Systems and methods for predicting installation quality of powertrains

Abstract

Systems and methods are provided for leveraging installation quality data for a component and subsequent asset performance data for assets that integrate that component. A predictive model is created using the installation quality data and subsequent asset performance data for the plurality of assets that integrate the component. The predictive model is used to predict a likelihood of future fault conditions for a new asset when installation requirements for the components are not followed.

Description

Atty Docket CMI002-000195 / 24-0483 -SRCSYSTEMS AND METHODS FOR PREDICTING INSTALLATION QUALITY OF POWERTRAINSCross-Reference to Related Application:

[0001] The present application claims priority to, and the benefit of the filing date of, U.S. Provisional Patent Application No. 63 / 746,407 filed January 17, 2025, which is incorporated herein by reference.BACKGROUND

[0002] Original equipment manufacturers (OEMs) often integrate components supplied by other manufacturers to produce a final product that is sold to consumers. For example, vehicle manufacturers may install a component such as an engine produced by an engine supplier into a vehicle chassis. The engine supplier can provide the OEM with installation requirements and recommendations that guide the OEM in installing the engine in a manner that is intended to produce a successful integration into the final product.

[0003] Some OEMs are incapable or unwilling to integrate engines or other components in the manner required and / or recommended by the supplier. Data that quantifies the future ramifications of such decisions and impacts on customers could be useful in persuading and / or informing the OEM to ensure the installation requirements and recommendations of the supplier are implemented. Therefore, further improvements in this technology area are needed.Atty Docket CMI002-000195 / 24-0483 -SRCSUMMARY

[0004] Embodiments are directed to unique systems, components, and methods are disclosed for leveraging installation quality data for components installed in assets, such as powertrains and / or vehicles, and subsequent asset performance data for those powertrains and / or vehicles. In an embodiment, a predictive model is determined using the installation quality data for the component and subsequent asset performance of the powertrains and / or vehicles in which the component is integrated. The predictive model is then used to predict a likelihood of future asset performance issues for a new powertrain and / or vehicle integrating that component when installation requirements for the new component are not followed.

[0005] Other embodiments are directed to apparatuses, systems, devices, hardware, methods, and combinations thereof for leveraging installation quality data for a component and subsequent asset performance to determine a predictive model that assesses the impact of failing to meet component installation requirements in a new or subsequent asset.

[0006] This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter. Further embodiments, forms, features, and aspects of the present application shall become apparent from the description and figures provided herewith.Atty Docket CMI002-000195 / 24-0483 -SRCBRIEF DESCRIPTION OF THE DRAWINGS

[0007] The concepts described herein are illustrative by way of example and not by way of limitation in the accompanying figures. For simplicity and clarity of illustration, elements illustrated in the figures are not necessarily drawn to scale. Where considered appropriate, references labels have been repeated among the figures to indicate corresponding or analogous elements.

[0008] FIG. 1 is a simplified block diagram of an embodiment of a system and process for determining a relationship between installation quality data and asset performance data for components installed and operated in assets such as powertrains and / or vehicles;

[0009] FIG. 2 is a graph depicting an example relationship of installation quality data versus fault frequency over time for a plurality of components installed in a plurality of assets;

[0010] FIG. 3 is a simplified block diagram of an embodiment of a system and process for assessing an installation quality of a new component in a new asset; and

[0011] FIG. 4 is a simplified flow diagram of an embodiment of a process for providing an assessment of the installation quality for a new component in a new asset based on the relationship between installation quality data and asset performance data.Atty Docket CMI002-000195 / 24-0483 -SRCDETAILED DESCRIPTION

[0012] Although the concepts of the present disclosure are susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described herein in detail. It should be understood, however, that there is no intent to limit the concepts of the present disclosure to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives consistent with the present disclosure and the appended claims.

[0013] References in the specification to “one embodiment,” “an embodiment,” “an illustrative embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may or may not necessarily include that particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. It should further be appreciated that although reference to a “preferred” component or feature may indicate the desirability of a particular component or feature with respect to an embodiment, the disclosure is not so limiting with respect to other embodiments, which may omit such a component or feature. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to implement such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.Additionally, it should be appreciated that items included in a list in the form of “at least one of A, B, and C” can mean (A); (B); (C); (A and B); (B and C); (A and C); or (A, B, and C).Similarly, items listed in the form of “at least one of A, B, or C” can mean (A); (B); (C); (A and B); (B and C); (A and C); or (A, B, and C). Further, with respect to the claims, the use of words and phrases such as “a,” “an,” “at least one,” and / or “at least one portion” should not be interpreted so as to be limiting to only one such element unless specifically stated to the contrary, and the use of phrases such as “at least a portion” and / or “a portion” should be interpreted as encompassing both embodiments including only a portion of such element and embodiments including the entirety of such element unless specifically stated to the contrary.

