability – an aspect of manufacturing
(LLMs), such as GPT-4 and Gemini, have shown that benefits greatly from tools like AI for waste
exceptional capabilities in converting textual reduction, energy efficiency improvements and
data into quantifiable demand drivers and sig- thoughtful resource use. And new AI-based
nificantly improving forecast accuracy.”And, ac-
training technologies, such as augmented reality
September 2025 PLASTICS NEWS 47
