Verification of cleaning process effectiveness

Abstract

The experimental color data obtained from the plurality of cleaning process verification test pieces (100) are used to determine the optimized cleaning process parameters in the automated cleaning machine (150). Color data can also be obtained from the cleaning process verification test pieces (100) to verify during the automated cleaning process that the effect of the actual cleaning process (430) produces unsatisfactory cleaning results. Based on the optimized process parameters (412), the automated cleaning machine can automatically adjust one or more cleaning process parameters (442) to correct the non-optimized parameters sensed during the execution of the cleaning process to help prevent unsatisfactory cleaning results.

Description

[0001] This application claims the benefit of U.S. Provisional Application No. 62 / 942,801, filed on December 3, 2019, entitled “VERIFICATION OF CLEANING PROCESS EFFECTIVENESS,” the entire contents of which are incorporated herein by reference. Background Art

[0002] Automated cleaning machines are used in restaurants, healthcare facilities, and other locations to clean, disinfect, and / or sanitize various items. In restaurants or food processing facilities, automated cleaning machines (e.g., dishwashers) can be used to clean food preparation and eating supplies, such as tableware, glassware, pots, pans, utensils, food processing equipment, and other items. For example, in healthcare facilities, automated washer-disinfectors can be used to clean and sterilize medical / surgical instruments and other medical items.

[0003] Generally speaking, the articles to be cleaned are placed on a rack and provided to a cleaning chamber of an automated cleaning machine. In the cleaning chamber, one or more cleaning products and / or rinse agents are applied to the articles during the cleaning process. The cleaning process may include one or more cleaning stages and one or more rinsing stages. At the end of the cleaning process, the racks and articles are removed from the cleaning chamber. Water pressure, water quality, chemical cleaning agent concentration, temperature, cycle duration and other factors may affect the effectiveness of the cleaning process. Summary of the invention

[0004] In one example, the present disclosure is directed to a system for determining effectiveness of a cleaning process based on color data from a validation test strip exposed to the cleaning process, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value.

[0005] In another example, the present disclosure is directed to a method of determining effectiveness of a cleaning process based on color data from a validation test strip exposed to the cleaning process, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value.

[0006] In another example, the present disclosure relates to a method of training a computer system to determine the effectiveness of a cleaning process based on color data from a plurality of validation test strips exposed to a plurality of experimental cleaning processes, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value.

[0007] In another example, the present disclosure relates to an automated cleaning machine that receives sensed values ​​of one or more cleaning process parameters during execution of a cleaning process, determines whether one or more of the sensed values ​​do not satisfy their respective optimized cleaning process parameter values, and adjusts a cleaning machine setting associated with a different one of the cleaning process parameters to ensure satisfactory cleaning results during execution of a subsequent cleaning process.

[0008] In another example, the present disclosure relates to an automated cleaning machine comprising: at least one processor; at least one sensor that senses information about one or more cleaning process parameters during execution of a cleaning process in a cleaning chamber of the cleaning machine; and a storage device comprising instructions executable by the at least one processor to perform the following operations: receiving sensed information about the one or more cleaning process parameters during execution of the cleaning process; determining, based on the sensed information, that one or more of the cleaning process parameters sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values; and adjusting a cleaning machine setting associated with a different one of the cleaning process parameters.

[0009] The one or more cleaning process parameters sensed during the execution of the cleaning process may include wash cycle duration, rinse cycle duration, detergent concentration, wash water temperature, and rinse water temperature. The one or more cleaning process parameters sensed during the execution of the cleaning process may include rinse aid concentration or inlet water temperature.

[0010] The one or more cleaning process parameters may include wash water temperature, and the adjusted cleaning machine settings may include wash cycle duration. The one or more cleaning process parameters may include detergent concentration, and the adjusted cleaning machine settings may include wash cycle duration. The one or more cleaning process parameters may include wash water temperature, and the adjusted cleaning machine settings may include detergent concentration.

[0011] The memory device may further include instructions executable by the at least one processor to initiate a sump water dump / fill cycle. The memory device may further include instructions executable by the at least one processor to initiate a ash removal cycle.

[0012] The storage device may further include instructions executable by the at least one processor to perform the following operations: generate a notification indicating that one or more of the cleaning process parameter values ​​sensed during the execution of the cleaning process do not meet the corresponding optimized cleaning process parameter values. The storage device may further include instructions executable by the at least one processor to perform the following operations: generate a notification including one or more corrective actions that can be taken to address the failure of the one or more cleaning process parameters to meet the corresponding optimized cleaning process parameter values. The storage device may further include instructions executable by the at least one processor to perform the following operations: apply the adjusted cleaning process parameters during the execution of the cleaning process. The storage device may further include instructions executable by the at least one processor to perform the following operations: apply the adjusted cleaning process parameters during the execution of a subsequent cleaning process.

[0013] In another example, the present disclosure relates to a non-volatile computer-readable storage medium storing instructions that, when executed, cause one or more processors to: receive sensed information about one or more cleaning process parameters during execution of a cleaning process in a cleaning chamber of a cleaning machine; determine, based on the sensed information, that one or more of the cleaning process parameters sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values; and adjust a cleaning machine setting associated with a different one of the cleaning process parameters.

[0014] In another example, the present disclosure relates to a system comprising: an automated cleaning machine comprising: at least one processor; at least one sensor that senses information about one or more cleaning process parameters during execution of a cleaning process in a cleaning chamber of the cleaning machine; and a storage device comprising instructions executable by the at least one processor to perform the following operations: receiving sensed information about the one or more cleaning process parameters during execution of the cleaning process; determining, based on the sensed information, that one or more of the cleaning process parameters sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values; and adjusting a cleaning machine setting associated with a different one of the cleaning process parameters.

[0015] The system may further include: a computing device including: at least one processor; a storage device including instructions executable by the at least one processor of the computing device to: obtain color data from a validation test strip exposed to the cleaning process, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value; and determine the effectiveness of the cleaning process based on the color data. The characteristic soil may include food-based soil or organic soil.

[0016] The details of one or more examples are set forth in the accompanying drawings and the description below. Other features will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 An example cleaning process verification coupon is shown with a test soil within the verification area of ​​the substrate.

[0018] Figure 2 Shows complete removal of the test dirt Figure 1 Example verification test piece.

[0019] Figure 3 An example automated cleaning machine according to the present disclosure is shown in which one or more validation coupons are used to validate a cleaning process.

[0020] Figure 4A is a block diagram illustrating an example computing system for verifying the effectiveness of a cleaning process according to the present disclosure.

