WO2023140859A1

WO2023140859A1 - Reference values of parameters for stages of 3d printing

Info

Publication number: WO2023140859A1
Application number: PCT/US2022/013346
Authority: WO
Inventors: Prateek Kumar SIKDAR; Amit Kumar; Prakash Reddy; Utkarsh SIDDU
Original assignee: Hewlett-Packard Development Company, L.P.
Priority date: 2022-01-21
Filing date: 2022-01-21
Publication date: 2023-07-27

Abstract

Examples techniques for determining a reference value for parameters of a three-dimensional (3D) printing process are described herein. Measured values of a parameter are received from each of a first batch of print jobs, the measured values corresponding to a plurality of stages of a phase of the 3D printing process. Based on the measured values, a reference value for the parameter for each of the plurality of stages of the phase of 3D printing process is determined.

Description

REFERENCE VALUES OF PARAMETERS FOR STAGES OF 3D

PRINTING

BACKGROUND

[0001] Three-dimensional (3D) printers are employed in additive manufacturing processes, also known as 3D printing. In 3D printing, a 3D object, or any part thereof, is fabricated by laying down successive layers of material one on top of each other. To form different objects or parts thereof, the 3D printers may utilize a variety of print materials, each possessing different properties. The different objects and the various layers therof, may be printed of the same or different material by varying parameters, such as temperature and printing speed of the 3D printers.

BRIEF DESCRIPTION OF FIGURES

[0002] A detailed description is provided with reference to the accompanying figures, wherein:

[0003] Figure 1 illustrates a network environment implementing a system for determining reference ranges for parameters of a three- dimensional (3D) printing process, in accordance with an example implementation of the present subject matter;

[0004] Figure 2 illustrates a system for determining reference ranges for parameters of a 3D printing process, in accordance with an example implementation of the present subject matter;

[0005] Figure 3 illustrates a system for determining reference ranges for parameters of a 3D printing process, in accordance with another example implementation of the present subject matter;

[0006] Figure 4 illustrates a graphical representation of reference ranges for a parameter for a printing phase of the 3D printing process, in accordance with an example implementation of the present subject matter; [0007] Figure 5 illustrates a graphical representation of a deviation score calculated for a plurality of parameters for four batches of print jobs, in accordance with an example;

[0008] Figure 6 illustrates a method to determine reference values for parameters of a 3D printing process, in accordance with an example implementation of the present subject matter;

[0009] Figure 7 illustrates a method to determine reference values for parameters of a 3D printing process in accordance with another example implementation of the present subject matter; and

[0010] Figure 8 illustrates a computing environment implementing a non-transitory computer-readable medium for determining reference ranges for parameters of a 3D printing process performed by a 3D printer, according to an example implementation of the present subject matter.

DETAILED DESCRIPTION

[0011] Three-dimensional (3D) printers may sequentially deposit materials in layers onto a material bed of a 3D printer to fabricate a 3D object. In a 3D printing process, a first material-layer is formed, and thereafter, successive material-layers or parts thereof are added one by one, wherein a current material-layer is added on a pre-formed materiallayer, until the 3D object is fabricated. Various parameters, such as operational parameters of servo motors of the 3D printer, operating temperature, and material properties may be varied for different layers of the 3D object to be printed by the 3D printer. The values of these parameters may also be varied for different phases of the 3D printing process, such as warming, printing, cooling, or curing.

[0012] To ensure consistency in the quality of 3D objects printed by execution of jobs by different printers, or by the same printer over a period of time, these parameters are monitored during the 3D printing process. For the monitoring, key performance indicators (KPI) that indicate acceptable limits for the respective parameters are relied upon. Among other factors, KPI limits’ violations are considered as a potential cause while performing root cause analysis of print defects in 3D objects. A deviation in a value of a parameter for a layer of a 3D object being printed from the corresponding KPI may result in a poor quality of that layer leading to a defect. The resulting defect may also affect the subsequent layers being printed, thereby causing the 3D object to have undesired quality.

[0013] Generally, the KPI limits for operational parameters of the 3D printers and material properties are set based on domain knowledge and intuition of R&D engineers. The KPI limit for a parameter is defined as a range that is constant for a print job throughout a phase of the 3D printing process, such as warming, printing, cooling, or curing phase. Also, generally, 3D printing monitoring techniques do not provide for monitoring of the parameter in reference to the KPI limits that correspond to various stages in a phase of the 3D printing process. For instance, monitoring of the parameter on a layer-by-layer basis in the printing phase is generally not enabled. Thus, such techniques for monitoring the 3D printing process may not be effective for anomaly detection.

[0014] The present subject matter relates to examples techniques for monitoring 3D printing processes. In an example, a method for monitoring a 3D printing process comprises determining reference ranges for parameters involved in a 3D printing process. According to an example of the present subject matter, measured values of a given parameter are obtained for a plurality of stages of a first phase of the 3D printing process from a set of print jobs. Similarly, measured values of the parameter for a plurality of stages of a second phase of the 3D printing process for the set of print jobs are obtained. A stage may be considered as a point in a phase of the 3d printing process at a time instance.

[0015] Based on the measured values obtained for the first phase and the second phase, a first set of reference values for the parameter for a plurality of stages in the first phase and a second set of reference values for the parameter for a plurality of stages in the second phase are determined. In an example, the measured values of the parameter obtained for the plurality of stages of the first phase and the second phase may be provided to a statistical model as input. The model may generate a stagewise reference value range or reference value for the parameter for the respective phase as output. For instance, for the printing phase, wherein a stage corresponds to a layer from amongst the plurality of layers of a 3D object, the model may define a reference range of the parameter for the respective layers. Thus, for a parameter, for example, ZPIatformMotor signal, the range may be determined to be 2.4 to 2.6 for layer ‘n’ while the range maybe 2.5 to 2.7 for layer ‘n+x’. The parameter ZPIatformMotor signal may be understood as a signal of a motor of a 3D printer which drives a printing platform of the 3D printer in z-direction as the 3D printer executes a print job.

