With so much emphasis on automating the packaging line, some organizations are overlooking the value that decision-making machine operators continue to deliver. Others, however, are embracing the benefits of the human element.
QAD, known for its enterprise resource planning (ERP) system for manufacturers, tuned into the need to incorporate people into the technology platform to enable better productivity, compliance, reliability, and learning on the plant floor and packaging line. That resulted in the rollout of QAD Redzone several years ago, which company officials claim is the original connected worker concept.
QAD Redzone was built specifically to unify productivity, engagement, and recognition of workers for the retention of people. “We believe in a bottom-up vs. a top-down approach to running a plant,” said Ron Davis, senior vice president of product engineering at QAD Redzone in an interview with Packaging OEM. “It’s how to align people, processes, and systems to drive outcome.”
To that end, QAD Redzone has long included artificial intelligence (AI) to overcome language barriers, transcribe and translate video content, and streamline support processes — all with a focus on tangible results and critical information that frontline workers need to excel.
Now, it also incorporates artificial intelligence (AI) to provide predictive analytics and pragmatic tools that will help operators work effectively.
Connecting workers with AI
During Pack Expo International 2024 in Chicago, QAD Redzone announced the launch of Champion AI, a suite of AI-driven capabilities designed to empower the frontlines with predictions, recommendations, proactive problem solving, which ultimately enable enhanced productivity. Champion AI goes beyond traditional AI applications by solving specific problems on the plant floor in a new way, the company said.
As the company’s next generation of AI, Champion AI provides predictive and prescriptive analytics through Generative AI (GenAI) to address daily challenges in manufacturing such as detecting plant-wide outliers, delivering daily operational summaries, predicting run durations and identifying potential run problems before they happen. The pragmatic AI solution equips workers with the tools to anticipate issues, optimize changeovers, and analyze performance data — setting new standards for engagement and productivity. Redzone’s automated productivity data collection provides a feedback loop so that Champion AI knows which recommendations drive the best outcome.
A proactive approach to problem-solving
Getting people to engage in real time means shortening the feedback loop, which is where AI comes in to help move from a reactive to a proactive state, Davis explained. Using machine learning (ML), Redzone can provide information on what went well — like hitting better overall equipment efficiency (OEE), or what went wrong, such as a quality test failure. This information is stored as daily vital signs to drive productivity through continuous improvement.
“Champion AI represents our commitment to practical AI solutions that assist workers in achieving higher productivity, not by overwhelming or replacing them with technology but by acting as an accessible, intelligent assistant,” said Davis. “This is the AI champion that factory teams have been waiting for because it provides meaningful insights to address real issues they are facing on the factory floor.”
A knowledge assist module uses GenAI to ask questions of the plant and packaging line data. In addition, a run assist module looks at historical data from shifts, runs, and people on the line to make predictions. For example, it could tell the operator when to expect the next changeover to be and potentially the top problems.
“It is AI plus humans, not AI minus humans,” Davis said. “The focus is on how to align people, process, and systems for industrial digital transformation.”
