Challenges in connected supply chains Globally networked supply chains are increasing. Their added value often shows not only regionally on site. The problem: Many supply chains of companies have grown historically. As a result, many supply chains are poorly networked. Efficiency and effectiveness are missing. Delivery bottlenecks as a challenge in mechanical engineeringThe more complex a plant is, such as a production line, the higher the risk in the supply chain. What should a mechanical engineering company do if the crucial parts for commissioning the system are missing? At the same time, customers want quick set-up or (very problematic in the event of supply bottlenecks) quick conversion. Every day that the systems are not running costs money. Solutions in networked supply chainsIn addition to logistical networking, digital networking within the global supply chain is becoming more and more important. The more complex the processes become, the more helpful is a digitized control of all information and material flows. From the raw material manufacturer to the end customer in the B2B area, the common occurrence of high inventories and delivery bottlenecks can be eliminated through greater transparency. This transparency enables targeted control of the supply chain and all potential for optimization.

Artificial intelligence in the mechanical engineering industry Everyone is talking about AI. In the field of mechanical engineering, the possibilities of AI are almost unlimited. The possible increases in efficiency are particularly interesting for customers, for example through greater automation of production or the development of brand-new products. But what does the buzzword AI mean?   What is artificial intelligence?Computer scientists have been working on the topic of AI for 50 years. In many cases, artificial intelligence is implemented using complex statistics. In the sub-area of machine learning, the algorithm finds statistical relationships between given characteristics in learning data. The algorithm then applies this data to similar external data. The latest achievement is called Deep Neural Networks (Deep Learning). These networks, which were set up in 2015 with the help of Google, enable artificial intelligence to learn relevant characteristics on its own. In this way, a robotic arm can find its own optimal movement and theoretically even its task in a specific environment.   How can AI be used in manufacturing and automation?The possibilities for using AI range from predictive maintenance and simplifying simulations to complex automation in production. Let’s look at the opportunities using the example of predictive maintenance: With the help of simple machine learning, statistical knowledge can be generated during maintenance. When does which part usually break and how does it bring production to a standstill during the repair? Thanks to AI, predictive maintenance systems can be serviced at favorable times before a defect occurs.   The possibilities of artificial intelligence continue to grow every day. Predictive maintenance will get more and more important in the mechanical engineering industry.

The history and development of CNC Milling The CNC milling industry has a long history. The year 1818 is the year of birth, when the American Eli Whitney developed the first milling machine for metal. Around 34 years later, on March 14, 1862, Brown & Sharp finally delivered the first universal milling machine. This new technology developed very quickly. At the end of the century, the first special machines for specific parts such as gears came onto the market, the accuracy of which was already surprisingly high. The next big step followed during the 1950s. The American John Parsons designed the first NC-controlled milling machine (NC = Numerical Control). The Brendix company adopted this technology in 1954 and developed an NC machine with over 300 electron tubes, controlled with punch cards. The NC program used here, which contained the sequence of individual pieces of information, can be described as the direct predecessor of the CNC program. Five years later, NC machines arrived in Europe, where they started an industrial revolution. It wasn’t long before companies were retrofitting many older milling machines with numerical controls. However, this was just the beginning. In the following years the technology became much more sophisticated. Many machines received upgrades for a more stable design or for roller guides. The gradual automation of milling machines began in 1965. IC technology was used for the first time in 1986, and microprocessors were used for the first time in 1976. The machines were no longer controlled directly on the hardware, but increasingly via software. The programming of these new CNC machines had to be done laboriously by hand. Even small mistakes could have a devastating effect. Shortly before the turn of the millennium, however, this problem was also solved since the programs were created directly from the CAD/CAM system. This innovation led to today’s CNC machines and their simple, precise control.