[0021] Figure 4B is a front view of a computing system displaying an example cleaning process validation notification.

[0022] Figure 5A and Figure 5B is a photograph showing example experimental validation coupons having various “clean” levels that may be used as part of a training data set to train a computing system to determine optimized cleaning process parameters for an automated cleaning machine.

[0023] Figure 6 is a flow chart illustrating an example process by which a computing device may determine optimized cleaning process parameters according to the present disclosure.

[0024] Figure 7 is a diagram illustrating adjusting one or more cleaning process parameters to compensate for the failure of another cleaning process parameter to meet its optimized cleaning process parameter value in accordance with the present disclosure.

[0025] Figure 8 is a flow chart illustrating an example process according to the present disclosure by which a cleaning process may be validated.

[0026] Fig. 9 is a flow chart illustrating an example process according to the present disclosure by which a computing device may verify the effectiveness of a cleaning process by analyzing color sensor readings associated with a verification test strip.

[0027] Fig.10 is a block diagram of an example cleaning machine controller that is programmed to automatically adjust one or more cleaning process parameters during performance of a cleaning process.

[0028] Fig.11 is a flow chart illustrating an example process by which a computing device may automatically adjust one or more cleaning process parameters according to the present disclosure.

[0029] Fig.12 is a block diagram of a computing system environment for using analysis of color readings associated with one or more verification test strips in accordance with the present disclosure. DETAILED DESCRIPTION

[0030] According to one aspect of the present disclosure, experimental color data obtained from multiple cleaning process verification test pieces are used to determine optimized cleaning process parameters in an automated cleaning machine. Color data can also be obtained from cleaning process verification test pieces to verify the effectiveness of an actual cleaning process in an automated cleaning machine and / or to obtain one or more recommended corrective measures if the cleaning process produces unsatisfactory cleaning results. According to another aspect of the present disclosure, based on the optimized cleaning process parameters, the automated cleaning machine can automatically adjust one or more cleaning process parameters to correct non-optimized parameters sensed during the execution of the cleaning process to help prevent unsatisfactory cleaning results.

[0031] During the experimental optimization phase, and / or during the actual verification phase, one or more verification test pieces are placed in the cleaning chamber of the automated cleaning machine. Each verification test piece includes a substrate having at least one test indicator in the verification area of ​​the substrate. When exposed to the cleaning process in the automated cleaning machine, the test indicator changes, such as completely removed, partially removed, or changes in color. The amount or degree of change is a function of the cleaning process effect, and can be used to quantify the effect of the cleaning process and / or identify the failure of one or more cleaning process parameters that may cause unsatisfactory cleaning results. This means that the process can provide a quantitative value that is proportional to the performance of the overall cleaning process or indicates the performance of the overall cleaning process.

[0032] In order to quantify the amount or degree of change of the test indicator due to the cleaning process, or in order to quantify the amount of the test indicator remaining on the test strip after the cleaning process is completed, color data is obtained from the verification area reading of the verification test strip. The color data may include the intensity of one or more colors, such as a red wavelength range, a blue wavelength range, a green wavelength range, or a gray wavelength range. The color data may also include one or more wavelengths in an infrared (IR) or ultraviolet (UV) color range. The color data may also include, for example, one or more RGB ratios of the verification area. The RGB ratio may include, for example, a red / green ratio (R / G), a red / blue ratio (R / B), a blue / green (B / G) ratio, and / or a C / G color ratio. In addition or alternatively, in some embodiments, the color data may include one or more percentage color values. The percentage color value may include, for example, a percentage red (%R), a percentage blue (%B), and / or a percentage green (%G). In some embodiments, the color data may also include a FIJI gray value.

[0033] If a defined color change or a defined color measurement is detected as a result of the analysis, the cleaning process may be determined to be satisfactory. If a defined color change or a defined color measurement is not detected as a result of the analysis, the cleaning process performance may be considered unsatisfactory. The results obtained from the analysis of validation coupons of multiple cleaning processes during the optimization phase may be used to determine optimized cleaning process parameters that will result in satisfactory cleaning results for the cleaning machine.

[0034] In addition, the results obtained from the analysis of the validation test pieces of multiple cleaning processes during the optimization phase can be used to determine the adjusted optimized cleaning process parameters to help ensure that satisfactory cleaning results are obtained in the actual situation where one or more cleaning process parameters measured during the cleaning process do not meet the optimized parameter value (or value range). In other words, the analysis during the optimization phase can determine how to automatically adjust one or more optimized cleaning process parameters to compensate for the failure of other cleaning process parameters to meet their respective optimized parameter values ​​during the actual cleaning process. In this way, if one or more cleaning process parameters are detected to be "out of specification" during the execution of the actual cleaning process, the cleaning machine can automatically adjust itself on the spot to ensure that satisfactory cleaning results are achieved even when certain optimized cleaning process parameters are not met or cannot be met. The cleaning machine can automatically adjust one or more cleaning process parameters and apply these adjusted cleaning process parameters during the execution of the cleaning process, or it can automatically adjust one or more parameters after the cleaning process is completed, and can apply the adjusted cleaning process parameters during the execution of subsequent cleaning processes.

[0035] To verify the actual cleaning process, one or more verification test pieces that have been through the cleaning process may be scanned to obtain color data associated with the cleaning process. The system may analyze the color data obtained from the scan to determine whether the cleaning process was satisfactory. The system may further generate an indication for display on the user computing device, or may generate some other type of electronic communication, indicating the result of the analysis (e.g., whether the result of the cleaning process verification was "passed" or "failed").

[0036] In the event of unsatisfactory cleaning process performance, further analysis of the color data can identify one or more cleaning process parameters whose failure may have led to unsatisfactory results. Such potential failures in the cleaning process can be investigated and / or resolved so that future cleaning processes can be satisfactorily verified. In some embodiments, the system can generate an indication for display on a user computing device, or some other type of electronic communication can be generated, indicating potential failures of one or more cleaning process parameters of the cleaning process. The communication can also indicate how to investigate these potential failures and / or suggest corrective measures that can be taken to resolve the potential failures.

[0037] In some embodiments, the cleaning process validation procedure can be performed periodically according to a cleaning process validation plan established by a business entity. Validation of the cleaning process can help ensure that the items to be cleaned are properly cleaned, disinfected, and / or sterilized.