[0016] Once the reference ranges of a parameter for the plurality of stages of a phase have been defined, new print jobs may be monitored based on the reference ranges and a deviation for the parameter at each of the plurality of stages may be indicated. For instance, referring to the previous example, if during printing of layer ‘n+x’ of a new job, the ZPIatformMotor signal deviates from the range 2.5 to 2.7, an alert may be generated.

[0017] For each phase of the 3D printing process, the reference range for the parameter may vary for different stages of the respective phase.

[0018] Estimation of the reference ranges for the parameter at various stages during the progression of the different phases of the 3D printing process enables monitoring of the parameter on stage by stage and phase by phase basis. Further, since the reference ranges are determined based on the analysis of execution of a batch of print jobs rather than the subjective inputs based on domain knowledge and intuition of R&D engineers, a narrow and specific reference range is determined which is more effective for anomaly detection in a 3D printed part.

[0019] The present subject matter is further described with reference to the accompanying figures. Wherever possible, the same reference numerals are used in the figures and the following description to refer to the same or similar parts. It should be noted that the description and figures merely illustrate principles of the present subject matter. It is thus understood that various arrangements may be devised that, although not explicitly described or shown herein, encompass the principles of the present subject matter. Moreover, all statements herein reciting principles, aspects, and examples of the present subject matter, as well as specific examples thereof, are intended to encompass equivalents thereof.

[0020] The manner in which the systems and methods are implemented are explained in detail with respect to FIGS. 1 -8 While aspects of described systems and methods can be implemented in any number of different electronic devices, environments, and/or implementations, the examples are described in the context of the following system(s). It is to be noted that drawings of the present subject matter shown here are for illustrative purposes and are not drawn to scale.

[0021] Figure 1 illustrates a network environment implementing a system 100 for determining reference values for parameters of a three- dimensional (3D) printing process, according to an example. The system 100 may be communicatively coupled to one or more 3D printers 102-1 , 102-2, ... and 102-n, that may perform the 3D printing process. Examples of the 3D printers 102-1 , 102-2, ... and 102-n, may include, but are not limited to, fused deposition modeling (FDM) printers, multi-jet fusion (MJF) printers, and selective laser sintering (SLS) printers. Examples of the system 100 may include but are not limited to, computing devices, such as desktop computers, personal computers, laptops, and servers.

[0022] In an example, the system 100 may include a key performance indicators (KPI) engine 104 and a quality control engine 106 as depicted in Figure 2. The key performance indicators (KPI) engine 104 and the quality control engine 106 may be implemented as a combination of hardware and programming, for example, programmable instructions to implement functionalities of the respective engine(s). In the examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the engine(s) may be processor-executable instructions stored on a non-transitory machine- readable storage medium, and the hardware for the KPI engine 104 and the quality control engine 106 may include a processing resource to execute such instructions. In an example, the processing resource may include microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any other devices that manipulate signals and data based on computer-readable instructions. In the present examples, the machine- readable storage medium may store instructions that, when executed by the processing resource, implement the KPI engine 104 and the quality control engine 106. In such examples, the system 100 may include the machine- readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system 100 and the processing resource.

[0023] In other examples, engine(s) of the system 100, including the KPI engine 104 and the quality control engine 106, may be implemented by electronic circuitry. The engine(s), amongst other things, include routines, programs, objects, components, and data structures, which perform particular tasks or implement particular abstract data types.

[0024] The 3D printers 102-1 , 102-2, ... and 102-n, may manufacture a 3D object from a digital file. The digital file may be a type of file that can be read by the 3D printers 102-1 , 102-2, ... and 102-n, for execution of the corresponding 3D print job. The digital file may include a 3D model of the 3D object to be printed by carrying out a 3D printing process that involves various phases such as warming, printing, cooling, and curing. During the printing phase of the 3D printing process, a 3D object is created as a sequence of layers by depositing a layer of printing material on a previously formed layer. A layer represents a cross section of the 3D object.

[0025] Each of the 3D printers 102-1 , 102-2, ... and 102-n, may include a plurality of sensors, such as humidity sensors, ambient temperature sensors, printhead sensors, thermal chamber pressure sensors, carriage pressure sensors. Various parameters, such as values corresponding to signals obtained from these sensors, as well as signals from other components, such as servo motors of the 3D printers 102-1 , 102- 2, ... and 102-n, are set in accordance with the print job and monitored throughout the 3D printing process. Also, properties of materials, such as temperature or elasticity, used by the 3D printers 102-1 , 102-2, ... and 102- n, for printing the 3D object are monitored.

[0026] A parameter is monitored with respect to a key performance indicator (KPI) limits which indicate limits or reference values for the parameter. In accordance with on example implementation of the present subject matter, for each phase of the 3D printing process, reference range of the parameter may vary at different time instances as the phase progresses. Accordingly, in an example, the system 100 determines reference values or KPI limits for the various parameters involved in 3D printing process.

