The customer wanted to increase production by adding three EOS P 396 systems to their two existing EOS P396 machines. However, the team was unsure whether the existing post-processing machines would handle the highest throughput with a one-worker shift. The AM product remained the same, which means that the workflow and the type of equipment also remained the same. The main challenge was to optimize the additional post-processing equipment and resources to have the highest throughput while keeping the cost per part as low as possible.
We supported the customer by developing a customized production model with suitable variable input parameters. Different scenarios can be generated by varying these input parameters to check the sensitivity of the throughput and cost per part. This information guides the customer in deciding the optimized scenario with the lowest additional investment to scale the AM production.
In summary, we identified the bottlenecks in the factory. By making small changes in post-processing, we increased the output by 24%, increased the margin by 124%, increased the return on investment (ROI) by 115%, and reduced the cost per part (CPP) by 18%.
The whole layout was divided into 3 areas (see figure 1):
The customer prefers having three regions to minimize the risk of cross contamination of powder. We first built a simulation model with the two existing EOS P 396 and then a second model with three additional EOS P 396 together with the above listed equipment. The customer uses a one worker shift from Monday to Friday. During the analysis process, we carefully adapted all kinds of variables such as consumables and operators for the production facility.
After optimizing the AM and powder management area, the post-processing area was the next challenging task. It involved seven different process stations with ten steps:
(*DyeMansion is part of the EOS Ecosystem)
Additionally, there were a few challenges regarding the customer workflow. For example, the blasting stations (Powershot S and C) from our partner DyeMansion should only process half of the parts produced in one build (72 out of 144 parts), in other words, two lots per build. However, for all other stations such as the DyeMansion DM60 coloring system, surface finishing, drying, and so on, all jobs need to be processed, in other words, one lot per build.
Once the original model was extended to include the post-processing area, we focused on finding the optimum number of operators. Starting with the AM optimum of 1062 jobs per year, we ran five different setups with 1-5 operators. As seen in Table 3, 4 operators would be needed for the post-processing area to have considerably higher throughput than the previous number of workers. 4 additional jobs do not justify the additional cost (not shown here) of an additional operator (848 vs. 849 jobs).
|No of operators||Jobs built through AM||Jobs produced through AM +
Table 3: No of operators for Post-Processing area and respective jobs
One solution to remove the bottleneck at the surface grinding equipment could be to add another surface grinding machine while keeping the same number of workers and shifts. After doing the necessary modification to the simulation model, we realized that adding another surface finishing machine did not completely remove production line bottlenecks but rather moved it to the DyeMansion* Powershot S. Luckily the size of the bottleneck reduced to 57 jobs or 8.226 parts. Figure 2 shows the new bottleneck and throughput.
The impact of this optimization is as follows:
The key message here is that scaling and optimizing your AM production strategy can be a complicated task. It is a unique challenge, tailored to a specific layout with different key parameters for each scenario. Not analyzing and taking your strategy into account can lead to incorrect conclusions. With our simulation expertise and 30 years of AM experience we can make a winning scaling strategy for you to achieve the highest machine utilization and lowest cost per part.