[0038] In certain embodiments, the test indicator may include one or more dirts, which are usually encountered by automated cleaning machines and are expected to be satisfactorily removed by the cleaning process. The test indicator may be designed to represent the dirt that is usually encountered in the application. For example, in health care applications, the test indicator may include medical dirt (usually found in a medical environment or representing the medical dirt encountered in a medical environment), which may also include organic dirt, such as protein, lipid, carbohydrate, bone scraps, etc., and / or inorganic dirt, such as salt water, bone cement, calcium and other minerals, dyes, inks, etc. In restaurant or food processing applications, the test indicator may include any type of dirt based on food, such as fat and oil, protein, carbohydrate, dye, mineral, starch, coffee and tea stains, etc., and / or other dirts usually encountered in food institutions, such as dyes, inks, lipsticks, polydimethylsiloxanes or other cosmetic dirts. In certain embodiments, the test indicator may be customized to represent the dirt type encountered during the cleaning process of a specific application most closely. Other possible test indicators of these and other applications will be apparent to those of ordinary skill in the art, and the disclosure is not limited in this respect.

[0039] The color data obtained from the reading of the verification area after the cleaning process is completed can be compared with one or more threshold values ​​indicating various cleaning performance levels. For example, one or more RGB ratios, percentage color values, FIJI gray values ​​or other color data can be compared with corresponding threshold values ​​to quantify the level of cleaning performance. Each RGB ratio, percentage color value, FIJI gray value (or other color data) can have one or more corresponding threshold values, wherein each corresponding threshold value indicates the cleaning performance level. The cleaning performance level can include, for example, clean (or "pass") and contaminated (or "failed"). The cleaning performance level can also include various "contamination" levels. In certain embodiments, each "contamination" level includes identifying the potential failure of one or more cleaning process parameters, and the parameters may have caused the unsatisfactory results of the whole cleaning process. For example, some "contamination" levels can indicate the potential failure of some cleaning process parameters, and other "contamination" levels can indicate the potential failure of different cleaning process parameters (for example, the amount of temperature and detergent) or the failure of different types of the same cleaning process parameters (for example, temperature is too high and temperature is too low).

[0040] Cleaning process parameters may include, for example, wash and rinse times and sequences, wash and rinse water temperatures, wash and rinse water conductivity, wash and rinse water pH, detergent concentration, rinse agent concentration, humidity, water hardness, turbidity, rack temperature, mechanical action within the cleaning machine, and any other cleaning process parameters that may affect the effectiveness of the cleaning process.

[0041] The cleaning process verification test piece can be placed in any suitable position or orientation within the cleaning environment of the cleaning machine so as to experience a representative cleaning process within the cleaning machine. For example, the verification test piece can be placed in such a place that it will be exposed to the same cleaning process experience that the item to be cleaned will experience. If the verification test piece runs through the cleaning process during the same cleaning cycle as the item to be cleaned, the verification test piece can be placed in such a place that it will not block or inhibit the flow of cleaning solutions, water, steam, air, heat or other cleaning components circulating throughout the cleaning chamber, nor will it inhibit the operation of the cleaning machine. In addition, during the same cleaning process, multiple verification test pieces can be placed at different locations within the cleaning machine to monitor the cleaning process conditions at these different locations within the cleaning machine.

[0042] During the optimization or verification process, one or more verification test strips, including the test indicator deposited or printed in the verification area, are placed in the cleaning chamber of the cleaning machine, such as on or in a rack, on or in an item to be cleaned, mounted to a side wall in the cleaning machine, etc., and the cleaning process is carried out in the cleaning machine. The verification test strips are cleaned by a combination of the chemical components (active cleaning components) in the cleaning solution and any mechanical action (such as impact on the verification test strip or flow of the cleaning solution on the verification test strip) occurring in the cleaning machine. Other factors that may affect the effectiveness of the cleaning process include, but are not limited to, the duration of the cleaning process, including the relative duration of each step or cycle in the overall cleaning process (e.g., washing time and rinsing time), the water temperature throughout the cleaning process (e.g., sump water temperature, washing water temperature and / or rinsing water temperature), water hardness and / or turbidity, detergent concentration, rinse agent concentration, conductivity of the washing and / or rinsing water, following defined procedures for the operation of the cleaning machine, correct mechanical operation of the cleaning machine, etc.

[0043] After the cleaning process is completed, the test indicator should undergo a defined change or a defined color measurement after the cleaning process is completed. The defined change or color measurement may include a defined color change or color measurement as determined by analyzing the color reading of the verification area and which indicates satisfactory removal of the test indicator by the cleaning process or indicates a satisfactory amount of indicator remaining after the cleaning process is completed.

[0044] After the cleaning process is completed, information about the amount of dirt remaining on the test piece can be obtained. This information can be obtained, for example, from a color scan measurement of the test piece (for example, by using a colorimeter), a digital image of the test piece, or other means of obtaining digital information about the amount of dirt remaining on the test piece. This information can be obtained inside the cleaning room of the cleaning machine or outside the cleaning room. This information can be automatically captured by a color sensor or a digital camera, or the capture of this information can be manually initiated by the user. One or more intermediate or additional steps may also be included, such as applying a dye to a verification area of ​​the verification test piece, and / or obtaining a color scan measurement or a digital image of the dyed verification area.

[0045] Figure 1 An example cleaning process validation test strip 100 is shown. The validation test strip includes a substrate 106 having a test indicator 104 within a validation area 102. Figure 2 Shows Figure 1 FIG. 1 is an example cleaning process verification test strip 100 in which the test indicator 104 has been completely removed by the cleaning process.

[0046] The substrate 106 may include any type of temperature stable material, such as plastic, paper, metal or ceramic. Examples of suitable substrate materials include, but are not limited to, polyethylene, polypropylene, polyester, polyvinyl chloride (vinyl), high density polyethylene (HDPE), synthetic forms of paper, plastic, ceramic, stainless steel and other metals. The test indicator 104 may be printed, inkjet printed, screen printed, sprayed, dipped or otherwise deposited on the substrate 106. In this embodiment, the test indicator 104 is octagonal; however, it should be understood that the test indicator 104 may take any desired regular or irregular shape, and the present disclosure is not limited in this regard.

[0047] The verification test strip 100 may also include one or more other areas, such as a writable area 108, which allows a user to add identification information or other annotations to the verification test strip 100. The identification information may include, for example, the date and time of the cleaning cycle, the identification of the cleaning machine, the identification of the person running the cleaning cycle and / or the verification procedure, a "clean" or "contaminated" indication, and / or other information related to the cleaning process verification procedure. The verification test strip 100 may also include a printed identifier 110 that uniquely identifies the test strip. Figure 1 In the embodiment of the present invention, the identifier 110 is a serial number that is visually readable by humans and / or electronically readable by a computing device. In other embodiments, the identifier 110 may also include one or more of a barcode, a QR code, or other types of electronically readable identifiers or codes.