[0014] The disclosed embodiments may, in some cases, be implemented in hardware, firmware, software, or a combination thereof. The disclosed embodiments may also be implemented at least in part as instructions carried by or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be read andAtty Docket CMI002-000195 / 24-0483 -SRCexecuted by one or more processors. A machine-readable storage medium may be embodied as any storage device, mechanism, or other physical structure for storing or transmitting information in a form readable by a machine (e.g., a volatile or non-volatile memory, a media disc, or other media device).

[0015] In the drawings, some structural or method features may be shown in specific arrangements and / or orderings. However, it should be appreciated that such specific arrangements and / or orderings may not be required. Rather, in some embodiments, such features may be arranged in a different manner and / or order than shown in the illustrative figures unless indicated to the contrary. Additionally, the inclusion of a structural or method feature in a particular figure is not meant to imply that such feature is required in all embodiments and, in some embodiments, may not be included or may be combined with other features.

[0016] Referring now to FIG. 1, in the illustrative embodiment, an embodiment of a system 100 for determining a relationship between installation quality data and asset performance data for a plurality of components 102 installed in corresponding ones of a plurality of assets, such as powertrains and / or vehicle 104. The illustrative system 100 further includes an installation quality audit workstation 106, an asset performance computer 108, a server 110, a network 112, an installation quality database 114, and / or an asset performance database 116.

[0017] The powertrain and / or vehicle 104 may be a truck, locomotive, genset, marine application, other vehicle or a part thereof, or other asset. As used herein, “component” can be any part or combination of parts of an asset for a powertrain and / or vehicle 104, or other component of another type of asset. Examples of components 102 for powertrain and / or vehicle 104 include, but are not limited to, internal combustion engines, fuel systems, charge air coolers, fuel cells, batteries, electrolyzers, electronic control modules such as engine control modules, engine blocks, pistons, cylinder heads, valves, aftertreatment systems, aftertreatment components, turbochargers, transmissions, and combinations thereof.

[0018] Installation quality audit workstation 106 is configured to perform, among other operations, operations to determine and / or collect installation quality data at the time component 102 is installed in the asset. Installation quality audit workstation 106 can be configured to perform and / or collect installation quality data from one or more installation quality audits or tests that generate installation quality data.Atty Docket CMI002-000195 / 24-0483 -SRC

[0019] In an embodiment of system 100, installation quality audit workstation 106 is used for initiating, controlling, recording, and / or collecting data from one or more installation quality tests on each of the powertrains and / or vehicle 104 in which a component 102 is installed. In an embodiment of system 100, installation quality audit workstation 106 is used for initiating, controlling, recording, and / or collecting data from one or more installation quality tests on a subset of the powertrains and / or vehicle 104 in which a powertrain component 102 is installed. Installation quality workstation 106 can be configured with one or more applications, algorithms, and / or computer programs that test the installation quality of component 102 into powertrain and / or vehicle 104 or other type of asset.

[0020] The installation quality data can include values associated with installation quality requirements that are measured after installation of component 102 and before the asset is shipped to the customer, and / or tested by the customer before at or near the time the asset is placed into service. The installation quality data can be stored, for example, in installation quality database 114. Installation quality database 114 can be a separate database, reside all or in part on installation quality audit workstation 106, reside all or in part on server 110, and / or reside all or in part on a cloud-based database.

[0021] System 100 also includes asset performance computer 108, such as an engine control module, telematics device, edge computer, and / or streaming device, that collects asset performance data over time during operation of assets with their corresponding installed component 102. Asset performance computer 108 may be, for example, an engine control module or other type of computer comprised of digital circuitry, analog circuitry, or a hybrid combination of both of these types. Also, asset performance computer 108 may be programmable, an integrated state machine, or a hybrid combination thereof. Asset performance computer 108 may include one or more Arithmetic Logic Units (ALUs), Central Processing Units (CPUs), memories, limiters, conditioners, filters, format converters, or the like which are not shown to preserve clarity. In one form, asset performance computer 108 is of a programmable variety that executes algorithms and processes data in accordance with operating logic that is defined by programming instructions (such as software or firmware). Alternatively or additionally, operating logic for asset performance computer 108 may be at least partially defined by hardwired logic or other hardware.Atty Docket CMI002-000195 / 24-0483 -SRC

[0022] Network 112 can connect installation quality database 114 and asset performance database 116 to server 110. In an embodiment, network 112 connects installation quality audit workstation 106 and / or asset performance computer 108 with one or more of server 110, installation quality database 114, and asset performance database 116. In an embodiment, server 110 is a cloud server, but a server 110 not in the cloud is also contemplated.

