Data Process Mining in warehouse logistics
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Artificial intelligence (AI) in logistics Where is the journey heading?
Artificial intelligence (AI) has been a hot topic for years, and the hype surrounding ChatGPT has brought it to a new high. As early as 2021, surveys showed that 54 percent, i.e. every second company, rated the use of artificial intelligence as "crucial for their own future competitiveness". A third were planning or discussing its use.(1)
These figures are likely to have picked up in the meantime. On the part of the digital association Bitkom, a recent report predicts that AI will change the world more "than such a major innovation as the smartphone has done."(2)
But what does this mean for logistics? Where might AI already be at work, and what new options does machine learning (ML) open up in intralogistics specifically? This article provides some food for thought!
FAQs
Artificial intelligence (AI) refers to the ability of a machine to mimic human cognitive competencies, such as perceptiveness and reasoning. AI is able to perceive the environment, adapt its actions, find answers independently and solve problems on its own.
In recent years, great strides have been made in the field of machine learning, owing to the increasing availability of big data and high computing power. Machine learning focuses on techniques and the use of algorithms that enable computers to learn autonomously from data and patterns. It allows computers to accomplish tasks and make decisions without the need for specific and detailed programming that gives them direct instructions. It is considered a technique for achieving artificial intelligence.
Business applications in the field of AI are mostly based on Machine Learning. Artificial Intelligence (AI) is an umbrella term that encompasses various concepts. The exact definition can vary depending on the industry and research area. It refers to a system that recognizes its environment (e.g., input data) and mimics human processing and decision-making mechanisms to interact with it.
AI simplifies all processes in the warehouse and supports staff in operations. AI recognizes even the most complex interrelationships and helps to make decisions regarding further process optimization along the supply chain faster and more reliably with the help of predictive logistics.
Fundamental advantages can be expected above all in inventory recording and management, picking and package sorting, and transport, including the optimization of delivery routes. Many of these tasks can be performed more economically and with less resource consumption with the help of AI.
Artificial intelligence as a data analyst in a class of its own
Chatbots have become indispensable, and not just for amateur cooks and do-it-yourselfers - in other words, artificial intelligence that is conditioned to answer queries and offer suggestions for solutions. And what works in everyday life also works in logistics and warehousing - when influencing factors become more complex and it becomes increasingly difficult for humans to make reliable decisions.
One major advantage of AI is the speed with which it compares a large number of parameters in parallel and generates accurate solutions practically in real time. In the process, not only the status quo but also historical data and currently changed framework conditions are included in the decision-making process. In this way, processes in the warehouse can be made simpler, more resource-efficient and more efficient at a speed that humans cannot keep up with.
AI as a tool for forecasting and process optimization
Artificial intelligence (AI) is ergo capable of mapping complex interrelationships, learning from experience and continuously expanding the accumulated wealth of knowledge. The complex algorithm behind an AI shows its strengths above all in the field of forecasting and process optimization. Intelligent warehouse strategies have already been a reality for years: just think of the use of warehouse management systems (WMS), which independently drive intelligent material flow strategies at the push of a button, taking into account the daily order volume. However, the strategies implemented in these systems are stored as sets of rules or settings/coding.
In the course of warehouse management, for example - especially in the case of complex warehouse structures - a wealth of data is generated that has already reached "big data" status. AI has the potential to capture, analyze and correlate this data in a previously unknown breadth and depth . Using state-of-the-art, AI-controlled warehouse strategies, it is already possible today, for example, not only to further increase the performance of an automated warehouse, but also to significantly reduce travel distances at the same time. This is precisely because not only are the rules stored at the time of implementation applied, but also current conditions are converted into rules and decisions. "Smart Slotting" is the name of one of the solutions that makes this possible. By using AI, the technology can determine and assign the optimal location in the warehouse for storing containers. There is particularly great potential here through AI for companies whose product range changes more frequently or is subject to seasonal fluctuations, for example.