[0048] Each verification test strip 100 and test indicator 104 are designed to represent the dirt experienced in a specific application and in response to the cleaning process suitable for those applications. For example, in a restaurant or other food institutions, an automated cleaning machine may include an automated dishwasher, and the cleaning process may be expected to remove food and / or other dirts usually encountered in such applications. Therefore, the test indicator designed for such applications may include dirt based on food, such as fat and oil, protein, carbohydrate, food dye, mineral substance, starch, coffee and tea stains, etc., or other dirts usually encountered in a food institution, such as dye, ink, lipstick or other cosmetics dirt. In health care applications, the test indicator may include dirt usually found in a medical environment or represented in a medical environment), it may also include organic dirt, such as protein, lipid, carbohydrate, bone chips, etc., and / or inorganic dirt, such as saline, dimethicone, bone cement, calcium and other mineral substances, dye, ink, etc. In other applications, the test indicator may include dirt or stains usually found in such applications or represented in such applications, and the present disclosure is not limited in this respect. Therefore, it should be understood that the verification test strip 100 is merely one embodiment of a verification test strip that may be used in accordance with the techniques of the present disclosure and that the present disclosure is not limited in this regard.

[0049] Figure 3 An example automated cleaning machine 150 according to the present disclosure is shown, wherein one or more cleaning process verification strips 100A-100D (collectively referred to as "verification strips 100") may be used to verify a cleaning process. In this embodiment, the cleaning machine 150 is a dishwasher for cleaning eating and / or food preparation items, including one or more of pots and pans, cutlery, glassware, eating and cooking utensils, etc. However, it should be understood that the cleaning machine 150 may include any other type of cleaning machine, such as a clothing or textile washing machine, a medical device reprocessor, an automated washer-disinfector, an autoclave, a sterilizer, or any other type of cleaning machine, and the present disclosure is not limited in this regard.

[0050] The cleaning machine 150 includes a housing 158 that defines one or more cleaning chambers 152 and has one or more doors 160 that permit entry and / or exit from the cleaning chambers 152. One or more removable shelves 154 are sized to fit within the cleaning chamber 152. Each shelf 154 can be configured to receive items to be cleaned directly thereon, or it can be configured to receive one or more trays or holders in which the items to be cleaned are held during the cleaning process. The shelves 154 can be general or special purpose shelves and can be configured to accommodate large and / or small items, food processing / preparation equipment such as deep pots, pans, cooking utensils, etc., and / or glassware, dinner plates and other eating utensils, etc. In hospital or healthcare applications, the shelves can be configured to accommodate instrument trays, durable goods, medical devices, pipes, masks, basins, bowls, bedpans, or other medical items. It should be understood that as described with respect to Figure 1 The configuration of the shelf 154 and the description of items that may be placed on or in the shelf 154 as shown and described and throughout this specification are for exemplary purposes only, and the present disclosure is not limited in this regard.

[0051] Typical cleaning machines such as cleaning machine 150 operate by spraying one or more cleaning solutions 164 (a mixture of water and one or more chemical cleaning products) into the cleaning chamber 152 and thus onto the items to be cleaned. The cleaning solution is pumped to one or more spray arms 162, which spray the cleaning solution 164 into the cleaning chamber 152 at the appropriate time. The cleaning machine 150 is provided with a fresh water source and, depending on the application, may also include one or more storage tanks to accommodate the used washing and / or rinsing solutions that will be reused in the next cleaning cycle. The cleaning machine 150 may also include or be provided with a chemical product dispenser 172, which automatically dispenses appropriate chemical cleaning products at the appropriate time during the cleaning process. The chemical product is mixed with a diluent, and the resulting cleaning solution 164 is pumped into the cleaning chamber 152 through the spray arm 162 at the appropriate time. Depending on the cleaning machine, the items to be cleaned, the amount of soil on the items to be cleaned, and other factors, one or more wash cycles may be interspersed with one or more rinse and / or sanitize cycles to form a complete cleaning process for the cleaning machine 150 .

[0052] The automated cleaning machine 150 further includes a dishwasher controller 170. The controller 170 may be further configured to communicate with an automated chemical product dispenser 172. The controller 170 includes one or more processors that monitor and control various cleaning process parameters of the cleaning machine 150 and / or the product dispenser 172, such as cycle time and length, cleaning solution concentration, wash water conductivity, timing and amount of dispensed chemical products, wash water temperature, rinse water temperature, heated air temperature, wash chamber temperature, humidity, timing of water and chemical product dispensed into the wash chamber, and the like.

[0053] like Figure 3 As shown, one or more cleaning process verification test strips, such as verification test strips 100A-100D, can be placed in various locations or on or in racks 154 within the cleaning chamber 152 during the cleaning process. In this embodiment, verification test strips 100A-100C are located in or on racks 154. Test strip 100D is positioned in a mounting bracket or holder 166 fixed to the side wall 157 of the cleaning chamber 152. Figure 3As shown, placing multiple verification test strips, such as test strips 100A-100D, in different areas of the cleaning chamber 152 can help verify the integrity and effectiveness of the cleaning process throughout the cleaning chamber 152. In other embodiments, a single verification test strip of the verification test strips 100 can be used for each cleaning cycle. The number of verification test strips used for each cleaning cycle can depend on the type of items to be cleaned, the type of cleaning machine, the type of soil to be removed, and / or the cleaning process and verification procedures defined by the enterprise or business entity. Therefore, it should be understood that one or more verification test strips can be used for each cleaning cycle, and the number of verification test strips used for each cleaning cycle is not limited in this regard.

[0054] The verification test strip mounting bracket, holder, clip or other fastener, such as the test strip holder 166, can be configured to support or hold the verification test strip during the cleaning process. In some embodiments, before the cleaning process begins, the holder, clip or other fastener can be manually attached to or placed in or on one or more walls of the rack 154 or the cleaning chamber 152. In other embodiments, the holder, clip or fastener can be molded directly into one or more walls of the cleaning chamber 152, or directly molded onto the rack 154. In this embodiment, the verification test strip will be placed in the molded holder before the cleaning process begins. In other embodiments, the fastener or holder may include a screw, a push-in plastic rod, a circular protrusion that will fit into a hole in a rack or tray, a rib that will snap into a matching slot structure on a rack or tray, or use a clip modified during the rack molding or may need to modify the rack. It should be understood that the test strip holder can be any suitable type, and the present disclosure is not limited in this respect.

