Energy efficiency is an extremely important topic in the highly cost-optimized field of intralogistics. Due to the current economic situation, saving resources is a topic that enjoys particular attention across all industries. One of the key challenges for warehouse managers is to keep track of all the options available in a highly diverse product landscape.

Every supplier of intralogistics hardware advertises increased energy efficiency compared to their own predecessor models or the solutions of the competition. Storage and picking processes are considered to be the most time- and energy-intensive processes in a warehouse. The parameters that decision-makers have to consider when designing, purchasing and maintaining hardware, but especially when designing internal processes, are many and often complex. These include:

  • Energy and raw material prices
  • Existing regulations
  • Lifecycle of technical components
  • Time vs. energy efficiency
  • Optimization of material flow
  • Adapted warehousing strategies

Mathematical models and measuring are indispensable

A stable foundation of data is the most important factor for evaluating and redesigning processes for greater energy efficiency. Calculation methods and simulations add value here. However, in practice, it has been shown that the models are often based on assumptions that collide with real conditions. For example, identically constructed conveyor systems do not necessarily have identical energy requirements. It is therefore essential to obtain an up-to-date overview with your own measurement data. As soon as a data-supported picture of the energy requirement exists, the available options can be adapted to their specific implementation form.

Graph showing energy usage of high bay warehousing systems
Storage and retrieval machines offer great potential for energy-efficient use.

The following applies in general: when using any kind of estimation or simulation, it should always be considered whether the underlying assumptions may have already been overtaken by the latest developments in technology and science. Simplifications can quickly lead astray if, for example, a constant speed is erroneously assumed for movements that actually accelerate. This is where powerful hardware interfaces and state-of-the-art prediction models play a central role in obtaining the necessary high-quality data.

Material flow strategies using intelligent systems

More complex processes, such as the double runs of storage and retrieval machines, are more difficult to plan than a process that only involves single runs. With the help of optimized programs for approaching a defined goal, so-called solvers, or solutions supported by artificial intelligence (AI), the likelihood of efficient operational sequences capable of producing tangible net profit increases. After all, simply maximizing double cycles and enjoying the theoretical energy savings while the preceding or subsequent processes falter, because the planning or simluation didn’t incorporate high quality data, is of no use to anyone.

The storage location is also crucial for energy-efficient intralogistics. Are the items stored in such a way that they can be retrieved quickly and also in an energy-efficient manner? IT systems support the secure application of complex storage strategies at this point, without sacrificing process reliability and speed. Where fixed storage location assignment previously offered the greatest security while also requiring a great deal of space, free storage location assignment or even mixed-item storage allocation are now better solutions. Optimizing goods distribution in this way makes it possible to improve efficiency and save energy.

Especially in e-commerce, where speed is the measure of all things, oversized packaging is often chosen. Once again, artificial intelligence offers an advantage over solvers: it adapts itself to new conditions and can be used in many different ways. Once trained, it can optimize cartons as well as pallets. This means that challenges that were previously spread across several systems can now be solved by a single application:

  • Allocation of orders to individual packing stations
  • Allocation of ordered items to individual packages and selection of suitable package sizes
  • Packing order of items and positioning of items within a parcel
  • Best possible distribution of the parcels loaded with articles and the pallets loaded with parcels to the individual delivery vehicles

Intelligent utilization of energy

“In a closed system, the total amount of energy can neither be increased nor decreased. Only the different types of energy can be converted into each other.” This section is an excerpt from the first law of thermodynamics. The term recuperation, a technical process for recovering energy, is often used in connection with electrically powered systems such as electric vehicles. This technology has been used in rail transportation for a long time in the form of so-called regenerative brakes, which convert kinetic energy back into electrical energy. Waste heat can also be reused in certain situations.

Energy and time are two competing target values for all movements in the warehouse that need to be brought into economic balance. For example, synchronized movements of storage and retrieval machines along the x and y axis may seem intuitively economical. However, if energy recovery technologies are installed, independent movement of the axis may offer greater benefits.

Outlook

Sustainability aspects play a central role in intralogistics – and their importance will increase. The complexity of this topic requires those responsible to carefully weigh up various parameters such as the price of resources, existing regulations and the life cycles of technical components. The creation of a stable database through measurements and simulations forms an indispensable basis for well-founded decisions. The integration of AI-supported solutions enables the development of sustainable workflows, as they can be used more efficiently in complex processes such as the double cycle of storage and retrieval machines. Greater flexibility in storage location allocation, supported by IT systems, reduces distances and saves time and energy. The responsible use of energy, in economic balance between resource efficiency and time, will be one of the fundamental competitive advantages of the future.

This article first appeared in the trade journal “Technische Logistik” 04/2024 in German and is available here as a PDF download.

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