[0023] One example installation quality test that can be conducted by installation quality audit workstation 106 include test(s) for ground noise such as engine ground noise in the engine control module of an engine type of component 102. The ground noise installation quality test can measure the amount of ground noise in the installed components 102 immediately after installation in powertrain and / or vehicle 104, such as at the end of the assembly line or at some point during the assembly process. The ground noise installation quality test measures the amount, such as in millivolts, of electrical interference or unwanted signals that enter the ground circuit of an engine control module. This measurement is just one example of the installation quality data output from installation quality audit workstation 106 that can be stored in installation quality database 114.

[0024] Engine ground noise can be used as one test for installation quality during an installation quality audit before powertrain and / or vehicle 104 with the installed component 102 is shipped to or placed into service by the customer. Excessive engine ground noise can disrupt operation of component 102, powertrain and / or vehicle 104, and / or engine control module, potentially causing malfunctions or other conditions that generate fault codes even if the sensor or other part identified by the fault code is functioning properly, leading to costly warranty claims and extended effort to identify the root cause of the fault code.

[0025] Engine ground noise can come from various sources within the vehicle's electrical system or from external sources, affecting the ability of the engine control module to accurately read sensor data and control engine functions. For example, the ground noise can introduce unwanted voltage fluctuations into the ground reference of the engine control module, leading to inaccurate sensor readings and potentially incorrect engine control decisions. The ground noise can also interfere with the signals from sensors connected to the engine control module making it difficult for the engine control module to interpret the data accurately and / or to operate component 102 properly, reducing the performance of component 102, and / or damaging the engine control module or other electrical components.Atty Docket CMI002-000195 / 24-0483 -SRC

[0026] Other tests for installation quality can also be ran by installation quality audit workstation 106 and the resulting installation quality data provided to installation quality database 114. Other installation quality tests can include installation quality data collected by, for example, testing an inlet restriction of the component 102 for air and / or fuel flow, testing a temperature drop across a charge air cooler type of component 102, or one or more parameters associated with one or more other components 102. The installation quality data can be represented or measured by, for example, voltages, resistances, pressures, temperatures, audible noise levels, vibration levels, and / or other parameters.

[0027] In an embodiment of system 100, asset performance computer 108 is used for controlling, monitoring, and / or collecting data over time from operation of the asset by the customer, such as powertrain and / or vehicle 104 with component 102 after installation of component 102. Asset performance computer 108 can be configured with one or more applications, algorithms, and / or computer programs that monitor operating parameters of powertrain and / or vehicle 104 with the installed component 102 and record operating parameters that are correlated to the installation quality data of component 102 into powertrain and / or vehicle 104.

[0028] For example, asset performance computer 108 can continuously monitor various engine sensors outputs and / or other parameters and compare them against pre-programmed thresholds, trends, or other values. When asset performance computer 108 detects a deviation from expected values, it triggers a corresponding asset performance flag, such as a fault code or warning. These asset performance flags can be stored in the memory of asset performance computer 108 and can be accessed and analyzed. The asset performance flags can also be received by and stored in asset performance database 116 which can be part of asset performance computer 108 and / or a separate database.

[0029] Server 110 communicates with or otherwise receives the installation quality data, such as from installation quality database 114 and / or installation quality audit workstation 106, and the asset performance data such as from asset performance database 116 and / or asset performance computer 108. Server 110 includes a processer and a memory with instructions encoded thereon that cause the processor to determine a relationship between the installation quality data and the asset performance data and output a predictive model 120. Predictive model 120 is then used as discussed further below to output a prediction associated with the assetAtty Docket CMI002-000195 / 24-0483 -SRCperformance flags, such as a frequency at which the asset performance flag will be generated for a component 102 that is newly installed in a powertrain and / or vehicle 102. The prediction is based on installation quality data collected during an installation quality audit conducted after assembly of the component 102 into the asset but before shipping and / or placement into service at the customer.

[0030] For example, with reference to FIG. 2, a graph 200 is provided with installation quality data 202 along the x-axis and asset performance data 204 along the y-axis for each one of a plurality of powertrains and / or vehicles 104 with a component 102 installed thereon. In the illustrated embodiment, installation quality data values increase in the positive direction of the x-axis due to higher measurements of, for example, voltages for engine ground noise, which are associated with higher fault frequencies along the y-axis. However, the values for the installation quality data and associated asset performance will vary depending on the component and the measurement.

[0031] The asset performance data 204 associated with each audited powertrain and / or vehicle 104 and its installed component 102 is provided along the y-axis of graph 200. For example, asset performance data 204 can include values for a flag frequency, such as a fault frequency or other warning, that occur over time while in use by the customer for each of the powertrains and / or vehicles 104 that were tested before shipment to / placement into service by the customer to generate the associated installation quality data value. Server 110 generates predictive model 120 based on the relationship 206 between the installation quality data 202 and the asset performance data 204 using any suitable algorithm.