[0055] In some embodiments, the test strip holder is designed to simulate the realistic challenges of the cleaning process for the type of item to be cleaned. Items such as certain types of cooking equipment, utensils, medical devices, or surgical instruments may include hard-to-reach areas that are more difficult to clean thoroughly during the cleaning process. To this end, the test strip holder may include a wall having one or more screens, holes, or slots that at least partially shield the verification area of ​​the verification test strip to provide a more realistic challenge for the cleaning process. It should be understood that the test strip holder is optional and the present disclosure is not limited in this regard.

[0056] One or more verification test strips 100 may be placed anywhere within the cleaning chamber 152 and may be located where they do not interfere with the spraying of the cleaning solution and / or the mechanical operation of the cleaning machine 150. The verification test strips 100 may also be of appropriate size so as not to block the spraying of the cleaning solution or interfere with the mechanical operation of the cleaning machine 150 during the cleaning process.

[0057] In some embodiments, the verification test strip 100 is rectangular and has dimensions (length and width) of sufficient size to accommodate a test indicator of appropriate size. It should be understood that the verification test strip 100 can be any suitable size or shape, and the shape of the test indicator can also vary, depending at least in part on the cleaning application, the type of soil to be removed, and / or the cleaning machine. For example, while Figures 1 to 3 The shape shown is an octagon, but other regular or irregular shapes may be used, and the present disclosure is not limited in this regard. For example, the test indicator can be divided into one or more regions, wherein each region includes the same test indicator or a different test indicator. The test indicator can further take the form of a circle, an ellipse, a square, a triangle, a rectangle, a pentagon, a hexagon, a parallelogram, a star, a splash, a line or a line sequence or pattern, a regular or irregular polygon, or any other suitable or desired regular or irregular shape.

[0058] Once each cleaning process is completed, the verification test strip 100 associated with the cleaning process is removed from the cleaning machine 150. Color Sensor (See Figure 4A-4B ) obtains a color reading associated with a verification area (e.g., verification area 102) of the test strip 100. The color sensor may include, for example, a colorimeter or other device for obtaining color data from a sample surface. The color reading is sent to a computing device (see Figure 4A ) and received by it, the computing device can analyze the color readings to generate additional color data. The color data may include, for example, one or more RGB ratios. The RGB ratios may include, for example, a red / green ratio (R / G), a red / blue ratio (R / B), and / or a blue / green (B / G) ratio. In addition or alternatively, in some embodiments, the color data may include one or more percentage color values. The percentage color values ​​may include, for example, percentage red (%R), percentage blue (%B), and / or percentage green (%G). In some embodiments, the color data may also include a FIJI grayscale value. Other color data may also be generated, and the present disclosure is not limited in this regard.

[0059] In some embodiments, the test indicator may be colored or dyed to cause a color change if certain dirt remains, such as proteins (Coomassie blue or silver staining), carbohydrates, fats, blood, etc. Coloring or dyeing of the test indicator can help to more easily detect certain changes in the test indicator under certain conditions.

[0060] The color data obtained from a plurality of experimental cleaning processes during the optimization phase can be used to determine one or more optimized cleaning process parameters of the cleaning machine. In addition, the relationship between the cleaning process parameters can be determined so that adjustments to the one or more cleaning process parameters can be identified that correct any non-optimized cleaning process parameters. In this way, the cleaning machine can be programmed to automatically adjust one or more cleaning process parameters to compensate for any non-optimized cleaning process parameters sensed during the actual cleaning process.

[0061] To verify the actual cleaning process, the computing device analyzes the color data associated with the verification area. If a defined color change is detected as a result of the analysis, it is determined that the cleaning process is satisfactory. If a defined color change is not detected, it is determined that the cleaning process performance is unsatisfactory. In the event that the cleaning process performance is determined to be unsatisfactory, further analysis of the color data and / or other data related to the cleaning process can identify potential failures of one or more cleaning process parameters that may have caused the unsatisfactory cleaning results, and corrective measures that can be taken to resolve the potential failures can be suggested.

[0062] In some embodiments, the computing device may generate a notification to indicate that the cleaning process was validated and / or that the cleaning process "passed" the validation procedure. If it is determined that the cleaning process is unsatisfactory, the computing device may generate a notification to indicate that the cleaning cycle was not validated and / or that the cleaning cycle "failed" the validation procedure. In some embodiments, a failure notification including possible reasons for the unsatisfactory cleaning process may be generated and displayed. The notification may also include suggested corrective actions that the user may take to resolve potential failures of the identified cleaning process parameters. In some embodiments, the identified cleaning process parameters may be automatically adjusted to correct the identified failures.

[0063] In some embodiments, dishwasher 150 uses dish racks with electronically readable identifiers to uniquely identify each rack and identify the type of items in the rack. Figure 3 In the illustrated embodiment, the rack 154 includes an RFID tag 180. The rack identification data stored in the RFID tag 180 includes a rack type and a unique rack identifier. The rack type corresponds to the type of items cleaned on or in the rack. For example, the rack type can be identified as a deep pot / pan rack, a glassware rack, a cutlery rack, a utensil rack, etc. The rack identifier is uniquely associated with an individual rack. The rack identifier enables each cleaning cycle to be tracked individually using a uniquely identified rack and an associated rack type and a date and time stamp. Example rack identification systems are described in U.S. Patent Nos. 7,437,213 and 6,463,940, the entire contents of which are incorporated herein by reference.

[0064] The dishwasher controller 170 includes a tag reader configured to read the RFID tag 180 and obtain the rack identification data. The dishwasher controller 170 (or other computing device) can associate the unique rack identifier with the current cleaning process. This also results in identifying the type of items cleaned during the current cleaning cycle, as well as associating the individual rack and item type with any other data associated with the current cleaning cycle (e.g., cycle type, water volume and temperature, amount / volume / weight of chemical product dispensed, cycle time, etc.).

