Recently I had the pleasure of joining an expert panel, brought together by UKWA member Linde Material Handling, for a webinar considering the potential impact of AI (Artificial Intelligence) in intralogistics. This is a hot topic right now and one which we plan to explore in depth at our next National Conference in March.
Arguably the most revolutionary technology of the 21st century, AI is set to transform society and the job market and, since its inception, has evolved rapidly, driving change across all sectors – not least warehousing & logistics.
Its potential is enormous and, when adopted universally, AI will change the face of warehouse management.
Key prizes include better forecasting for energy use, consumer demand and labour needs. By leveraging machine learning algorithms to analyse historical data, real-time inputs, and market trends, AI can provide highly accurate predictions around demand to optimise inventory levels and reduce the risk of stockouts or overstocking, labour resource requirements and energy use to calculate related costs.
Another opportunity offered by AI is improved route optimisation, identifying the best movement paths around the warehouse by analysing real-time data on inventory locations, order priorities, and worker or robot movements. Machine learning algorithms determine the most efficient paths for picking, packing, and replenishment tasks, minimising travel distance and time. Optimisation of these internal routes, accelerates order processing, and increases overall productivity, leading to faster fulfilment times and reduced operational costs in warehouse management
AI can support proactive maintenance too, avoiding costly breakdowns and downtime inside the warehouse. Data from sensors on equipment, like forklifts, machinery and racking can be used to predict potential failures before they occur.
Supported by computer vision technology allowing information to be extracted from barcodes, videos, digital images and other visual inputs, AI-driven cameras can track inventory levels, detect misplaced items, and monitor the movement of goods and personnel.
The creation of sophisticated digital twins is perhaps one of the most important aspects of AI, supporting enhanced scenario planning and training in a warehouse environment. AI-powered digital twins can simulate warehouse operations, enabling scenario testing before change implementation in the physical environment. This allows dynamic adjustments in layout, inventory management and workflow processes, based on real-time conditions and predictions. AI digital twins can be used to provide low risk training where failure doesn’t matter, workers wearing headsets to drive a virtual forklift truck before they operate a real one, for example.
In time, supply chain leaders will be able to use AI like Siri or Alexa to get simple answers in human language to questions on specific issues, and as the technology develops it will become smart enough to allow robots to do more jobs, such as working in hazardous and/or low and high temperature environments.
In summary, while the take up of AI in the warehouse is currently a mixed picture, it is undoubtedly the future for us all.
Clare Bottle
UKWA, CEO
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