[0027] In an example, to determine a reference value of a given parameter, a first set of print jobs performed by the 3D printers 102-1 , 102- 2, ... and 102-n is monitored. The KPI engine 104 receives measured values of the parameter for each of the first set of print jobs from the 3D printers 102-1 , 102-2, ... , and 102-n. The measured values correspond to a plurality of stages of a phase of the 3D printing process of the first set of print jobs. For example, for a phase of the 3D printing process, a stage may be a time instance along the phase from a time of initiation (TO) to an end time (Tn) of the phase, such that a stage may correspond to the progression of the phase. In an example, a stage of the phase may be represented as a percentage of completion of the phase. For instance, in a curing phase, wherein the excess solvent is removed from the layers of the 3D object, various stages, such as stages 1 to 10 may correspond to time instances of 10%, 20% ....100% of volume V of solvent removed from the 3D object. In another example, for a printing phase, a stage may be indicative of a layer or a set of layers of a 3D object being printed as part of the 3D printing process.

[0028] In an example, the KPI engine 104 may use a statistical model to determine the reference values for the plurality of stages based on the measured values of the parameter of the first set of print jobs. For example, if the phase is printing and the first set of print jobs comprises 30 jobs, each comprising 2000 layers, then the KPI engine 104 receives 30*2000 (=60000) measured values of the parameter, for example, ZPIatform Motor PWM signal, 30 measured values for each layer. Based on the measured values, the KPI engine 104 may determine reference values for the parameter for plurality of stages of the phase of the 3D printing process. Referring to the previous example relating to the printing phase, the KPI engine 104 may determine a reference value for the parameter, ZPIatformMotor PWM signal, for a layer of the printing phase based on the 30 measured values of the parameter received corresponding to that layer from the 30 print jobs.

[0029] Similarly, in another example, if the first set of print jobs comprises 20 print jobs in the curing phase, and during the progress of the phase in a time period of TO to Tn, the parameter, the percentage of volume of excess solvent removed, is recorded at 1000 ime instances, then the KPI engine 104 receives 20*1000 (=20000) measured values, with 20 measured values for each stage. The KPI engine 104 may accordingly determine a reference value for a stage of the curing phase based on the 20 measured values of the parameter recorded from the 20 jobs received corresponding to that stage. Thus, for a given phase, a set of reference values is determined, wherein each reference value corresponds to a stage from amongst the plurality of stages of the phase.

[0030] Once the reference values have been determined based on the plurality of measured values of the parameter, a new printjob or a batch of print jobs may be monitored based on the reference ranges, for example, on a real-time basis, to identify deviation of the parameter at each stage of the phase with respect to the corresponding reference range. For this purpose, the quality control engine 106 use reference values to monitor the parameter of a second batch of print jobs.

[0031] The quality control engine 106 may make the reference values available to one or more of the 3D printers 102-1 , 102-2. , and 102-n or other printers or other systems, similar to the system 100. Such entities that receive the reference values from the quality control engine 106 may implement various techniques to monitor print jobs based on the received reference values. In an example, the 3D printers 102-1 , 102-2. , and 102- n, other systems, or other printers may communicate with the system 100 over a network 108 to receive the reference values from the quality control engine 106.

[0032] The network 108 may be a single network or a combination of multiple networks and may use a variety of different communication protocols. The network 108 may be a wireless or a wired network, or a combination thereof. Examples of such individual networks include, but are not limited to, Global System for Mobile Communication (GSM) network, Universal Mobile telecommunications System (UMTS) network, Personal Communications Service (PCS) network, Time Division Multiple Access (TDMA) network, Code Division Multiple Access (CDMA) network, Next Generation Network (NON), Public Switched Telephone Network (PSTN). Depending on the technology, the communication network 108 includes various network entities, such as gateways, routers; however, such details have been omitted for sake of brevity of the present description. [0033] Thus, based on the reference value of a parameter for each of the plurality of stages of the phase, the quality control engine 106, one or more printers 102-1 , 102-2 , and 102-n or other systems may indicate a deviation for the parameter at a stage of the phase, in case of occurrence of the deviation at the respective stage.

[0034] Since the reference range for a parameter of a phase may vary dynamically for stages of a phase during the execution of the phase from the time of initiation to the end of the phase, stage-wise or the time dependent reference values provided by the quality control engine 106, may provide for more accurate monitoring and anomaly detection as compared to the methods which rely on reference ranges that are static with respect to the stages of the phase.

[0035] FIG. 3 illustrates a system 300 for determining reference ranges for parameters of a 3D printing process by a 3D printer 302, in accordance with an example of the present subject matter. In an example, the system 300 may be similar to the system 100. The system 300 among other things, includes a memory 322, interface(s) 324, engine(s) 304, and data 312. The 3D printer 302 may be any of the 3D printers 102-1 , 102-2, ..., and 102-n, that may perform the 3D printing process. In an example, the 3D printer 302 may be coupled with the system 300 in the networked environment as described previously. The memory 322 may include any computer-readable medium including, for example, volatile memory (e.g., RAM), and/or non-volatile memory (e.g., EPROM, flash memory, etc.).

[0036] The interface 324 may include a variety of software and hardware interfaces that allow the system 300 to interact with other devices, such as the 3D printer 302 and network entities, web servers, and external repositories, and peripheral devices such as input/output (I/O) devices. The interface 324 may also enable the coupling of internal components of the system 300 with each other.

[0037] The engine(s) 304 may include a KPI engine 306, a quality control engine 308, a batch inferencing engine 310, and other engine(s) 320 that supplement functions of the system 300. The KPI engine 306 and the quality control engine 308 may be similar to the above described KPI engine 104 and the quality control engine 106.

[0038] The data 312 serves, amongst other things, as a repository for storing data that may be fetched, processed, received, or generated by the engine(s) 304. In the illustrated example, the data 312 of the system 300 comprises input data 314, KPI data 316, and other data 318. The other data 318 may store the data pertaining to the other engine(s).