[0032] In an embodiment, the installation quality data 202 and asset performance data 204 are normalized to account of the type of component 102 such as different sizes and models of the component. The data can also be normalized for the applications and / or types of vehicles and / or powertrains in which the same components are employed. Other normalization of the data used to generate predictive model 120 is also contemplated and not precluded.

[0033] In an embodiment, the predictive model 120 used to determine relationship 202 is a linear regression analysis or other type of regression algorithm. Other embodiments contemplate server 110 utilizes other algorithms, including neural network algorithms, instancebased algorithms, regularization algorithms, decision tree algorithms, Bayesian algorithms, clustering algorithms, association rule learning algorithms, deep learning algorithms,Atty Docket CMI002-000195 / 24-0483 -SRCdimensionality reduction algorithms, and / or other suitable machine learning and / or predictive algorithms, techniques, and / or mechanisms.

[0034] Referring to FIG. 3, a new component 102’ is provided that is installed in a new asset, such as a new powertrain and / or vehicle 104’. An installation quality audit is then performed by, for example, a service advisor or technician, such as by employing installation quality workstation 106 to collect installation quality data using one or more tests associated with one or more installation requirements for new component 102’. The installation quality data is then input into predictive model 120 to generate an assessment of the installation quality for the new component 102’ based on the new installation quality data and the relationship between installation quality data and asset performance data determined by predictive model 120.Predictive model 120 can produce an output 122 of the assessment of installation quality, which can be provided to the OEM by the advisor or technician along with any recommendations to improve the installation quality if needed.

[0035] Predictive model 120 can reside on installation quality workstation 106, on server 110, on the cloud, and / or other location. Output 122 can be provided as, for example, as a display on a computer screen or touch screen, a printout in hard copy form, an electronic message, an electronic file readable by a computer, an audible output or recording, a computer file, etc.

[0036] Referring to FIG. 4, a flow diagram of an embodiment of an assessment method or procedure 400 using predictive model 120 is provided. Procedure 400 includes an operation 402 to determine a relationship between the installation quality data 202 and the asset performance data 204. As discussed above, the relationship can be determined by predictive model 120. In some embodiments, predictive model 120 is periodically updated with new installation quality data and associated asset performance data.

[0037] Procedure 400 includes an operation 404 to determine new installation quality data, such as from installing a new component 102’ into a new powertrain and / or vehicle 104’. Procedure 400 further includes an operation 406 to generate an assessment for the new installation based on the relationship determined at operation 402 and new installation quality data for the new component 102’. Procedure 400 includes an operation 408 to output the assessment.Atty Docket CMI002-000195 / 24-0483 -SRC

[0038] In an embodiment, operation 402 includes determining the relationship between installation quality data and asset performance data for each of a plurality of components 102 installed in corresponding ones of a plurality of powertrains and / or vehicles 104. The installation quality data is collected, for example, immediately after installation or before placement into service of each of a plurality of components 102 and the asset performance data is collected for each of the plurality of components 102 over time after installation of the component 102 in the powertrain and / or vehicle 104.

[0039] In an embodiment of procedure 400, the installation quality data for the plurality of the components 102 installed in the plurality of powertrains and / or vehicles 104 is determined immediately after installation or prior to placement into service. The asset performance data for the plurality of components 102 installed in the plurality of powertrains and / or vehicles 104 is determined over time after installation, such as while the asset and the installed component 102 are in service.

[0040] In an embodiment of procedure 400, the asset performance data is determined by one or more fault codes or other flags in asset performance computer 108 of the powertrain and / or vehicle 104. The one or more fault codes are triggered by one or more operating parameters of the powertrain and / or vehicle 104 that are associated with one or more test parameters used to determine the installation quality data.

[0041] In an embodiment, the assessment of the installation quality is generated by determining an expected flag frequency of the asset performance data for the new component 102’ based on the new installation quality data. In an embodiment, the expected flag frequency is determined by predictive model 120 using the installation quality data.

[0042] In an embodiment, determining the relationship between the installation quality data 202 and the asset performance data 204 includes determining a correlation between the installation quality data 202 and a normalized asset performance data for the plurality of components 102 installed in the plurality of assets. In a specific embodiment, the correlation is determined by a regression analysis of the installation quality data 202 and the normalized asset performance data.

[0043] In an embodiment, the installation quality data 202 and the new installation quality data include a ground noise for each of the plurality of components 102 and the new component 102’ that is collected immediately after installation or before placement into serviceAtty Docket CMI002-000195 / 24-0483 -SRCof each of a plurality of components 102 and the new component 102’. Tn an embodiment, the plurality of components 102 and the new component 102’ include internal combustion engines and the ground noise is an engine ground noise. In an embodiment, the installation quality data include an engine ground noise, an inlet restriction for air and / or fuel, and / or a temperature drop across a charge air cooler.

