Bosch is using Industry 4.0 to increase its competitiveness
One production line, 200 different hydraulic modules
On its multi-product assembly line in Homburg, Germany, Bosch can manufacture 200 different hydraulic modules from more than 2,000 different components. Thanks to connectivity, these components are automatically ordered in time. The modules control the work and driving hydraulics in trucks or tractors, which help do things such as incline loading surfaces or lift a plow. The production line’s nine stations are connected by a smart network. Thanks to an RFID chip attached to the workpiece, the stations know how the finished product has to be assembled and what steps are necessary. This facilitates efficient production, even for small batch sizes. That flexibility is important, since some modules are requested more often than others. What is more, Bosch can produce different types of module simultaneously on the multi-product line. This cuts tooling times on machinery, which increases productivity. The work plans required for assembling the hydraulics components are automatically called up and shown on the monitors as a photo or video. The display is customized to each associate’s level of training, and shown in their native language. The aim is to offer associates the best possible support in their work. This is an example of how Bosch is successfully putting multiple core elements of Industry 4.0 into practice: distributed intelligence, rapid connectivity, contextualization in real time, and autonomous behavior. Details: http://bit.ly/1TOCbsh
Industry 4.0 boosts productivity in ABS/ESP braking-system manufacturing
Award-winning success: in less than one year, Bosch improved its productivity in the manufacture of ABS/ESP braking systems by nearly one-quarter by deploying Industry 4.0 solutions throughout its international manufacturing network. In recognition of this achievement, the Blaichach plant – which spearheaded the initiative – received the prestigious Industry 4.0 Award in 2015. One reason for this productivity increase is that Bosch collects data from the thousands of sensors that are installed along the plant’s production lines. Sensors record the movement of cylinders, the cycle times of grippers, and the temperature and pressure levels in the manufacturing process. This wealth of information is entered into massive databases, with a clear structure. And thanks to RFID (radio frequency identification) technology, Blaichach can also digitally map its internal flows of goods. The result is a computer-generated virtual representation, or “digital twin,” of the actual factory. This digital representation facilitates transparency across the entire value stream. And in turn, this transparency makes many more I4.0 solutions possible.
One of these solutions is applied in machinery maintenance: software analyzes machinery performance to spot deviations from the target state and indicate in good time when maintenance is necessary. The system helps associates detect and deal with errors by offering them instructions on how to carry out these repairs. On their tablets, for instance, associates can call up videos showing them how to replace parts. If they encounter a problem they cannot solve immediately, they can use a wireless video link to speak with experts who then assist in solving the problem remotely. All this reduces unplanned downtimes as well as increasing productivity and hence also competitiveness.
Data mining cuts the time needed to test hydraulic valves
By evaluating manufacturing data from its own facilities, the Bosch plant in Homburg, Germany, has managed to cut the time taken to inspect hydraulic valves by 18 percent. Given the frequently high level of optimization in modern manufacturing, such huge savings represent a major advance. Assuming an annual rate of production of 40,000 valves, the savings add up to 14 days per year. An analysis of the production data relating to 30,000 manufactured hydraulic valves showed that certain subsequent testing steps in the inspection process are unnecessary, provided the results of several earlier steps are positive. The outcome of those subsequent steps can be reliably predicted by analyzing the earlier steps. Pinpointing such correlations – which are generally much more complex than the example given here – saves time and money. When the number of parts runs into the millions, even savings of just a few seconds can soon add up to days, turning a few cents into millions of euros. The search for new correlations (a process called data mining) requires that, over a long period of time, companies collect and appropriately evaluate the data they generate. Bosch has been doing this for many years.