[0039] The 3D printer 302 may build a 3D object from a digital file comprising a 3D model of the 3D object in response to a print job. In an example, the 3D printer 302 may be a multi-jet fusion (MJF) 3D printer. The MJF 3D printer may use an array to selectively apply fusing agent and detailing agent across a bed of powdered material, which are then fused by heating elements into a solid layer. The 3D printer 302 may include a thermal chamber having a print bed on which a plurality of layers of the 3D object may get printed in accordance with the print job.

[0040] The 3D printer 302 may include a plurality of sensors 326, such as humidity sensors, ambient temperature sensors, printhead sensors, thermal chamber pressure sensors, carriage pressure sensors, and so on. In an example, a humidity sensor may be placed in a work area of the 3D printer 302. The work area may be the area in which print bed of the 3D printer 302 is present. The humidity sensor may measure the humidity of the work area before a 3D printing process of the 3D printer 302 is started or during the 3D printing process. In another example, an ambient temperature sensor may be placed in the work area to measure the ambient temperature of the work area. Further, the printhead sensors may include a temperature sensor to measure the temperature of a printhead during the 3D printing process. In an example, the thermal chamber pressure sensors may be placed in the thermal chamber to measure air pressure inside the thermal chamber. In another example, a carriage pressure sensor may be placed in the work area in connection with a carriage that movably carries an inkjet array above the print bed. The carriage pressure sensor may measure pressure being applied on the carriage during the 3D printing process. To execute a print job, the 3D printing process may involve monitoring outputs of one or more of the sensors 326.

[0041] Further, the execution of a print job may also involve monitoring of operational parameters of the 3D printer 302. In an example, the operational parameters of the 3D printer 302 may also be measured by the plurality of sensors 326. Examples of the operational parameters of the 3D printer 302 may include but are not limited to nozzle size, angle, and path, printing speed, thermal heating and cooling, layering direction, filament size, melting temperature, bed temperature, printing speed, layer thickness, infill geometry, infill density, filament diameter, extruder temperature, feed rate, characteristic of working material.

[0042] In addition, the execution of a print job may entail selection of properties and monitoring of materials to be used in the 3D printing process. Properties of material may include, for example, heat resistance, impact resistance, chemical resistance, or rigidity that may be monitored during the 3D printing process.

[0043] As discussed previously, the factors involved in the 3D printing process that may be monitored or selected, such as outputs of the sensors 326 and operational parameters of a 3D printer, and properties of material are herein referred to as parameters. The system 300 determines reference values for the respective parameters. As mentioned above, a reference value for a parameter may correspond to stages within a phase of the 3D printing process. In an example, a reference value may be indicated as a range comprising a lower and an upper value.

[0044] In operation, to determine such reference values for a parameter, the system 300 may obtain recorded measured values of the parameter of previously executed 3D printing processes or may monitor the 3D printing process of a first batch of print jobs to obtain the measured values. In one example, the first batch of print jobs may comprise print jobs executed by the 3D printer 302 over a period of time. In another example, the first batch of print jobs may comprise printjobs executed by one or more 3D printers coupled to the system 300. In an example, the first batch of print jobs may be selected by a user. The user may select a number of print jobs to be included in the first batch of printjobs based on various considerations. For instance, greater the number of print jobs selected in the first batch of print jobs for monitoring, higher the accuracy of the reference ranges as well as higher the computing resources that may be consumed in the monitoring. [0045] The KPI engine 306 receives the measured values of the parameter for each print job of the first batch of print jobs from the 3D printer 302. The measured values correspond to the plurality of stages of a phase of the 3D printing process of the first batch of print jobs. As described above, a stage may be a state of progression of the phase at a time instance. For example, for a cooling phase, the stages may correspond to values of temperature of a 3D object being cooled, wherein the measured values indicate decreasing temperatures in the work area. Similarly, for a curing phase, the stages may correspond to a percentage of the volume of excess solvent to be removed from layers 328, 330 of the 3D object being printed. [0046] In an example, wherein 30 print jobs, each comprising 2000 layers of the respective 3D object are monitored for the values of the ZPIatformMotor PWM signal of the phase of printing, the KPI engine 306 receives 30*2000 (=60000) measured values of the ZPIatformMotor PWM signal, 30 measured values for each layer. These measured values are stored in the input data 314 of the system 300.

[0047] Based on the measured values of the parameter for the stages of the phase of the 3D printing process, the KPI engine 306 determines the reference value for the parameter, such that the reference values vary along the stages of the phase.

[0048] In an example, to determine a stage-wise reference value, the KPI engine 306 performs statistical modeling. At the start of statistical modeling, the measured values received by the KPI engine 306 are tested to verify if the measured values follow a normal distribution. In an example, the measured values received for a stage of the phase are plotted as data points in a x-y plane. The data points are equivalent to the number of print jobs in the first batch, for instance, 30 in the above example. In a graphical form, distribution of data is considered as normal distribution if data near the mean are more frequent in occurrence than data far from the mean. In another example, for the verification, the KPI engine 306 performs Shapiro- Wilk Test of Normality. In yet another example, Anderson-Darling Test may be performed for the verification of normal distribution of the measured values.

[0049] In an example, to perform Shapiro-Wilk test, the KPI engine 306 calculates a sum of square values of each data point as ss =

- x)², wherein ‘xi’ is the value of data point, i.e., the measured value of parameter for i^th print job in a batch of ‘n’ printjobs. Then, ‘m’ is calculated as n/2 or (n-1 )/2 depending on whether ‘n’ is even or odd respectively. From table-1 of Shapiro-Wilk, weight values or coefficients ‘as’ are obtained based on the number of data points ‘n’. Thereupon, ‘b’ is calculated as b = ai (x_n=1-i - Xi) . Further, test statics ‘W can be calculated as (b²/SS). Using the table-2 of Shapiro-Wilk, W and n are used to find the p values in the table. If p-value is great than ‘0.05’, distribution of the values is considered as following a normal distribution.

