Food giants are closing legacy plants and building greenfield facilities to achieve higher volumes, greater flexibility and increased margins. So how are plant managers and corporate leadership executing, managing and delivering data to help operators find accurate KPIs and OEE metrics?
Overall equipment effectiveness (OEE) remains the go-to benchmark for gauging performance, but raising OEE requires more than tracking metrics. It calls for a holistic approach that combines robust planning, skilled people and seamless digital integration.
Achieving a high OEE score has been elusive in the past as processors grapple with where to begin in troubleshooting OEE issues. The future of OEE, with the help of AI technology, will help manufacturers find the most miniscule of line problems and be on top of their game.
With manufacturing barely expanding and costs tightening, companies are looking to squeeze every bit of efficiency from their operations. AI-driven optimization of OEE metrics is becoming an essential lever for doing exactly that.
Because boiler systems are inherently dangerous, safety must be factored into the design of not just the boiler but also the burner, combustion control, and overall operation of the system.
The race to standardize plant data is happening fast. As food manufacturers standardize data, digital tools accelerate and provide a closer look at overall equipment effectiveness (OEE) and maintenance metrics.
Data collection has become a major part of food manufacturing, but without data standardization, measuring overall equipment effectiveness (OEE) poses a challenge.
Creating efficient conveying systems begins with knowing what you want to accomplish, then enlisting the help of system integrators and suppliers — you may find that you can do things you hadn’t thought possible.
Creating efficient conveying systems begins with knowing what you want to accomplish, then enlisting the help of system integrators and suppliers — you may find that you can do things you hadn’t thought possible.
Artificial intelligence-powered PLM can make accurate projections about planning new products, introducing them to the market and looking at all the factors a processor might miss in execution.
Artificial intelligence-powered PLM can make accurate projections about planning new products, introducing them to the market and looking at all the factors a processor might miss in execution.
Goodman Fielder, a large Australian baking company, bucks the digitalization project trend by integrating system software platforms for three factories.
The food manufacturing sector is rapidly embracing automation and data-driven tools, with companies like Tyson Foods and Goodman Fielder leading the charge. From reducing labor costs to streamlining operations with advanced SCADA and MES platforms, the industry is leveraging cutting-edge technology to address workforce challenges, boost efficiency, and drive sustainable growth.
Artificial intelligence, coupled with machine learning, promises to improve plant operations from sensor level to the enterprise, but adoption has been slow with some overzealous starts.