[0044] In an embodiment, the installation quality data 202 and the new installation quality data include a voltage; a resistance; a pressure; a temperature; an audible noise level; and / or a vibration level. Other embodiments contemplate other types of installation quality data that can be measured and correlated to asset performance data.

[0045] The supplier of the component can use the systems and methods disclosed herein to generate assessments of potential asset performance flags or other fault conditions for new assets, such as new powertrains and / or vehicles 104’, that are based on the installation quality for new components 102’ into these new powertrains and / or vehicles 104’. These assessments can educate OEMs about the potential frequency of asset performance flags for the new powertrain and / or vehicle 104’ due to the level of installation quality for the new component 102’ that is achieved by the OEM. Since installation quality is correlated to asset performance data which provides an indicator of future warranty and repair costs, improving installation quality can lower future costs for the OEM and the component supplier. Accordingly, the supplier can provide the OEM with new information to persuade the OEM to comply with installation requirements that are designed to improve installation quality, or at least better understand the ramifications of not doing so.

[0046] The systems and methods disclosed herein provide feedback to the OEM about the ramifications of failing to comply with one or more installation requirements for a new component 102’ into a new powertrain and / or vehicle 104’. The OEM can use this information to understand the reliability of its powertrains and / or vehicles relative to its competitors. The OEM can also use this information to evaluate benefits to improving the design of its chassis or other platforms into which the new component 102’ is to be integrated to better comply with installation requirements that are designed to improve installation quality.

[0047] The installation quality audit workstation 106, asset performance computer 108, and / or server 110 may be embodied as any type of computing network capable of facilitating communication between the various devices of the system 100. As such, these computingAtty Docket CMI002-000195 / 24-0483 -SRCdevices may include one or more networks, routers, switches, computers, and / or other intervening devices. For example, the server 110 may be embodied as a cloud server or otherwise include one or more cellular networks, telephone networks, local or wide area networks, publicly available global networks (e.g., the Internet), ad hoc networks, short-range communication links, or a combination thereof. In the illustrative embodiment, the server 110 may be configured to process installation quality data captured by installation quality audit database 106 and / or fault data captured by asset performance computer 108 using artificial intelligence, machine learning, and / or other techniques. In an embodiment, installation audit quality workstation 106 and / or asset performance computer 108 reside on server 110.

[0048] It should be further appreciated that the server 110 described herein may function in a cloud computing environment. Server 110 may be embodied as a cloud-based device or collection of devices within a cloud computing environment. Further, in cloud-based embodiments, the server 110 may be embodied as a server-ambiguous computing solution, for example, which executes a plurality of instructions on-demand, contains logic to execute instructions only when prompted by a particular activity / trigger, and does not consume computing resources when not in use. That is, the server 110 may be embodied as a virtual computing environment residing “on” a computing system (e.g., a distributed network of devices) in which various virtual functions (e.g., Lambda functions, Azure functions, Google cloud functions, and / or other suitable virtual functions) may be executed corresponding with the functions of the server 110 described herein. For example, when an event occurs (e.g., data is transferred to the server 110 for handling), the virtual computing environment may be communicated with (e.g., via a request to an API of the virtual computing environment), whereby the API may route the request to the correct virtual function (e.g., a particular server-ambiguous computing resource) based on a set of rules. As such, when a request for the transmission of installation quality data from network 112 is made (e.g., via an appropriate user interface to the server 110), the appropriate virtual function(s) may be executed to perform the actions before eliminating the instance of the virtual function(s).

[0049] It should be appreciated that each of the installation quality audit workstation 106, asset performance computer 108, and / or server 110 may be embodied as a computing device / system. For example, in the illustrative embodiment, one or more of the installation quality audit workstation 106, asset performance computer 108, and / or server 110 may include aAtty Docket CMI002-000195 / 24-0483 -SRCprocessing device and a memory having stored thereon operating logic for execution by the processing device for operation of the corresponding device.

[0050] Depending on the particular embodiment, the installation quality audit workstation 106, asset performance computer 108, and / or server 110 may be embodied as a mobile computing device, server, desktop computer, laptop computer, tablet computer, notebook, netbook, Ultrabook™, cellular phone, smartphone, wearable computing device, personal digital assistant, Internet of Things (loT) device, control panel, router, gateway, and / or any other computing, processing, and / or communication device capable of performing the functions described herein.

[0051] The installation quality audit workstation 106, asset performance computer 108, and / or server 110 includes a processing device that executes algorithms and / or processes data in accordance with operating logic, an input / output device that enables communication between with one or more external devices, and memory which stores, for example, data received from the one or more external devices via an input / output device.