[0050] In another example, the Anderson-Darling test for assessing whether the measured values follow a normal distribution, may be performed by the KPI engine 306 using the formulae:

wherein, ‘n’ is the number of data points; F(x) is the cumulative distribution of the i^th ‘x’ value; and In represents natural logarithms.

[0051] Based on the calculated AD, adjusted AD* is calculated as:

[0052] Once AD* is calculated, p value can be determined as follows: if AD*=>0.6, then p = exp(1 .2937 - 5.709(AD*)+ 0.0186(AD*)²); if 0.34 < AD* < .6, then p = exp(0.9177 - 4.279(AD*) - 1.38(AD*)²); if 0.2 < AD* < 0.34, then p = 1 - exp(-8.318 + 42.796(AD*)- 59.938(AD*)²); and if AD* <= 0.2, then p = 1 - exp(-13.436 + 101.14(AD*)- 223.73(AD*)²). If p-value is great than 0.05, distribution of the measured values is considered normal in nature.

[0053] Once it is verified that the measured values received by the KPI engine 306 follow a normal distribution, a mean of the measured values is calculated by the KPI engine 306. The mean value ‘p’ may be calculated as S =i ^xi/ⁿ- where ‘n’ is the data points or the number of print jobs. Then, a standard deviation ‘o’ is calculated using the formula a =

Using standard deviation, reference value of the parameter for the respective stages of the phase are computed.

[0054] In an example, the reference value may be defined as (// ± 3<J). Thus, a reference value for the plurality of stages of the phase is determined based on the mean and standard deviation of the data points corresponding to the respective stages. These reference values are stored in the KPI data 316.

[0055] In the above example, 2000 reference values, one for each layer are determined for the parameter ZPIatformMotor PWM signal. Thus, the reference values that the parameter may be monitored in reference to, do not remain static throughout the phase. Rather, the reference values may vary at different time instances during the phase.

[0056] FIG. 4 illustrates a graphical representation of the reference values of each of the 2000 layers of the printing phase determined for parameter ZPIatformMotor PWM signal in accordance with the above example. A first plot 402 and a second plot 404 represent the reference ranges comprising upper limits and lower limits, respectively, for parameter ZPIatformMotor PWM signal for each of the 2000 layers (mapped on X-axis) of the printing phase. As depicted, for the parameter ZPIatformMotor PWM signal, the reference range represented on Y axis varies for the 2000 layers which are mapped on the X axis. Thus, the reference ranges that the parameter ZPIatformMotor PWM may be monitored in reference to, may vary during the printing phase.

[0057] Based on the reference values of the parameter that are determined, the quality control engine 308 may cause monitoring of the parameter of future print jobs. In an example, the quality control engine 308 may perform the monitoring. In another example, the quality control engine 308 may provide the reference values to the 3D printer 302 or to other systems, similar to system 300, for monitoring the parameter of future print jobs. In an example, a new print job or a second batch of print jobs can be monitored for the deviation of parameters from the determined reference ranges.

[0058] In an example, a deviation score can be assigned to a new print job being monitored. The deviation score for a print job can be calculated as a weighted average of deviations for the plurality of stages from the respective mean values. For instance, in case of a printing phase, a weight can be assigned to each layer of the plurality of layers of the printing phase. Based on the weights and deviations of the measured values of the parameter from the respective mean value for each of the plurality of layers, an average of weighted deviations may be calculated. For example, for a printing phase comprising n layers with corresponding weights as wi, W2, ....Wn and deviations from the respective mean values as di, d2, ...., dn, deviation score for the printjob can be calculated as (widi+W2d2+... .w_ndn)/n. The deviation score of a print job indicates compliance of the job with the determined reference ranges. Higher deviation score indicates larger violation of reference ranges for a given parameter, thus an indication of an anomaly caused by the parameter. In an example, deviation score can be calculated for each job of a batch in a set of batches. [0059] In an example, based on the reference values of the parameter for the plurality of stages of the phase, the quality control engine 308 may indicate a deviation for the parameter a plurality of stages. Referring to Figure 4, plot 406 represents the monitored ZPIateform Motor PWM signal of a new print job for each of the 2000 layers of printing phase. Plot 408 represents the mean value for parameter ZPIatformMotor PWM signal for each of the 2000 layers. The plot 408 may be used to identify a deviation in the monitored values of ZPIateform Motor PWM signal with respect to the mean value depicted by plot 408 for each of the 2000 layers. [0060] In an example, the system 300 may monitor the 3D printing process of a second batch of print jobs. A second batch of print jobs may comprise print jobs that may be grouped together based on common property, such as a 3D printer executing the print jobs or a time of execution of the print jobs. Also, in one example, print jobs using a similar type of print materials may be grouped into a batch. For instance, a batch may be formed of print jobs executed by the 3D printer 302 over a period of time. In another example, print jobs executed by one or more 3D printers coupled to the system 300 to manufacture a 3D object based on a given digital file may be included in a batch. In yet another example, a batch of print jobs may comprise jobs executed by the one or more 3D printers during a time frame selected by a user.

[0061] In an example, the batch inferencing engine 310 may create multiple batches of print jobs based on a property of the print jobs selected by a user. In an example, the batch inferencing engine 310 may render a user interface to the user for selecting a property of the print job for creating a batch of print jobs. Once, one or more batches are created based on the selected property, the batch inferencing engine 310 may monitor a parameter for the respective batches of print jobs based on the reference values of the parameter as determined by the KPI engine 306.

