The Impact of Automation on 3D Printing
Production Costs and Throughput
The Cost of Production for 3D Printing using FFF or FDM Methods:
One question that we are often asked is: What makes up the cost of 3D print production and what factors are responsible for driving that cost down to improve industrial adoption?
Improving uptime and reliability by reducing machine failures is the most important aspect of driving the cost of 3D print production down. This finding is repeatedly reinforced by the data gathered across ten unmodified FDM printers during a span of six months and over 30,000 printing hours in our San Diego production facility as will be demonstrated throughout this report.
“What makes up the cost of 3D print production and what factors are responsible for driving that cost down to improve industrial adoption?”
65.9% – nearly two thirds of all technician time is spent on the following tasks which can be reduced to near-zero with automation:
- 25.5% of billable time is spent on fixing printers that need to be recalibrated after failed prints or due to lacking control systems
- 21.3% spent on order documentation prep
- 10.6% on software preparation (loading settings, generating machine code, etc.)
- 8.5% on part removal
SD3D has developed modular subsystems which can be adopted by OEM’s into their existing products’ tool chain to plug-and-play with our automation platform. The following failure modes are either removed or majorly reduced from the technician workflow when using our automation platform: order preparation, software preparation, part removal and fixing failures.
3D Genie is SD3D’s prototype and represents our current development status to demonstrate fully automated 3D printing using our beta automation platform with tested modules including ABE, CAP, Filtracker, Printelize and the SD3D SCADA App. In the graph below we compare the failure rate of 3D Genie to standard off-the-shelf desktop 3D printers:
Failure modes categorized and frequency of occurrence:
For the calculations made throughout this review, software and general user errors were omitted as an effort to provide a controlled baseline for the forthcoming comparisons. By looking at the Fleet Failure Rate chart, there is a clear statistical improvement to print success rates when adopting the SD3D automation platform.
“average failure rates of approximately 25.3% for off-the-shelf systems”
This reduction in failures was accomplished by systematically implementing a modular control system capable of communicating with a common cloud based SCADA platform to either eliminate or drastically reduce these failure modes (shown above) through automation and machine learning. Compared to the baseline average failure rates of approximately 25.3% for off-the-shelf systems (considering all factors except software and user errors) – our 3D Genie prototype was capable of providing sustained production with average failure rates at 5.3% and repeatability exceeding 98% (ie. the likelihood of properly printing an identical geometry over and over again with the same material).
Variable Cost of Production:
Summing the values from the tasks shown in the graph above, the labor cost per printing hour ranges between $0.39 per printing hour with full automation and $1.10/hr without any automation for open source printers.
Based on 30 cc/hr output extrusion rate and $25/kg generic retail material cost; cost per hour in material is $0.75/hr. with an industry standard failure rate of 25.3% and assuming the material used in those failed prints is not recoverable, the cost of material production raises to $0.94/hr. With closed source printers such as the Fortus production line made by Stratasys, the material cost will on average be much higher at around $250/kg. with an effective material consumption cost of $7.5 per hour.
Basing the above on the 30cc/hr output rate, the cost of just labor and raw material for each kg of parts produced using generic materials comes to $39.67 per kg with our automation platform and $68 per kg without our platform. The cost of production without our platform and using proprietary materials is approximately $286.68 per kg. However, to understand the full cost of production we must also include electricity and space as well. To do that we will settle on average values between the different printer models and apply them to each category.
Using a $0.15/kWh electricity rate and 600W average continuous power draw from the printer and support equipment, the cost of energy for each printing hour is $0.09/hr. With applicable failure rates accounted for (25.3%), that effective rate reaches $0.113/hr. Based on the 30cc/hr output rate, that comes to an additional $3.76/kg when not using our platform and $3.25/kg when using our platform. Our SCADA application has been shown to be able to save approximately 30% on factory level energy usage by exploiting account specific discounts or avoiding peak charging. Therefore, the average energy usage cost with and without our platform is closer to $2.76/kg. and $4.89/kg. respectively.
To account for space, we will base our calculations on each printer effectively requiring 80 sqft and the cost of space being $0.50/sqft/mo. Printers on the SD3D platform are shown to have an improved uptime by approximately 38% due to the lower failure frequency and ability to auto eject parts while unattended. That corresponds to the following costs per kg produced based on the 30cc/hr extrusion rate: $1.16 with our platform and $1.85 without our platform
The true combined variable cost of production for space, energy, material and labor costs are therefore $43.59/kg with our platform and $74.83/kg without our platform when using generic materials and open source 3D printing systems. When using proprietary materials such as with the Fortus line of printers by Stratasys without our automation platform, costs can exceed $293.42/kg in production. By using our automation platform, these materials may be substituted with generic alternatives without risking any loss in print quality or reliability.
As shown in the graph above, our automation platform and modular subsystems save an estimated 42% to 85% in variable costs when compared to existing production 3D printing variable costs.
Apart from looking at the difference in these systems purely in the context of production cost, we can also look at the impact on production output – or throughput. To do that we will take a look at nine different printer models and measure the throughput with and without the use of our automation platform:
“increase production output by 80%… while simultaneously reducing variable production costs by up to 85%”
Based on this graph we see that the average throughput increase when implementing our automation platform across these printer models is approximately 80%. Therefore, the SD3D automation platform has been shown to increase production output by 80% on average while simultaneously reducing variable production costs by up to 85%.
Full Cost of Production Over Printer Life:
To put the benefits of higher throughput coupled with lower production cost into full perspective, let us consider the following use-case scenario in which we set the effective operational lifespan of each printer compared to be three years:
Objective: Produce as many parts as possible with volume of 10cc over three years.
The following chart shows the results of that analysis as well as the number of parts produced by end of life with the German RepRap X400 being the only machine connected to the SD3D Automated Additive Manufacturing Production Line (AAMPL). The following charts have fully amortized the capital investment into the cost of production over three years:
On a cost-per-part basis over the course of the printer life, the cost savings capable with automation become very apparent. As we can see in the graphs above, the AAMPL system provided by SD3D saves 59-94% vs. competing prototyping and production solutions over the lifetime of the investment.
“the AAMPL system provided by SD3D saves 59%-94% vs. competing solutions.”
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