More examples of AI-driven technologies in logistics.
The boom in the field of artificial intelligence (AI) is also a consequence of recent technological progress, especially with regard to processors, sensors, networks and Big Data mining. This development creates optimal conditions for the targeted use of automatic image or object recognition, robotic process automation, drones and autonomous transport vehicles in logistics. In short, human-machine interaction can be raised to an unprecedented level with the help of AI.
The greatest potential of AI in logistics currently certainly lies in the field of robotics. Robots act in the same way as humans, learn from mistakes and successes in equal measure, and their concentration does not wane even in 24-hour operation. A good example is the Pick-by-Robot robotics solution integrated in SAP for automated single-item picking. These robots relieve staff through their ability to work completely autonomously, but are also congenially supportive of humans. One smart function of Pick-by-Robot, for example, is the optimal "grip in the box": Various algorithms in SAP EWM are used to calculate the ideal gripping and suction points for the items in fractions of a second. At the same time, integrated and camera-controlled monitoring functions ensure 100% picking reliability. In addition, packing pattern algorithms and machine learning functions are stored for automatic master data maintenance.
If you want to know more: We've covered the areas of application for robots in the blog post "How are robots worthwhile in warehouse logistics?" and more about machine learning in the post "Machine learning on the rise".
Logistics 4.0: Self-organization and control as a goal
The control of vehicle fleets is also predestined for the use of artificial intelligence (AI). "Automated Guided Vehicles" (AGVs = AGVs) or "Autonomous Mobile Robots" (AMR) are increasingly taking over transport tasks that were previously handled by forklifts or hand pallet trucks. These freely or autonomously navigating vehicles of the latest design are also trimmed to machine learning, organize themselves independently and react flexibly to changes that they perceive within their radius of action. In this way, collisions are avoided and transports are carried out reliably.
Another example of applied artificial intelligence and Logistics 4.0 is the patented HAWK3 pack assistance system. This "eye of logistics" installed above a conveyor system permanently monitors the status of a packing process and improves packaging planning. Through AI, HAWK2 learns from collaboration with a human counterpart (Packer:in) and uses the insights gained for future packing operations.
Conclusion: Profiting from AI and its advantages
Will AI really revolutionize the world of work completely, as is often rumored? Is it the future? Objectively speaking, the fact is that familiar processes will undergo lasting change. This will happen simply because digitization and AI are associated with significant added value for companies. This is because forecasts regarding customer behavior will be improved and will be reflected in the provision of inventories and capacities. Logistics costs can be reduced and few to no errors occur. The latter increases delivery quality and strengthens customer relationships. Picking and internal transports are accelerated so that order lead times are minimized.
Skeptics may remark at this point that the benefits can be achieved through process automation alone. In principle, this is true, but AI puts the proverbial "icing on the cake", as it is able to analyze and correlate data, map complex relationships and learn from experience. Performance values are thus significantly topped once again. At the same time, artificial intelligence in logistics will in the future offer the possibility of developing business models whose content has so far only been vaguely conceivable. But already today, comprehensible or measurable advantages of AI technologies can be found in many areas:
- AI-controlled robots increase picking efficiency and shorten lead times.
- Inventory management is massively improved so that capital is not tied up unnecessarily.
- Management and staff are supported in decision-making, fully exploiting the potential of Big Data.
- AI-based resource planning helps ensure that employees and resources in the warehouse are deployed in a more targeted manner and costs are saved.
- Interaction and communication with robots, for example, take place in real time so that changes can be responded to immediately.
- AI is increasingly becoming an integral part of modern warehouse management systems (WMS), which act as a clock generator for continuously learning, self-organizing intralogistics.
More info and sources on the topic:
(1) " IT Trends 2022: Companies are counting on these technologies" | Article | IAVCWorld
(2) " Three quarters see artificial intelligence as an opportunity" | Press release | Bitkom e.V.