[0062] The batch inferencing engine 310, in one example, may determine a deviation score for two or more batches from amongst the multiple batches of print jobs, based on the deviation for the parameter at each of the plurality of stages for the respective batches. Deviation score for a print job may be calculated as a weighted average of deviations for the plurality of stages from the respective mean values as mentioned earlier. Further, a deviation score for a batch can be calculated as average of deviation scores for each of the jobs in the batch. In an example, based on the deviation score of a print job in the batch of jobs, the quality control engine 308 may conduct a quality assessment for the print job from amongst the batch of print jobs. In another example, quality control engine 308 may provide the deviation score of a print job in the batch of jobs as an input to other system such as system 300 to conduct a quality assessment for the print job from amongst the batch of print jobs. In an example, the batch inferencing engine may compare the two or more batches based on the deviation score of the respective batches.

[0063] FIG. 5 illustrates graphical representation of a deviation score for plurality of parameters P1 , P2, P3, , P28 for four batches of print jobs. Four graphical lines, 502, 504, 506 and 508 denote four different batches of print jobs. The Y axis represents deviation scores for the respective parameter represented on X axis. By analyzing the graphical representation, trends across different signals or parameters for the four batches can be identified.

[0064] Creation of batches of print jobs enables batch inferencing to be performed for a variety of purposes, such as root cause analysis and helps in studying aggregated behaviour of a given batch with respect to another batch. Also, batch inferencing, as opposed to individual job inferencing, provides for highlighting dominant trends and suppresses nonsignificant trends, which in turn aids the root cause of failures. Batch inferencing may also indicate how a parameter may be impacted by the common property of the batch. For example, if two batches are created based on the criteria of two different materials, batch inferencing may highlight the impact caused by differences in properties of the respective material of the two batches on a given parameter.

[0065] Figures 6 and 7 illustrate method 600 and 700, respectively, to determine reference values for parameters involved in a 3D printing process by a 3D printer, for example, the 3D printer 302, in accordance with an example of the present subject matter. Although methods 600 and 700 may be implemented in a variety of computing devices similar to system 100 or 300, for ease of explanation, the present description of the example methods 600 and 700 are provided in reference to the above-described system 300.

[0066] The orders in which the methods 600 and 700 are described are not intended to be construed as a limitation, and any number of the described method blocks may be combined in any order to implement the methods 600 and 700, or an alternative method.

[0067] It may be understood that blocks of the methods 600 and 700 may be performed by programmed computing devices. The blocks of the methods 600 and 700 may be executed based on instructions stored in a non-transitory computer-readable medium, as will be readily understood. The non-transitory computer-readable medium may include, for example, digital memories, magnetic storage media, such as magnetic disks and magnetic tapes, hard drives, or optically readable digital data storage media.

[0068] Referring to Figure 6, at block 602, for a first phase of a 3D printing process, measured values of a parameter for a plurality of stages of the first phase are obtained for a plurality of print jobs. At block 604, for a second phase of the 3D printing process, the measured values of the parameter for a plurality of stages of the second phase are obtained for the plurality of print jobs. In an example, a key performance indicator engine, such as the KPI engine 306 of the system 300, obtains the measured values of the parameter for the first phase and the second phase. As explained earlier, a stage may be considered as a point in a phase of the 3D printing process at a time instance.

[0069] At block 606, a first set of reference values is determined for the parameter for the plurality of stages in the first phase and a second set of reference values is determined for the parameter for the plurality of stages in the second phase based on the obtained values. In an example, the KPI engine 306 may determine the first set of reference values and the second set of reference values using a statistical model. The reference values may be different for each of the plurality of stages of the phase.

[0070] Accordingly, stage- by-stage and phase-by-phase reference values for a parameter are determined through the method 600. Based on the reference values, future execution of the print jobs through a 3D printer, such as the 3D printer 302, may be monitored for any deviation from the reference values. In an example, the first set of reference values and the second set of reference values may be provided to a system such as the system 300 to conduct quality assessment for a new print job.

[0071] Reference is now made to Figure 7 that illustrates the method 700 wherein a batch of print jobs is analyzed to determine reference values for a parameter ‘P’ for stages of a phase of a 3D printing process, in accordance with the example method 700. For example, the phase of a 3D printing process may be one of warming, printing, cooling, and curing. For the explanation of the example method 700, it may be considered that the batch of the print jobs comprises ‘n’ number of print jobs. For the ‘n’ number of print jobs being analyzed, ‘m’ may be a number of stages of the phase at which measured value of parameter ‘P’ may be recorded. The number of stages ‘m’ may be selected by a user, in an example. At block 702, m*n values of the parameter ‘P’ are obtained. In an example, a key performance indicator engine, for example, the KPI engine 306 may receive the m*n values of parameter ‘P’. [0072] At block 704, for each of the ‘m’ stages, it is verified whether the respective measured values received from the ‘n’ print jobs: ‘M1 N1 , M1 N2, M1 N3 , M1 Nn’; ‘M2N1 , M2N2, M2N3 , M2Nn’ ; ; and ‘MmN1 , MmN2, MmN3 , and MmNn’, follow a normal distribution. In an example, for the verification of normal distribution of the measured values, the KPI engine 306 may perform tests, such as Shapiro-Wilk Test of Normality or Anderson-Darling Test as described above.