[0052] The input / output device allows the installation quality audit workstation 106, asset performance computer 108, and / or server 110 to communicate with the external device. For example, the input / output device may include a transceiver, a network adapter, a network card, an interface, one or more communication ports (e.g., a USB port, serial port, parallel port, an analog port, a digital port, VGA, DVI, HDMI, FireWire, CAT 5, or any other type of communication port or interface), and / or other communication circuitry. Communication circuitry may be configured to use any one or more communication technologies (e.g., wireless or wired communications) and associated protocols (e.g., Ethernet, Bluetooth®, Wi-Fi®, WiMAX, etc.) to effect such communication depending on the particular installation quality audit workstation 106, asset performance computer 108, and / or server 110. The input / output device may include hardware, software, and / or firmware suitable for performing the techniques described herein.

[0053] The external device may be any type of device that allows data to be inputted or output from the installation quality audit workstation 106, asset performance computer 108, and / or server 110. For example, in various embodiments, the external device may be embodied as the installation quality audit workstation 106, and / or server 110. Further, in some embodiments, the external device may be embodied as another computing device, switch,Atty Docket CMI002-000195 / 24-0483 -SRCdiagnostic tool, controller, printer, display, alarm, peripheral device (e.g., keyboard, mouse, touch screen display, etc.), and / or any other computing, processing, and / or communication device capable of performing the functions described herein. Furthermore, in some embodiments, it should be appreciated that the external device may be integrated into the installation quality audit workstation 106, asset performance computer 108, and / or server 110.

[0054] The processing device may be embodied as any type of processor(s) capable of performing the functions described herein. In particular, the processing device may be embodied as one or more single or multi-core processors, microcontrollers, or other processor or processing / controlling circuits. For example, in some embodiments, the processing device may include or be embodied as an arithmetic logic unit (ALU), central processing unit (CPU), digital signal processor (DSP), and / or another suitable processor(s). The processing device may be a programmable type, a dedicated hardwired state machine, or a combination thereof. Processing devices with multiple processing units may utilize distributed, pipelined, and / or parallel processing in various embodiments. Further, the processing device may be dedicated to performance of just the operations described herein or may be utilized in one or more additional applications. In the illustrative embodiment, the processing device is of a programmable variety that executes algorithms and / or processes data in accordance with operating logic as defined by programming instructions (such as software or firmware) stored in memory. Additionally or alternatively, the operating logic for processing device may be at least partially defined by hardwired logic or other hardware. Further, the processing device may include one or more components of any type suitable to process the signals received from input / output device or from other components or devices and to provide desired output signals. Such components may include digital circuitry, analog circuitry, or a combination thereof.

[0055] The memory may be of one or more types of non-transitory computer-readable media, such as a solid-state memory, electromagnetic memory, optical memory, or a combination thereof. Furthermore, the memory may be volatile and / or nonvolatile and, in some embodiments, some or all of the memory may be of a portable variety, such as a disk, tape, memory stick, cartridge, and / or other suitable portable memory. In operation, the memory may store various data and software used during operation of the computing device such as operating systems, applications, programs, libraries, and drivers. It should be appreciated that the memory may store data that is manipulated by the operating logic of processing device, such as, forAtty Docket CMI002-000195 / 24-0483 -SRCexample, data representative of signals received from and / or sent to the input / output device in addition to or in lieu of storing programming instructions defining operating logic. The memory may be included with the processing device and / or coupled to the processing device depending on the particular embodiment. For example, in some embodiments, the processing device, the memory, and / or other components of the installation quality audit workstation 106, asset performance computer 108, and / or server 110 may form a portion of a system-on-a-chip (SoC) and be incorporated on a single integrated circuit chip.

[0056] In some embodiments, various components of the installation quality audit workstation 106, asset performance computer 108, and / or server 110 (e.g., the processing device and the memory) may be communicatively coupled via an input / output subsystem, which may be embodied as circuitry and / or components to facilitate input / output operations with the processing device, the memory, and other components of the computing system. For example, the input / output subsystem may be embodied as, or otherwise include, memory controller hubs, input / output control hubs, firmware devices, communication links (i.e., point-to-point links, bus links, wires, cables, light guides, printed circuit board traces, etc.) and / or other components and subsystems to facilitate the input / output operations.

[0057] The installation quality audit workstation 106, asset performance computer 108, and / or server 110 may include other or additional components, such as those commonly found in a typical computing device (e.g., various input / output devices and / or other components), in other embodiments. It should be further appreciated that one or more of the components of the installation quality audit workstation 106, asset performance computer 108, and / or server 110 described herein may be distributed across multiple computing devices. In other words, the techniques described herein may be employed by a computing system that includes one or more computing devices.