[0065] The dishwasher controller 170 further determines the rack type and thus identifies the type of items being cleaned during the current cleaning process. The dishwasher controller 170 can adjust the cleaning process to best cope with the type of items being cleaned and the type of dirt commonly encountered when cleaning these items. For example, as described above, different types of items cleaned in a dishwasher may experience different types of dirt. For example, deep pots and pans may be contaminated with a large amount of starch, sugar, protein and fat dirt. In contrast, glasses are usually not severely contaminated but have difficult-to-remove dirt, such as lipstick, coffee and tea stains. Once the dishwasher controller 170 identifies the type of items in the rack, it can modify the dishwasher cycle in a manner that selects the optimal wash / rinse cycle, time, temperature and chemical composition required to clean the items while minimizing the use of water, energy, or chemical cleaning products. For example, running a wash cycle using a chemical composition that can effectively clean deep pots and pans may be too much for a rack of glasses. Rack identification allows the dishwasher controller 170 to use the correct type and concentration of chemicals for the items to be cleaned. By not overusing chemicals, the dishwasher can use fewer chemicals overall while still achieving the expected cleaning performance results.

[0066] These RFID tags, such as tag 180, can be integrated into the racks of the dishwasher in a variety of ways. They can be physically attached to the racks by using fasteners, can be molded directly into the racks, or can be attached to the racks with molded or machined clips or brackets. They can be located anywhere on the racks, but are preferably along the outer edges of the racks so that they do not interfere with the water spray for cleaning dishes. The mounting structure can allow RFID tags to be attached to new and pre-existing racks. One way to do this is to use an injection molded bracket that is designed to hold the RFID tag in a specific position on the rack and can be inserted into multiple types of racks. In some embodiments, the tags are placed in a consistent position on each rack and can be read by an antenna located in, mounted in, on or near the floor 155 or the side wall 157 of the dishwasher. In other embodiments, the tag reader can be located on the outside of the dishwasher or on the outer wall of the dishwasher.

[0067] The identification of individual racks and rack types and the cleaning process data that may also be obtained by the dishwasher can be further analyzed to identify the number and types of cleaning processes within a specified time period, view historical data on problems encountered during the cleaning processes, view data about the general operation of the cleaning machine (e.g., how many cycles per day / week / month, how often the drains are run, etc.), and view the types of wares cleaned at specific times and days of the week in addition to cycle times, temperatures, amounts of chemicals dispensed, and can help create reports to improve management of the dishwashing facility.

[0068] The identification of the rack type can also determine the way in which the computing device analyzes the color data associated with the verification test strip. For example, according to the type of the cleaned article, different types of verification test strips (and therefore different test indicators) can be used, and each different type of verification test strip can be associated with different corresponding analyses of color data. For example, multiple RGB ratios and / or color values ​​or percentages (for example, two or more of RG, RB, BG or CG color ratios, and / or FIJI gray values) can be used to analyze certain test indicators. In other embodiments, certain test indicators may only require one of the RGB ratios (for example, one of the RG, RB, BG or CG color ratios, and / or FIJI gray values) to obtain statistically significant results. For a satisfactory cleaning process, an unsatisfactory cleaning process or both, the type of color data and the threshold associated with the color data can depend on, for example, the color of the test indicator, the formula of the test indicator, and the type (color and / or quantity) of the change that the test indicator undergoes during the entire cleaning process.

[0069] Figure 4A is a block diagram of an example computing device 200 according to the present disclosure that can be used to obtain color data associated with a verification test strip and / or to verify a cleaning process based on an analysis of color data associated with a verification test strip. The computing device 200 can include, for example, a mobile computing device, a smart phone, a tablet computer, a laptop computer, a desktop computer, a server computer, a personal digital assistant (PDA), a portable gaming device, a portable media player, an e-book reader, a wearable computing device, a smart watch, a television platform, a remote or cloud-based computing device, or any other type of computing device.

[0070] The computing device 200 includes one or more processors 202, one or more user interface components 204, one or more communication interfaces 212, a color sensor 208, and a data storage medium 214. The user interface component 204 may include one or more of an audio interface, a visual interface, and a touch-based interface component, including a touch screen display, a speaker, a button, a keypad, a stylus, a mouse, or other mechanisms that allow a person to interact with the computing device. The communication interface 212 allows the computing device 200 to communicate with other remote or local computing devices through a wired and / or wireless connection. Wired and / or wireless communication may include communication through one or more networks, such as any type of local area network or wide area network including Wi-Fi network, Bluetooth communication, near field communication, and / or the Internet. For example, the computing device 200 may communicate with one or more remote computing devices. The data storage medium 214 includes a cleaning validation module 206 and a data memory 210. The cleaning validation module 206 includes computer-readable instructions, which, when executed by one or more processors 202, cause the one or more processors 202 to analyze the color data associated with the validation test piece and determine the effect of the associated cleaning process based on the analysis.

[0071] The color sensor 208 may include a color sensor capable of obtaining a color reading from a surface. For example, the color sensor 208 may include a light source that directs white light at a surface (e.g., a verification area of ​​a verification test strip), and one or more detectors, such as one or more photodiodes, that sense the color reflected from the surface. Each detector output indicates a corresponding color sensor reading of the intensity of the detected reflected wavelength, such as red, green, blue, and / or visible spectrum wavelengths. The color sensor 208 may also detect reflected light within the IR and / or UV wavelength ranges. In other embodiments, the color sensor 208 may be a camera-based reader that uses a camera and image processing technology to capture and analyze an RGB image of the verification area to obtain color information indicating the amount of dirt remaining on the verification test strip. For the purposes of this specification, the term "color sensor reading" will be used to describe the raw color information obtained from reading, scanning, or image analysis of the verification area, and it should be understood that the present disclosure is not limited in this regard.

[0072] The computing device 200 receives color sensor readings associated with the verification test strip 100 from the color sensor 208. The cleaning validation module 206 includes computer-readable instructions that, when executed by the one or more processors 202, cause the one or more processors 202 to generate color data using the color sensor readings. The cleaning validation module 206 also includes computer-readable instructions that, when executed on the one or more processors 202, cause the one or more processors 202 to analyze the color data and determine the effectiveness of the cleaning process based on the analysis of the color data. The cleaning validation module 206 may also include computer-readable instructions that, when executed on the one or more processors 202, cause the one or more processors 202 to analyze the color data and identify potential failures of one or more cleaning process parameters that may have led to unsatisfactory cleaning results. The cleaning validation module 206 may also include computer-readable instructions that, when executed on the one or more processors 202, cause the one or more processors 202 to analyze the potential failures of one or more cleaning process parameters that may have led to unsatisfactory cleaning results and recommend corrective measures that may be taken to resolve one or more potential failures.