[0073] If a result of the test of normality is affirmative, at block 706, a mean of the measured values, corresponding to each of the ‘m’ stages, p1 , p2, .... p1 m, is calculated. Thus, the mean of ‘M1 N1 , M1 N2, M1 N3 , M1 Nn’, i.e., p1 ; the mean of ‘M2N1 , M2N2, M2N3 , M2Nn’, i.e., p2; ; and the mean of ‘MmN1 , MmN2, MmN3 , and MmNn’, i.e., pm is calculated. In an example, the KPI engine 306 may calculate the mean. In an example, if the result of the assessment made at block 704 is negative, the measured values obtained at block 702 from the batch of print jobs may be discarded and the procedure of the blocks 702 and 704 may be repeated for a new batch of print jobs.

[0074] Once the mean of the values corresponding to each of the ‘m’ stages has been calculated, at block 708, standard deviations o1 , o2,...., om for each of the ‘m’ stages may be calculated, based on the mean p1 , p2, .... pm respectively. In an example, the KPI engine 306 may calculate the standard deviations.

[0075] At block 710, reference ranges R1 , R2, ... Rm for the parameter ‘P’ for each of the ‘m’ stages in the phase are determined based on the mean p1 , p2, .... pm and the standard deviation o1 , o2, ...., om, respectively. In an example, the KPI engine 306 may determine the reference ranges for each of the ‘m’ stages. In an example, the reference ranges R1 , R2, ... Rm for each of the ‘m’ stages may be determined as (p1 ± 3o1 ), (p2± 3o2), .... (pm±3 om). [0076] Upon the reference ranges have been determined, at block 712, a new print job in the same phase of the 3D printing process, may be monitored for the parameter ‘P’ at one or more of the ‘m’ stages of the phase. At block 714, based on the reference values R1 , R2, ... Rm, deviations of the parameter of the new printjob at the corresponding stages of the phase from the respective reference range may be indicated. In an example, a quality control engine such as the quality control engine 308 of system 300 may perform the steps of blocks 710 and 712. In case of a deviation from the reference range at a stage of the phase, in an example, an alert may be generated, for instance, if the new printjob is monitored on an ongoing basis. The alert may cause a user to intervene and take corrective measures to avoid deviation of the parameter.

[0077] In another example, in addition to real time monitoring of new printjobs, the reference ranges R1 , R2, ... Rm for the parameter ‘P’ defined for the ‘m’ stages also allow root cause analysis of deviation in quality of a 3D object printed as a result of an executed print job. The parameter of the printjob that may be recorded at various stages during the execution of the print job and may be compared with the corresponding reference ranges. Since comparison is done based on reference ranges that may vary on a stage-by-stage basis, root cause analysis is more precise as opposed to a comparison made against reference ranges that are constant throughout a phase.

[0078] Figure 8 illustrates a computing environment 800 implementing a non-transitory computer-readable medium 802 for determining reference ranges for parameters involved in a 3D printing process performed by a 3D printer, according to an example of the present subject matter.

[0079] In an example, the computing environment 800 may comprise the above-explained system 100 or 300 and a 3D printer, such as the 3D printer 302. The computing environment 800 includes a processing resource 804 communicatively coupled to the non-transitory computer- readable medium 802 through a communication link 806. In an example, the processing resource 804 may be a processor of the system 300 that fetches and executes computer-readable instructions from the non- transitory computer-readable medium 802.

[0080] The non-transitory computer-readable medium 802 may be, for example, an internal memory device or an external memory device. In an example, the communication link 806 may be a direct communication link, such as any memory read/write interface. In another example, the communication link 806 may be an indirect communication link, such as a network interface. In such a case, the processing resource 804 may access the non-transitory computer-readable medium 802 through a network 808. The network 808 may be a single network or a combination of multiple networks and may use a variety of different communication protocols.

[0081] The processing resource 804 and the non-transitory computer-readable medium 802 may also be communicatively coupled to data source(s) 810. The data source(s) 810 may be used to store details, such as values of parameters of the 3D printing process, in an example. In an example, the non-transitory computer-readable medium 802 may comprise executable computer readable instructions 812 for determining the reference ranges for the parameter of the 3D printing process. For example, the non-transitory computer-readable medium 802 may comprise instructions executable to implement the previously described KPI engine 306 and the quality control engine 308.

[0082] In an example, the computer readable instructions 812 may cause the processing resource 804 to provide measured values of a parameter of a 3D printing process to a statistical model. The values correspond to stages of a phase of the 3D printing process and may be obtained from a first batch of print jobs. The first batch of print jobs may be executed by a 3D printer, such as the 3D printer 302. In an example, phase may be one of warming, printing, cooling, and curing. As explained previously, the stage is a time instance during the execution of the phase.

[0083] Further, the computer readable instructions 812 may cause the processing resource 804 to obtain a set of reference values for the parameter from the statistical model. The set of reference values comprises limits for the parameter at different stages of the phase of the 3D printing process. In an example, the statistical model may process the measured values of the parameter corresponding to the stages of the phase to determine the reference values for the respective stages of the phase. In an example, the statistical model may calculate a mean and a standard deviation for each stage for determining the reference value for the respective stage. The mean for a stage may be calculated based on the measured values of the parameter for the respective stage for each print job in the first batch of print jobs and standard deviation may, in turn, be computed based on the mean.

[0084] In an example implementation, the computer readable instructions 812 may cause the processing resource 804 to cause monitoring of the parameter for a second batch of print jobs based on the set of reference values. In an example, the computer readable instructions 812 may cause the processing resource 804 to provide the reference values to a 3D printer, such as the 3D printer 302, to monitor the parameter for the second batch of print jobs for a deviation at various stages of the phase from respective reference values.

