Electronics manufacturer controls its production with plant simulation

100 percent quality, delivery performance and more

Electronics can be produced in Germany at competitive market prices only as long as the manufacturing process is continuously improved. For this reason, the Siemens Manufacturing-Karlsruhe (MF-K) plant introduced the Plant Simulation solution in the Tecnomatix® portfolio to support the company’s continuous improvement process. Today, not only are production lines simulated before they are built, but workers actually control daily production using the software.

“Our mission is 100 percent quality, 100 percent delivery performance and 100 percent waste-free,” says Bernd Schmid, plant manager at Siemens MF-K. “That means we want to manufacture our products with as few resources as possible. This requires that the manufacturing processes operate how we envision them to. Plant Simulation is a big help to that end.” For its consistent use of simulation software, Siemens MF-K was recently named one of the winners of “100 Places for Industry 4.0 in Baden-Wuerttemberg.” The jury of experts recognized the company for practical concepts that intelligently combined production and value chains.

Siemens MF-K is a prime example of the challenges that manufacturing companies are mastering with the help of Industry 4.0: a high degree of variance, continuously shrinking batch sizes and fluctuations in order volume that are increasingly difficult to predict. For example, the plant manufactures 125,000 industrial personal computers (PCs) per year, but the average batch size per order is a mere 1.8. From 90 million different possible variations to choose from in the configurator, approximately 10,000 are actually used. The life of an industrial PC generation is 2.5 years − short compared to the proven SIMATIC controllers, but long compared to industrial communications where a new product has to be produced every two days.

Today’s industrial customers behave like consumers of PCs: they want to configure their product online and if possible have it delivered by the next day. To be able to respond to these individual customer requirements and fluctuations in the order volume, Siemens MF-K will completely restructure its production in the next months. The effort is “like open-heart surgery,” and will also be simulated using Plant Simulation. To avoid collisions while reorganizing production, the manufacturing lines, which so far only exist as 2D models, must first be remodeled in 3D using the Line Designer capabilities of NX™ software.

Continuous improvement processes are a tradition at Siemens MF-K. “We are proud of the increase in business value to the tune of nine million euros per year achieved by the suggestions for improvement by employees,” emphasizes Schmid, who was personally involved in the search for a solution for the digitalization of production planning. “Plant Simulation is a beacon of our overall digitalization strategy to improve every day with Industry 4.0.”

No new capital investment required

The vision of creating a digital model of the plant by using Plant Simulation was born four years ago after a presentation by colleagues from Siemens Digital Industries Software. As a pilot project for testing the software, Siemens MF-K chose a production line that had reached its capacity limit and was actually due to be replaced. In this production line, through-hole technology (THT) elements are soldered selectively to printed circuit boards that are already fitted with other components. “The difficulty is that different products, each with its own processing time for the individual processing steps, are processed in the production line simultaneously,” explains Bernd Bastian, one of the first Plant Simulation users at Siemens MF-K.

“By optimizing the preparation of product combinations and the line balancing of the process steps in the system, Siemens MF-K was able to increase the output by so much that an investment in a new production line was no longer necessary,” says Markus Fischer, head of Siemens MF-K’s continuous improvement processes in Karlsruhe. “The investment would otherwise have cost the company a six-figure sum. Based on the positive experience with the pilot project, the plant management decided to implement the software enterprise-wide to optimize production.”

Re-creating the existing production cells, production lines and manufacturing cells using Plant Simulation cost Bastian and his colleagues some time. While the software includes libraries of standard objects for modeling assembly lines and material flows or value streams, it must still be adapted to the requirements of electronics manufacturing. So far, the three application users have re-created approximately 60 to 70 percent of the existing plant production, facilitated by the equipment’s re-usable modules. Fischer explains, “Thanks to our modular system, the basic model of a production cell currently takes about two hours to complete.”

Simulation of entire production lines

To achieve high quality, Siemens MF-K uses a one-piece flow; that is, one employee is responsible for one specific workpiece or device from the first step in the assembly to the last when it is packaged and shipped. In a production line, there are always multiple devices in a single product family; due to their variance, they can have very different assembly times. “The biggest challenge is line balancing,” explains Bastian. “The manual and automated processes have to be coordinated, so that all devices can be manufactured on the same line without waiting times.”

Building a new production line used to be a very time-consuming process. First, cardboard boxes and wooden frames were used by engineers to plan the individual work steps. After several trial-and-error runs, a real production cell was created in a workshop and a test run was performed. Once the production cell reached 80 to 85 percent maturity, real production could be started and then optimized in real-time operation. “The entire process lasted about three months,” Fischer recalls. “Today, we’re able to do it in three weeks, because we can simulate everything on the computer that we previously had to do in the workshop, and we can try out different scenarios in the simulation software. As soon as the concept has reached the workshop, it is much more sophisticated than before, so that the workers only have to make some small final adjustments.”

Using Plant Simulation, engineers simulate not only individual production cells, but also entire production areas. “In the next step we want to re-create the complete material flow in the software so that we can define the order volume and then see where the bottlenecks are throughout the entire production process,” adds Bastian. In addition to the order requirements, work schedules, work space requirements with assigned times for man and machine and shift schedules with recorded working times are imported into the simulation model from the SAP® enterprise resource planning system to simulate production under real working conditions.

Simulation experts from Siemens MF-K are currently working to incorporate parts of the control logic from SAP into the simulation models.

This will enable them to simulate the preparation of the components for the individual work steps based on deadlines and defined quantities through backwards scheduling, as Bastian’s colleague Anne Stetzler explains: “We will be able to use the simulation models to optimize the scheduling logic − something that no one would dare try on the live system.”

Savings in the six-figure range

Optimizing production within the framework of continuous improvement processes has yielded measurable cost savings in the six-figure range in the last three years, not including the effects of process optimization on day-to-day operations.

Siemens MF-K does not use the simulation models exclusively for strategic tasks such as restructuring or creating new production lines, but for production control in the operating business. “Production line managers and workers simulate how best to manage the production volume of tomorrow through their production cells,” says Fischer. “They can see, for example, if they will need more workers or how the process will change if they remove a worker. We have even programmed an optimization algorithm that recommends the optimal ordering sequence.”

One particular highlight is the fact that the employees optimize their own work in the production line with Plant Simulation. For this, the key users have programmed an intuitive user dialog for the input of simulation parameters; for example, users do not need to worry about the complex rules. “Since everyone has realized how reliably the simulation works, no one would want anything else,” concludes Fischer. “The employees immediately understand the steps and quickly see where they can improve something else.”