Industry 4.0 – The manufacturing of the future The term Industry 4.0 is omnipresent. But what is behind this buzzword and what does it mean for the industry of tomorrow? To clarify this, one should first understand where the term comes from. Industry 4.0 means that there have been three major industrial revolutions so far and another one, the fourth, will now follow. The first revolution came with the invention of the power loom in 1784. Mechanization was the key technology. In 1870, industry was electrified with the first assembly line. In 1969, the first programmable logic controller started the age of automation. What is the next step now? It is the networking of all robots, AIs and people that leads to a highly efficient production process. The basic requirement for this is the collection of data. Because only if all production processes are meticulously recorded and saved are intelligent systems able to uncover weak points and optimize the processes in the next step. Industry 4.0 also means recording and analyzing data. This recording is made possible by modern systems with many sensors. After the data has been recorded, an AI performs the analysis, with humans playing a supporting role. Since all robots and devices are networked with each other, optimizations can be implemented immediately. In addition, unexpected errors or delays can be reacted to quickly and effectively, since artificial intelligence can adapt all processes in real time. So will the factory of the future be deserted? No, the fear of some people that robots and AIs will take away our jobs in the future is unfounded. Although robots and AIs will soon take over many tasks, new jobs will be created for people. Ultimately, there is close cooperation between man and machine, with the machine relieving humans of tedious and monotonous work, while humans control the processes, maintain the machines, and do detailed work. Human tasks are thus shifted from the physical to the cognitive. The transition to Industry 4.0 is already happening. Because every day more data is recorded, more robots are connected, and more AIs are activated. This process is very welcome. On the one hand, highly qualified and well-paid jobs are created, on the other hand, customers can benefit from lower prices because the manufacturers achieve considerable savings through the various optimizations.

Customers are increasingly demanding individualized products. Companies that can produce individual products economically and competitively in small quantities thus gain a competitive advantage. But what is the appropriate manufacturing process for this? One important solution is value stream kinematics.   Kinematics means the movement, for example of a robotic arm, in terms of location, time, velocity and acceleration. With value stream kinematics, several kinematics, such as industrial robots, are placed in a modular grid. With the help of value stream kinematics, an economical production of individualized industrial and consumer goods is possible.   Standard kinematics based on vertical articulated arm robots are intended to map corresponding production flows. The robot takes on additional tasks such as assembly, machining processes, cutting, and joining processes, etc. The production layout is supplemented by a grid of zero-point clamping systems.   In order for standard kinematics to be able to solve extended tasks, they have to be optimized compared to conventional vertical articulated arm robots. This applies to the flexibility of movement. By using standard kinematics, production can be flexibly rearranged as required. Additional systems do not have to be purchased. The value stream kinematics can radically change today’s production landscape. For example, it can make large production halls superfluous and prevent long supply chains or production downtimes due to supply bottlenecks. The structure and rearrangement of the production system can be planned virtually thanks to software support for the hardware. The requirements for the production process are determined using a CAD model of the end product. Thus, the number, arrangement, and positioning of the kinematics as well as the necessary couplings and end effectors can be determined in the last process. The optimal production process is validated by simulating all individual processes and the whole production system. This leads to time and cost-optimized production planning. Figure 2: Virtual production planning – from the 3D model to the production concept

The lightweight Aluminum Aluminum is the perfect material for many different applications. Aluminum has amazing properties: it’s light, strong, and sustainable! After oxygen and silicon, aluminum is the third most common element in the earth’s crust. So, there is more aluminum than iron in this world. This means that the deposit, based on today’s requirements, will be sufficient for generations. The People’s Republic of China is by far the world’s largest aluminum producer. Aluminum is lightweight. At around 2.7 g/cm3, aluminum weighs two-thirds less than steel. This makes further processing and application easier and reduces energy consumption during transport. Because of its low weight, aluminum is often the most economically sensible choice of material.   Aluminum foil in every household Aluminum foil reflects both heat and light and is impermeable. This means that no taste, aroma, or light penetrates inwards or outwards. This property makes aluminum foil perfect for food preservation. It is therefore often integrated as a barrier layer in plastic packaging films.   Formability and Alloys The easily deformable aluminum is used in various everyday products: in beverage cans, housings, bicycle frames or kitchen utensils. Aluminum can be easily deformed and processed (e.g., by extrusion or die-casting) both when it is cold and when it is warm. Various alloys are produced to further improve the properties of aluminum. The most used elements in aluminum alloys are magnesium, silicon, manganese, zinc, and copper. For example, they improve heat treatment, solderability and weldability, tensile strength, and corrosion resistance.   Corrosion resistance Aluminum reacts with oxygen in the air to form a protective oxide layer that resists corrosion. For this reason, aluminum is often used bare and generally does not require any surface treatment. If you want to change or improve the corrosion resistance and the mechanical properties, the material can be anodized. In the anodizing process, the oxidation layer is deliberately brought about by anodic oxidation. In addition, a specific coloring is possible with this process. Other processes, such as hard anodizing, can be used to make the material more wear resistant.   Infinitely recyclable Few materials are as easy to recycle as aluminum. Just 5 percent of the energy used to produce the aluminum is enough to recycle it. In fact, 75 percent of all aluminum ever produced is still in use.