[0085] In an example, the computer readable instructions 812 may cause the processing resource 804 to monitor the parameter of the second batch of print jobs across the stages of the phase of the 3D printing process based on the set of reference values. In an example, the computer readable instructions 812 may cause the processing resource 804 to indicate a deviation in the values of parameters at various stages from respective reference values, if any. [0086] As will be understood based on the foregoing description, in some cases, the computer readable instructions 812 may cause the processing resource 804 to obtain, for a printing phase of the 3D printing process, the set of reference values for the parameter corresponding to one or more layers of a plurality of layers of the printing phase.

[0087] In an example implementation, the computer readable instructions 812 may cause the processing resource 804 to compute, a deviation score for the parameter of a print job from amongst the second batch of the print jobs, based on the deviation of the parameter from the set of reference values. In an example, the deviation for a stage of a print job in the second set of print jobs may be understood as a deviation in the value of the parameter for that stage from the mean value of the parameter for the respective stage. The deviation score for a print job in the second batch of print jobs may be computed as the weighted average of deviations for each stage of the phase. In an example, the computer readable instructions 812 may cause the processing resource 804 to provide the deviation score as an input to a system, such as the system 300 to conduct a quality assessment for the print job from amongst the second batch of print jobs.

[0088] Although aspects for the present subject matter have been described in a language specific to structural features and/or methods, it is to be understood that the appended claims are not limited to the specific features or methods described herein. Rather, the specific features and methods are disclosed as examples of the present disclosu

Claims

We claim:

1 . A method comprising: obtaining, for a first phase of a three-dimensional (3D) printing process, measured values of a parameter for a plurality of stages of the first phase for a plurality of print jobs; obtaining, for a second phase of the 3D printing process, the measured values of the parameter for a plurality of stages of the second phase for the plurality of print jobs; and determining, based on the measured values obtained for the first phase and the second phase, a first set of reference values for the parameter for the plurality of stages in the first phase and a second set of reference values for the parameter for the plurality of stages in the second phase.

2. The method as claimed in claim 1 , wherein determining the first set of reference values and the second set of reference values comprises verifying that the measured values obtained for the first phase and the second phase follow a normal distribution.

3. The method as claimed in claim 1 , further comprising providing the first set of reference values and the second set of reference values to a system to conduct quality assessment for a new print job.

4. The method as claimed in claim 1 , wherein the method comprises: monitoring a parameter of a new print job along the first phase of the 3D printing process or the second phase of the 3D printing process; and indicating a deviation of the parameter of the new print job at a stage of the first phase or the second phase of the new print job based on the first set of reference values or the second set of reference values.

5. The method as claimed in claim 1 , wherein the first phase and the second phase of the 3D printing process are one of warming, printing, cooling and curing.

6. A system comprising: a key performance indicators (KPI) engine, to: receive measured values of a parameter from each of a first batch of print jobs, wherein the measured values correspond to a plurality of stages of a phase of a three-dimensional (3D) printing process of the first batch of print jobs; and determine, based on the measured values, a reference value for the parameter for each of the plurality of stages of the phase of 3D printing process; and a quality control engine, to: provide the reference value for the parameter for each of the plurality of stages of the phase of 3D printing process to monitor the parameter of a second batch of print jobs.

7. The system as claimed in claim 6, wherein the quality control engine is to: indicate, based on the reference value of the parameter for each of the plurality of stages of the phase, a deviation for the parameter at each of the plurality of stages.

8. The system as claimed in claim 6, wherein the system, comprises a batch inferencing engine, to: create multiple batches of print jobs based on a property of the print jobs selected by a user; monitor the parameter of the multiple batches of print jobs; and indicate, based on the reference value of the parameter for each of the plurality of stages of the phase, a deviation for the parameter at each of the plurality of stages for the multiple batches of print jobs.

9. The system as claimed in claim 8, wherein the batch inferencing engine is to: determine a deviation score for two or more batches from amongst the multiple batches of print jobs based on the deviation for the parameter at each of the plurality of stages for the respective batches; and compare, the two or more batches, based on the deviation score of the respective batches.

10. The system as claimed in claim 6, wherein to determine the reference values for the parameter for each of the plurality of stages of the phase, the KPI engine is to: determine, based on the measured values of the parameter at a stage of the phase received from each of the first batch of print jobs, a mean value for the stage; determine a standard deviation of the parameter for the stage from the mean value of the respective stage; and determine, the reference values for the parameter for each of the plurality of stages of the phase, based on the standard deviation and mean value of the respective stage.

11. The system as claimed in claim 6, wherein the KPI engine is to determine the reference values of the parameter corresponding to a plurality of layers of a printing phase of the 3D printing process.

12. A non-transitory computer-readable medium comprising instructions executable by a processing resource to: provide measured values of a parameter of a 3D printing process to a statistical model, the measured values pertaining to stages of a phase of 3D printing process and obtained from a first batch of print jobs; obtain, from the statistical model, a set of reference values for the parameter, the set of reference values comprising limits for the parameter at different stages of the phase of 3D printing process; and cause, based on the set of reference values, monitoring of the parameter for a second batch of print jobs.

13. The non-transitory computer-readable medium as claimed in claim 12, further comprising instructions executable by the processing resource to: monitor, based on the set of reference values, the parameter of the second batch of print jobs across the stages of the phase of 3D printing process.

14. The non-transitory computer-readable medium as claimed in claim 12, wherein instructions executable by the processing resource 804 to: obtain, for a printing phase of the 3D printing process, the set of reference values for the parameter corresponding to one or more layers of a plurality of layers of the 3D printing phase.

15. The non-transitory computer-readable medium as claimed in claim 12, wherein instructions executable by the processing resource to: compute a deviation score for the parameter of a print job from amongst the second batch of printjobs based on deviation of the parameter from the set of reference values; and provide the deviation score as an input to a system to conduct a quality assessment for the print job from amongst the second batch of print jobs.