Close Go back Collapse all sections
Process Data set: Additive manufacturing process by Fused Deposition Modelling (FDM) 3D technology, for lab and industrial use with recycled polymers, BR 2021 (en) en

Key Data Set Information
Location BR
Geographical representativeness description Sorocaba city and region of the São Paulo State of Brazil.
Reference year 2018
Name
Additive manufacturing process by Fused Deposition Modelling (FDM) 3D technology, for lab and industrial use with recycled polymers, BR 2021
Classification
Class name : Hierarchy level
  • ILCD: Manufacturing processes
General comment on data set This dataset covers all relevant input and output flows of the represented gate-to-gate unit process. The inventory is mainly based on industry data for a pilot product scale and, where necessary, complemented by secondary data. The reference flow is one printed part with 75% infill as baseline, and all inputs and outputs are normalized for each machine operation mode. The inventory flows were parametrized for the different operation modes (stand-by, filament loading, table heating, pre-printing, nozzle heating, printing, filament unloading, and filament winder) of the 3D printer.
Copyright No
Owner of data set
Quantitative reference
Reference flow(s)
Time representativeness
Data set valid until 2019
Time representativeness description The temporal scope of all inventory data corresponds to the average data for the 01 year of measurements during 2018/19.
Technological representativeness
Technology description including background system Current technology for the FDM 3D technology process. The infill percentages were varied to analyse the influence of this parameter on the inventory results. This additive manufacturing process considered the following production modes: - Stand-by: when the printer is not operating, while its electronic panel is on. - Filament loading: it happens when the filament is loaded in the machine (filament made of recycled ABS). - Table heating: the machine spends time, normally 40 minutes, heating the table before a printing process. - Pre-printing: this mode of operation consists of a sequence of steps performed by the printer to ensure that the table is in the right place and the distance between the nozzle and the table is correct. - Nozzle heating: heating the extruder nozzle of the printer. - Printing: the mode of operation in which the parts with different infill % are printed. - Filament unloading: similar to the loading mode, but taking the filament out of the tube.
Mathematical model
Variable / parameter Formula Mean value Minimum value Maximum value Uncertainty distribution type Relative StdDev in % General comment
Printing_mode 15.78*infill +54.58 66.41499999999999 % electricity consumed per printed part, in Wh
Filament_loading_mode 2.2 NORMAL 0.04 % electricity consumed per printed part, in Wh
Consum_Total_Electricity standby_mode +filament_winder_mode +filament_loading_mode +filament_unloading_mode +table_heating_mode +printing_mode +preprinting_mode 92.96999999999998 % Total electricity consumed per printed part, in Wh
Filament_winder_mode 0.3*infill +0.8 1.025 % electricity consumed per printed part, in Wh
Infill 0.75 % [0.0 to 1.0] Infill percentage of a manufactured part
ABS_waste 0.087 NORMAL 0.08 % Corresponds to the amount of ABS chip wasted, in g per printed part
Standby_mode 0.06 NORMAL 0.01 % electricity consumed per printed part, in Wh
Filament_unloading_mode 1.1 NORMAL 0.02 % electricity consumed per printed part, in Wh
ABS_consum_Total 2260.2*Infill +5818.8 7513.95 % Corresponds to the entrance of ABS as raw material for the FDM 3D printing process, in g per batch
Preprinting_mode 0.55 NORMAL 0.01 % electricity consumed per printed part, in Wh
Table_heating_mode 21.62 NORMAL 0.45 % electricity consumed per printed part, in Wh
gd_price_waste 0.5 % This parameter was added by GreenDelta during the implementation of the ecoinvent database in openLCA. It is used by those exchanges which did not have a price specified by ecoinvent for being wastes (i.e. negative reference product), and that were considered that they should have a cost/revenue specified. The prices used for them, equal to the prices of the same product in other processes of the database, are modified by this parameter with value 0.5 (i.e. half the price of the normal product), considering that the reference product of a waste treatment process might have a lower price in reality than the same flow produced by a production process. However, you can modify this value to 0 if you prefer to consider no price for them like ecoinvent, or also 1 if you do not want to distinguish wastes from other products.
gd_price_product 1.0 % This parameter was added by GreenDelta during the implementation of the ecoinvent database in openLCA. It is used by those exchanges which did not have a price specified by ecoinvent and that were considered to be products or co-products of waste treatments (i.e. positive reference product), and that they should have a cost/revenue specified. The prices used for them, equal to the prices of the same product in other processes of the database, are modified by this parameter with value 1. However, you can modify this value to 0 if you prefer to consider no price for them like ecoinvent.