[0058] Various aspect and embodiments are contemplated by the present disclosure. For example, one aspect includes a method of assessing an installation quality for a component a powertrain and / or vehicle. The method includes determining a relationship between installation quality data and asset performance data for each of a plurality of components installed in corresponding ones of a plurality of assets. The installation quality data is collected after installation of each of a plurality of components and the asset performance data is collected for each of the plurality of components over time after installation of the component in the asset.Atty Docket CMI002-000195 / 24-0483 -SRCThe method further includes determining new installation quality data for a new component installed in a new asset; generating an assessment of the installation quality for the new component based on the new installation quality data and the relationship between the installation quality data and the asset performance data; and outputting the assessment of the installation quality.

[0059] In an embodiment, the method includes determining the installation quality data for the plurality of the components installed in the plurality of assets that are powertrains and / or vehicles immediately after installation; and determining the asset performance data for the plurality of components installed in the plurality of powertrains and / or vehicles over time after installation.

[0060] In an embodiment, the asset performance data is determined by one or more fault codes in an electronic control module of the powertrain and / or vehicle.

[0061] In an embodiment, the one or more fault codes are triggered by one or more operating parameters of the powertrain and / or vehicle that are associated with one or more test parameters used to determine the installation quality data.

[0062] In an embodiment, generating the assessment of the installation quality includes determining an expected frequency of asset performance flags for the new component based on the new installation quality data.

[0063] In an embodiment, determining the relationship includes determining a correlation between the installation quality data and a frequency of asset performance flags for the plurality of components.

[0064] In an embodiment, the correlation is determined by a regression analysis of the installation quality data and the frequency of the asset performance flags.

[0065] In an embodiment, the installation quality data and the new installation quality data include a ground noise for each of the plurality of components and the new component that is determined immediately after installation of each of a plurality of components and the new component, respectively.

[0066] In an embodiment, the plurality of components and the new component include internal combustion engines and the installation quality data and the new installation quality data include an engine ground noise, an inlet restriction for air and / or fuel, and / or a temperature drop across a charge air cooler.Atty Docket CMI002-000195 / 24-0483 -SRC

[0067] In an embodiment, the installation quality data and the new installation quality data include: a voltage; a resistance; a pressure; a temperature; an audible noise level; and / or a vibration level.

[0068] According to another aspect of the present disclosure, a system for assessing an installation quality for a component of an asset is provided. The system includes a server comprising a processor and a memory having a plurality of instructions stored thereon that, in response to execution by the processor, causes the processor to determine a relationship between installation quality data and asset performance data for each of a plurality of components installed in corresponding ones of a plurality of assets. The installation quality data is collected after installation of each of a plurality of components and the asset performance data is collected for each of the plurality of components over time after installation of the component in the asset. The plurality of instructions further cause the processor to process new installation quality data for a new component installed in a new asset; generate an assessment of the installation quality for the new component based on the new installation quality data and the relationship between the installation quality data and the asset performance data; and output the assessment of the installation quality.

[0069] In an embodiment, the plurality of instructions stored on the processor causes the processor to: receive the installation quality data for the plurality of the components installed in the plurality of assets that are powertrains and / or vehicles immediately after installation from an installation quality database; and received the asset performance data for the plurality of components over time after installation from an asset performance computer.

[0070] In an embodiment, the asset performance data is determined by one or more fault codes in an electronic control module of the powertrain and / or vehicle.

[0071] In an embodiment, the one or more fault codes are triggered by one or more operating parameters of the powertrain and / or vehicle that are associated with one or more test parameters used to determine the installation quality data.

[0072] In an embodiment, the plurality of instructions stored one the processor causes the processor to generate the assessment of the installation quality by determining an expected frequency for asset performance flags for the new component based on the new installation quality data.Atty Docket CMI002-000195 / 24-0483 -SRC

[0073] In an embodiment, the plurality of instructions stored on the processor causes the processor to determine a correlation between the installation quality data and a frequency of the asset performance flags.

[0074] In an embodiment, the plurality of instructions stored on the processor causes the processor to determine the correlation by a regression analysis of the installation quality data and the frequency of the asset performance flags.

[0075] In an embodiment, the installation quality data and the new installation quality data include a ground noise for each of the plurality of components and the new component that is determined immediately after installation of each of a plurality of components and the new component.

[0076] In an embodiment, the plurality of components and the new component include internal combustion engines and the installation quality data and the new installation quality data include an engine ground noise, an inlet restriction for air and / or fuel, and / or a temperature drop across a charge air cooler.

[0077] In an embodiment, the system includes an installation quality audit workstation configured to determine the installation quality data and the new installation quality data. The installation quality data and the new installation quality data include: a voltage; a resistance; a pressure; a temperature; an audible noise level; and / or a vibration level.

