AT BLG LOGISTICS, WE FIND INNOVATIVE APPLICATIONS FOR ARTIFICIAL INTELLIGENCE
What can artificial intelligence achieve, how can it benefit people? Facial recognition on your smartphone, the algorithms behind Siri or Alexa – artificial intelligence is already part of everyday life, above all in the form of machine learning. For logistics, AI is akin to a revolution. It enables us to optimize supply chains which are already part of the Internet of Things . And at the operational level as well, AI offers great potential for massive labor saving. Read on to find out how.
A general and conclusive definition of the term artificial intelligence is difficult, because it depends on how you define "intelligence". Merriam-Webster defines intelligence as: "the ability to apply knowledge to manipulate one's environment or to think abstractly as measured by objective criteria". According to this, an AI must be able to understand meaning from existing data, transfer this meaning to new data and on this basis – autonomously – reach decisions on action and execute them.
That is why research into AI grapples with the question: How can we enable machines to solve tasks in ways that require the same intelligence that a human would apply?
ARTIFICIAL INTELLIGENCE IS A GAME CHANGER FOR COMPANIES, BECAUSE SO FAR WE HAVE BEEN PRODUCING DEAD DATA
Data volumes have exploded in recent years. These volumes are likely to continue to multiply in the future. In logistics, data volumes are growing across all company departments thanks to the horizontal and vertical interconnection of value creation chains. Managing this data with AI would open up massive potentials. Quite simply, a machine working with AI processes figures faster, doesn't take any breaks, and doesn't make mistakes.
"We are drowning in information but starved for knowledge," said John Naisbitt. He's right. We barely know what data we have, how we can access it, and how we can usefully use it.
An overview of the big picture is missing. The solution: AI.
ARTIFICIAL INTELLIGENCE IS THE KEY TO COMPETITIVENESS IN LOGISTICS
Currently, AI is most frequently used in the logistics industry in the form of robotic process automation (RPA). Included here are software robots. RPA helps us transfer data to an IT system.
Increasingly, logistics companies are using driverless vehicles, for example in on-site logistics. The vehicles use self-learning algorithms that recognize their surroundings, react in real time and plan efficient routes. Combined with the Internet of Things, this is a type of logistics that would have been unthinkable just a few years ago.
MACHINE LEARNING AS A FLEXIBLE BASIS FOR AI PROJECTS SO THAT (DIGITAL) INNOVATION IS NOT JUST A SPECTATOR SPORT
Data quality, structure and procurement are crucial factors for the success of AI projects. That is why we analyze data sources even before project launch so that we have a clear focus on the task to be solved. We have been using a machine learning software since June 2019. It enables all users at BLG LOGISTICS to process a wide range of use cases within a short time and without advanced data science skills.
APPLICATIONS FOR ARTIFICIAL INTELLIGENCE AT BLG LOGISTICS
In principle, AI could make all data-driven processes more efficient and therefore cost-effective for the company. The goal is always to enable data-driven decision making. At BLG, we have already realized some use cases relating to AI.
In CKD assembly in our Logistics Center in Bremen, we carried out a 100-day project in 2019 during which we successfully achieved automatic optical recognition of standard and small parts. A machine can optically capture the parts and check their weight. Then a self-learning algorithm autonomously decides whether the part matches the information from the previously scanned material number. There are also other projects in progress in which we are testing and further developing AI in operations.
Automated optical character recognition of engravings: reducing stress for our employees and minimizing errors
BLG Industrielogistik takes care of the collection, packaging and transport of turbine blades for one of our customers. Our colleagues identify the critical goods via a serial number. This number is engraved into the blade. Identifying it manually takes a lot of work because a number of factors vary: the location of the serial number on the blades, the characters and engraving types, the size and the legibility. That costs precious time, not only during checking the blades, but also in the downstream processes.
A camera technology solution to record and recognize the engravings. In combination with OCR (optical character recognition), this system reduces manual work and minimizes errors. Our experienced employees can train the system so that it learns and improves continuously. In the downstream process steps, a barcode enables identification of the turbine blades after the initial check.
Every day in accounting, we check and process a large volume of documents, above all invoices.
We already use robotic process automation (RPA) in some areas. This means we use technology to support manual tasks. However, ahead of this work there are other tedious tasks such as extracting specific contents from the documents and filling out system templates.
The goal is to simplify the monotonous extraction and administration of contents from documents. We have added an intelligent document management system to our existing robotic process automation. This tool takes care of the upstream steps. The AI system extracts pre-defined contents from specific documents so that the RPA can transfer the contents to the ERP system.
On an ever more complex employment market, recruiting is an important and multi-layered task. Especially for new locations of BLG LOGISTICS, managing a large number of interested, motivated applicants with various qualifications is a challenge. We have to read countless documents and conduct interviews. Compiling job vacancy ads is also very labor intensive.
A chatbot supplements the existing conventional recruiting instruments. This simplifies the application process and lowers entry barriers for potential applicants. The chatbot guides the applicant through the application process along different paths. During this process, the chatbot and the applicant collect the relevant information in a brief applicant profile. Then the HR department can access the profile for the further application process.