ei_price_product 1.0 % This parameter was added by GreenDelta during the implementation of the ecoinvent database in openLCA. It is used by those exchanges which did not have a price specified by ecoinvent in this specific system model, but yes in at least one of the other two system models. The prices used for them, equal to the prices of the same product and provider in the other system model, are modified by this parameter with value 1. However, you can modify this value to 0 if you prefer to consider no price for them in this system model like ecoinvent.
Heavy_metal_uptake 1.0 % Take the heavy metal emissions into account? Yes = "1", "no" = "0" (If the heavy metals direct emissions are included, put the value to "1". If the heavy metals direct emissions are excluded, put the value to "0".)
LUC_crop_specific 1.0 % Approach for LUC: If the approach is "Crop specific", put the value to "1". If the approach is "Shared responsability", put the value to "0"
temp_olca_param16 Consum_Total_Electricity 92.96999999999998 %
temp_olca_param17 abs_waste 0.087 %
temp_olca_param18 abs_consum_Total 7513.95 %
LCI method and allocation
Type of data set Unit process, black box
LCI Method Principle Other
Deviation from LCI method principle / explanations Attributional method
Modelling constants No allocation rules were used for this dataset, as well as any of the transportation activities for the inputs. This is a G2G product system type.
Data sources, treatment and representativeness
Data cut-off and completeness principles Input flows with less than 1% mass representativeness were disregarded from the system boundaries.
Deviation from data cut-off and completeness principles / explanations None.
Data selection and combination principles Primary data were collected for the FDM 3D production system. See 'Geography' and 'Technology' scopes for more details.
Deviation from data selection and combination principles / explanations None.
Data treatment and extrapolations principles All the input/output data were converted to the functional unit by using the UPLCI methodology developed by Kellens et al. (2012a,b). All the collected input/output flows followed the "in-depth assessment" approach proposed by the UPLCI methodology.
Data source(s) used for this data set
Sampling procedure Average data for historical series of data from 2018/19. All the primary data were 'in loco' mesuared, or calculated based on reports of consumptions of resources and emissions at the shop-floor area in the region of this study.
Data collection period See 'Time' scope for more details.
Completeness
Completeness of product model No statement
Commissioner and goal
Project GARCIA, FABRICIO LEON. Comparação entre moldagem por injeção e a manufatura aditiva utilizando materiais poliméricos reciclados: um estudo de ACV. Universidade Federal de São Carlos, campus Sorocaba, Sorocaba, 2018. 105 f.
Intended applications This process LCI can be used for any types of LCA studies in the area of manufacturing processes.
Data generator
Data set generator / modeller
Data entry by
Time stamp (last saved) 2023-02-09T10:26:35.745-02:00
Data set format(s)
Data entry by
Publication and ownership
UUID 867db473-5385-43e0-a6ea-3c1be2f71c92
Date of last revision 2023-02-09T10:26:10.321-02:00
Data set version 00.00.093
Unchanged re-publication of
Owner of data set
Copyright No
Access and use restrictions The data set can be used free of charge by anybody to perform LCA studies, to distribute it to third parties, to convert it to other LCA formats, to develop own data sets, etc.

Inputs

Type of flow Classification Flow Variable Mean amount Resulting amount Minimum amount Maximum amount
Product flow
Energy carriers and technologies / Electricity temp_olca_param16 1.0 MJ0.33469199999999993 MJ
General comment Total electric energy consumed by the machine tool over the five production modes.
Product flow C:Manufacturing / 20:Manufacture of chemicals and chemical products / 201:Manufacture of basic chemicals, fertilizers and nitrogen compounds, plastics and synthetic rubber in primary forms / 2013:Manufacture of plastics and synthetic rubber in primary forms temp_olca_param18 1.0 kg7.51395 kg

Outputs

Type of flow Classification Flow Variable Mean amount Resulting amount Minimum amount Maximum amount
Product flow
1.0 kg1.0 kg
General comment The total amount of parts (output) after the printing process.
Waste flow
E:Water supply; sewerage, waste management and remediation activities / 38:Waste collection, treatment and disposal activities; materials recovery / 382:Waste treatment and disposal / 3821:Treatment and disposal of non-hazardous waste temp_olca_param17 1.0 kg0.087 kg
General comment Represents the amount of ABS chips wasted from the process.