Claims

Atty Docket CMI002-000195 / 24-0483 -SRCWHAT TS CLAIMED IS:

1. A method of assessing an installation quality for a component a powertrain and / or vehicle, the method comprising:determining a relationship between installation quality data and asset performance data for each of a plurality of components installed in corresponding ones of a plurality of assets, wherein the installation quality data is collected after installation of each of a plurality of components and the asset performance data is collected for each of the plurality of components over time after installation of the component in the assets;determining new installation quality data for a new component installed in a new asset; generating an assessment of the installation quality for the new component based on the new installation quality data and the relationship between the installation quality data and the asset performance data; andoutputting the assessment of the installation quality.

2. The method of claim 1, further comprising:determining the installation quality data for the plurality of the components installed in a plurality of assets that are powertrains and / or vehicles immediately after installation; and determining the asset performance data for the plurality of components installed in the plurality of powertrains and / or vehicles over time after installation.

3. The method of claim 2, wherein the asset performance data is determined by one or more fault codes in an electronic control module of the powertrain and / or vehicle.

4. The method of claim 3, wherein the one or more fault codes are triggered by one or more operating parameters of the powertrain and / or vehicle that are associated with one or more test parameters used to determine the installation quality data.

5. The method of claim 1, wherein generating the assessment of the installation quality includes determining an expected frequency of asset performance flags for the new component based on the new installation quality data.Atty Docket CMI002-000195 / 24-0483 -SRC6. The method of claim 1, wherein determining the relationship includes determining a correlation between the installation quality data and a frequency of asset performance flags for the plurality of components.

7. The method of claim 6, wherein the correlation is determined by a regression analysis of the installation quality data and the frequency of the asset performance flags.

8. The method of claim 1, wherein the installation quality data and the new installation quality data include a ground noise for each of the plurality of components and the new component that is determined immediately after installation of each of a plurality of components and the new component, respectively.

9. The method of claim 1, wherein the plurality of components and the new component include internal combustion engines and the installation quality data and the new installation quality data include an engine ground noise, an inlet restriction for air and / or fuel, and / or a temperature drop across a charge air cooler.

10. The method of claim 1, wherein the installation quality data and the new installation quality data include:a voltage;a resistance;a pressure;a temperature;an audible noise level; and / ora vibration level.

11. A system for assessing an installation quality for a component an asset, the system comprising:a server comprising a processor and a memory having a plurality of instructions stored thereon that, in response to execution by the processor, causes the processor to:Atty Docket CMI002-000195 / 24-0483 -SRCdetermine a relationship between installation quality data and asset performance data for each of a plurality of components installed in corresponding ones of a plurality of assets, wherein the installation quality data is collected immediately after installation of each of a plurality of components and the asset performance data is collected for each of the plurality of components over time after installation of the component in the asset; process new installation quality data for a new component installed in a new asset;generate an assessment of the installation quality for the new component based on the new installation quality data and the relationship between the installation quality data and the asset performance data; andoutput the assessment of the installation quality.

12. The system of claim 11, wherein the plurality of instructions stored on the processor causes the processor to:receive the installation quality data for the plurality of the components installed in the plurality of assets that are powertrains and / or vehicles immediately after installation from an installation quality database; andreceive the asset performance data for the plurality of components over time after installation from an asset performance database.

13. The system of claim 12, wherein the asset performance data is determined by one or more fault codes in an electronic control module of the powertrain and / or vehicle.

14. The system of claim 13, wherein the one or more fault codes are triggered by one or more operating parameters of the powertrain and / or vehicle that are associated with one or more test parameters used to determine the installation quality data.

15. The system of claim 11, wherein the plurality of instructions stored on the processor causes the processor to generate the assessment of the installation quality by determining an expected frequency of asset performance flags for the new component based on the new installation quality data.Atty Docket CMI002-000195 / 24-0483 -SRC16. The system of claim 11, wherein the plurality of instructions stored on the processor causes the processor to determine a correlation between the installation quality data and a frequency of asset performance flags for the plurality of components.

17. The system of claim 16, wherein the plurality of instructions stored on the processor causes the processor to determine the correlation by a regression analysis of the installation quality data and the frequency of the asset performance flags.

18. The system of claim 11, wherein the installation quality data and the new installation quality data include a ground noise for each of the plurality of components and the new component that is determined immediately after installation of each of a plurality of components and the new component, respectively.

19. The system of claim 18, wherein the plurality of components and the new component include internal combustion engines and the installation quality data and the new installation quality data include an engine ground noise, an inlet restriction for air and / or fuel, and / or a temperature drop across a charge air cooler.

20. The system of claim 11, further comprising an installation quality audit workstation configured to determine the installation quality data and the new installation quality data, wherein the installation quality data and the new installation quality data include:a voltage;a resistance;a pressure;a temperature;an audible noise level; and / ora vibration level.

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