[0073] The cleaning validation module 206 may also include computer-readable instructions that, when executed on the one or more processors 202, cause the one or more processors 202 to communicate with a remote or cloud-based computing device to send and / or receive information associated with the cleaning process validation program. In some embodiments where the computing device 200 is a remote or cloud-based computer, the cleaning validation module 206 may also include computer-readable instructions that, when executed on the one or more processors 202, cause the one or more processors 202 to automatically communicate with a cleaning machine controller (e.g., dishwasher controller 170) to automatically adjust one or more cleaning process parameters of the cleaning machine based on the analysis results.

[0074] The cleaning validation module 206 may also include computer-readable instructions that, when executed by the one or more processors 202, cause the one or more processors 202 to generate one or more notifications to display results of the cleaning process validation procedure on the user interface 204 of the computing device 200 or on a user interface of another computing device, such as the user interface 222 of the user computing device 225. For example, Figure 4BA computing device 225 (in this embodiment, a smartphone or tablet computer) having a touch screen display 222 is shown. Notices 216 and 218 are displayed on the touch screen 222. Notice 216 indicates that the cleaning process performed on August 7, 2018 using the verification test piece with serial number A10456-52 did not pass the corresponding cleaning process verification procedure. In other words, the analysis of the color data associated with the verification area on the verification test piece with serial number A10456-52 shows that the test indicator has not been satisfactorily cleaned. Notice 216 may include, for example, the words "failed" and (!) instructions or other icons that attract attention to help the user notice that the specific cleaning process has not passed and that one or more problems with the cleaning process may need to be resolved. Notice 218 indicates that the cleaning process performed on August 7, 2018 using the verification test piece with serial number D25432-40 passed the corresponding cleaning process verification procedure. In other words, the analysis of the color data associated with the verification area on the verification test piece with serial number D25432-40 shows that the test indicator is satisfactorily cleaned. In this embodiment, the notification 208 therefore includes the word "passed" to indicate that the corresponding cleaning process has been verified as satisfactory.

[0075] A button 220 displayed on touch screen 222 and labeled "Scan Next Strip" or similar text may be tapped to enable the user to obtain color data from another verification strip using color sensor 208. In some embodiments, color sensor 208 may be integrated into one of computing device 200 or computing device 225. In other embodiments, color sensor 208 may be an external device.

[0076] In some embodiments, notifications 216 and / or 218 on the touch screen 222 can be activated (e.g., selected, touched, or tapped) to cause the computing device 225 to display additional information about the specific cleaning process validation procedure. For example, tapping notification 216 on the touch screen 222 can cause one or more detailed reports about the cleaning process performed on August 7, 2018 using the validation test strip with serial number A10456-52 and receiving a "fail" to be displayed on the touch screen 222. The more detailed report can, for example, include information such as the date and time of the cleaning cycle, the unique identification of the cleaning machine, the unique identification of the person running the cleaning process and / or the cleaning validation procedure, the type of items cleaned during the cleaning process, the type of racks or trays used during the cleaning process, the type of items cleaned during the cleaning process, the type and amount of chemical products dispensed during each cycle of the cleaning process, the amount of water dispensed during each cycle of the cleaning process, a "pass" or "fail" indication of the cleaning process, and / or other information related to the cleaning process or the cleaning process validation procedure. A more detailed report may also include information about the color data, analysis of the color data, and / or results of the analysis of the color data. The report may also include an identification of a failure of one or more cleaning process parameters that may have resulted in an unsatisfactory cleaning process result, and / or a suggested corrective action for resolving the failure. Tapping or touching the notification 218 on the touch screen 222 may cause the processor 202 to generate for display one or more similar detailed reports of a cleaning process performed on August 7, 2018 using a verification test piece with serial number D25432-40 and receiving a "pass". The more detailed report may include further interactive areas on the touch screen display that allow the user to explore any level of detail about the analysis and / or results, and / or adjust one or more settings for the analysis, and / or perform further analysis of the color data as desired.

[0077] The storage medium 214 of the computing device 200 includes data 210 used or generated by the computing device 200 during execution of the cleaning validation module or any other function of the computing device 200. For example, the storage medium 214 may include color sensor readings and other information received from the color sensor 208, data input by a user through the user interface component 204, and / or color data and any other data used or generated by the cleaning validation module 206 during execution of the cleaning process validation procedure.

[0078] Figure 5A is a photograph showing example verification strips 499-502 and 527-534 corresponding to twelve experimental dishwasher cleaning cycles with different cleaning process parameters. In this embodiment, the strips 499-502 and 527-534 are the same type of verification strips, with the same characteristic, red food-based soil. Figure 5A Test pieces 499-502 and 527-534 show the amount of dirt remaining on each test piece after completing the corresponding experimental cleaning cycle. Figure 5B Shown with Figure 5A The same validation panels 499-502 and 527-534, but the remaining stain was stained with Coomassie blue dye to highlight the remaining protein.

[0079] Table 1 (below) shows the Figure 5A The relative soil removal percentage % is calculated from the RGB color sensor values ​​for 12 dishwasher cycles of a test strip of The soil removal percentage is determined based on the RGB color ratios obtained from the test strip and the RGB color ratios obtained from a "clean" test strip and an unused "contaminated" test strip (e.g., a validation test strip that has not been exposed to a cleaning process).

[0080] In the embodiment of Table 1, the column marked with "RGB color ratio" is the red / green (RG) ratio calculated according to the color sensor reading associated with the verification test piece. In some embodiments, for the verification test piece including red characteristic food stains, the red / green ratio may be more indicative of the remaining / removed dirt percentage than, for example, the red / blue ratio or the blue / green ratio. However, as described herein, the color data may also include one or more RGB ratios, such as red / green ratio (R / G), red / blue ratio (R / B), blue / green (B / G) ratio and / or C / G color ratio. In addition or alternatively, the color data may include one or more percentage color values. The percentage color value may include, for example, percentage red (%R), percentage blue (%B) and / or percentage green (%G). The color data may also include a grayscale value or any other color data indicating the amount of dirt remaining on the verification test piece. In general, the color data type that is relatively more indicative of the percentage of dirt removal may vary according to the type of dirt on the verification sample, the color of the dirt on the verification sample, and other factors, and it should be understood that the present disclosure is not limited to the use of the specific color data shown in Table 1.

[0081] For the data in Table 1, the soil removal percentage corresponding to a "clean" cleaning prediction is defined as greater than 95.5% soil removal. For some of the test pieces in this example (e.g., test piece 530 in Table 1), the soil removal percentage is greater than 100% because the cleaning process also removes some of the small red stop signs below the characteristic soil (which are not always removed because they are not part of the soil), so it is more "white" than the clean baseline reading.