Details: http://bit.ly/21G5ZsG
Predictive maintenance of machine tools
One of the items Bosch manufactures at its plants in Stuttgart-Feuerbach (Germany) and Jihlava (Czech Republic) is high-pressure pumps for injection systems. Part of the manufacturing process for the aluminum housing involves precise drilling of holes and milling of other parts. Large machine tools are deployed in the process, whose motorized drive units are referred to as “spindles.” Each spindle weighs some 50-70 kilograms and spins at a rate of 30,000 to 40,000 rpm. Sensors record vibrations in the operation of these spindles, and software stores and evaluates the data. Whenever the system registers that the intensity of vibrations exceeds a set limit, it sends a signal to the service associate in charge. The technician can then decide if and when to replace the spindle. Maintenance becomes easier to plan, machine availability improves, and productivity rises. Continuous monitoring of machine parts such as these spindles is also referred to as “condition monitoring.” Planned servicing is called “predictive maintenance.”
Ultrasound gloves for quality assurance
The Reutlingen plant is involved in electromobility, among other business areas. Manufacture of the necessary power electronics involves many manual activities. To support its associates in this work, Bosch introduced a system that records their hand movements. The system is based on special gloves worn by the associates. Ultrasound technology helps determine the position of these gloves. In turn, this indicates if associates have carried out a hand motion correctly, and which work step is being performed at any given moment. The entire work process is displayed step by step on a screen until it has been completed. This helps improve quality assurance.
Radio signals create transparency in the flow of goods
In many of Bosch’s more than 250 plants worldwide, the company has equipped plastic crates for the internal transport of parts and finished products with RFID (radio frequency identification) tags. RFID readers are positioned at all the doors to the manufacturing shops. When a transport cart goes from one shop to another, the reader registers its tag automatically and without any need for physical contact. The result is a digital map of the flows of goods in that particular plant. At any time, the company can determine when parts will most likely arrive on the production line, when and how many finished products have to be packaged, where a specific part is located, and what the inventory levels are. The system also knows how many packaging boxes are required and can reorder these as needed. RFID technology ensures transparency in the flow of goods, as well as reducing manual effort and keeping inventory levels low. It simultaneously increases reaction speed and productivity. This is how Bosch achieves leaner logistics processes. Thanks to its use of RFID, Bosch was able to boost productivity in its Homburg plant’s intralogistics by ten percent, and reduce storage in production by nearly one-third.
China: RFID cuts inventory time by 97 percent
In the Bosch plant located in the Chinese city of Suzhou, the yearly task of taking machine inventory used to be a major undertaking. Plant 1 has four manufacturing areas, each with up to 2,500 machines, test benches, and items of measuring equipment. For ABS manufacturing alone, the inventory process used to take up to a month in some cases. Sometimes associates printed out lists to help them manually record machine inventory. Now, thanks to smart connectivity, inventory takes just four hours. All the machines and equipment items have been fitted with RFID (radio frequency identification) transponders. This allows objects to be identified without physical contact. Now, associates push RFID trolleys fitted with a laptop and antennas through the manufacturing shop. As they move along, the trolleys use RFID technology to automatically identify machines and devices. It cuts the time needed for inventory by 97 percent, or 440 man-hours.
Transporters with swarm intelligence
Engineers in Bosch’s Nuremberg plant have developed and successfully tested an AutoBod – a driverless, self-navigating transport system equipped with swarm intelligence. The two-wheeler AutoBod, which is equipped with four additional stabilizer wheels, knows when to pick up production materials that have previously been automatically ordered. It then takes these materials to the production line. Using a laser sensor, the system navigates by following a map drawn up during its first drive. It recognizes and evades obstacles, then wirelessly transmits information about them to the other AutoBods. This collective behavior relies on data about the location, electric drive charge level, and maintenance status of the various transporters. This means requests are routed to the AutoBod that is closest to the pick-up point, that is not already busy with another request, and that has enough battery charge. This kind of intelligence sets the AutoBod apart from other driverless transport systems, which are incapable of deviating from their programmed route. In contrast to conventional driverless transport systems, AutoBods do not require the installation of expensive in-plant infrastructure. The deployment of AutoBods reduces the time and effort spent on transport, frees up space, and considerably decreases inventory.
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