[0082] Table 1

[0083] Test piece Detergent concentration (ppm) RGB color ratio (RG) Dirt removal percentage % Cleaning prediction 499 1582.87 1.24 65 pollute 500 1582.87 1.15 76.25 pollute 501 1582.87 1.09 83.75 pollute 502 1582,87 1.02 92,5 pollute 527 2080.27 0.962 99.75 clean 528 2080.27 0.961 99.875 clean 529 2080.27 0.962 99.75 clean 530 2080.27 0.958 100.25 clean 531 961.12 1.02 92,5 pollute 532 961.12 1.16 75 pollute 533 961.12 1.13 78.75 pollute 534 961.12 1.125 79.375 pollute

[0084] In this embodiment, the detergent concentration is varied, and the dirt removal percentage is determined based on the RG color data. By changing one or more of the wash time, rinse time, detergent type, water hardness, sump pH value, wash temperature, rinse temperature and any other cleaning cycle parameters, similar experiments can be performed during the optimization phase. Digital color data and corresponding dirt removal percentages can be stored as training data to generate a prediction model for determining the effect of the cleaning process by analyzing the color data from the verification test piece. The cleaning process parameters that produce consistent "clean" results based on the color analysis of the verification test piece can be defined as optimized cleaning process parameters. These optimized cleaning process parameter values ​​(or ranges of values) can be stored as cleaning process parameters for use in the same type of automated cleaning machines on which the optimized cleaning process parameters determined empirically have been obtained during the optimization phase. In this way, the articles that use the optimized cleaning process parameters of the cleaning machine for the cleaning process should achieve a "clean" result as long as the optimized cleaning process parameters are met.

[0085] Figure 6 250 is a flow chart showing an example process by which a computing device can determine optimized cleaning process parameters based on color readings from validation test strips corresponding to multiple cleaning processes during an optimization phase. The optimization phase can be an experimental or framework phase that includes performing one or more cleaning processes and changing one or more cleaning process parameters. The cleaning process parameters that can be varied can include wash time, rinse time, detergent type, water hardness, tank pH, wash temperature, rinse temperature, and / or any other cleaning cycle parameters. Color readings, color data, and corresponding cleaning results (e.g., percentage of soil removed or other metrics of "clean" or "contaminated") can be stored as training data to generate a predictive model for determining optimized cleaning process parameters for a cleaning machine or a type of cleaning machine. Cleaning process parameters that produce consistent "clean" results based on color analysis of the validation test strip can be defined as optimized cleaning process parameters. These optimized cleaning process parameter values ​​(or ranges of values) can be stored as optimized cleaning process parameters for use in the same type of automated cleaning machine on which the optimized cleaning process parameters determined empirically were identified during the optimization phase. In this way, the articles that are subjected to the cleaning process using the optimized cleaning process parameters of the cleaning machine should achieve a "clean" result as long as the optimized cleaning process parameters are met.

[0086] The computing device may include a local computing device, such as a mobile computing device, a smart phone, a tablet computer, a laptop computer, a desktop computer, a server computer, a personal digital assistant (PDA), a portable gaming device, a portable media player, an e-book reader, a wearable computing device, a smart watch, a television platform, or any other type of computing device. The computing device may also include a remotely located computing device, such as one or more server computing devices or a cloud-based computing system.

[0087] exist Figure 6 In an embodiment of the present invention, a computing device receives or obtains color sensor readings (252) from one or more validation test pieces corresponding to cleaning processes of multiple experimental designs. The computing device also receives cleaning process parameters (254) corresponding to each of the multiple cleaning processes. The cleaning process parameters are varied, so that the relationship between each cleaning process parameter and the cleaning process result (e.g., clean, contaminated, dirt removal / remaining percentage, etc.) can be determined by analyzing the color sensor readings from each validation test piece. Classification data (256) corresponding to each color sensor reading is also obtained. In other words, each color sensor reading and the corresponding color data can be classified during an optimization or training phase to determine whether the result corresponds to "clean", "contaminated", a percentage of dirt removed or a percentage of dirt remaining, or one or more other metrics classified as cleaning results.

[0088] The computing device identifies optimized cleaning process parameters based on the color readings, the cleaning process parameters, and the classification data corresponding to each cleaning process (258). The optimized cleaning process parameters may include a minimum threshold value for one or more of the cleaning process parameters, a maximum threshold value for one or more of the cleaning process parameters, or a threshold range for one or more of the cleaning process parameters.

[0089] The computing device may also identify adjustments to one or more cleaning process parameters to compensate for non-optimal or substandard cleaning process parameters based on the color readings, cleaning process parameters, and classification data corresponding to each cleaning process (260). In other words, the computing device may identify how to adjust certain cleaning process parameters when a specific cleaning process parameter does not meet an optimized value for the specific cleaning process parameter. For example, the computing device may determine that when a sensed detergent concentration is not within an optimized detergent concentration range, the duration of the wash cycle should be extended by a predetermined period of time to compensate for the failure of the detergent concentration to meet its optimized value, thereby helping to ensure satisfactory cleaning results. In this way, an automated cleaning machine may be programmed with cleaning process parameter adjustments to self-adjust during execution of a real-world cleaning process and help ensure that satisfactory cleaning results are obtained even if the detergent concentration (or other cleaning process parameter) fails to meet its optimized value.

[0090] Figure 7 It is a diagram illustrating adjusting one or more cleaning process parameters to compensate for another cleaning process parameter failing to meet its optimized cleaning process parameter value.Domain 280 represents a whole set of optimized cleaning process parameters, through which a satisfactory or "clean" result can be achieved by the cleaning process in the automated cleaning machine.The cleaning machine can be programmed to perform the cleaning process using these optimized cleaning process parameters in domain 280.Subdomain 282 represents a specific set of cleaning process parameters sensed during the cleaning machine's execution of the first cleaning process.Subdomain 284 represents a specific set of cleaning process parameters sensed during the cleaning machine's execution of the second cleaning process, and subdomain 286 represents a specific set of cleaning process parameters sensed during the cleaning machine's execution of the third cleaning process.For subdomains 282 and 284, the sensed cleaning process parameters are in domain 280, so the cleaning process parameters each meet the threshold value of the optimized cleaning process parameters, so a "clean" result should be achieved.For subdomain 286A associated with the third cleaning process, at least one cleaning process parameter, i.e., a specified cleaning process parameter x, fails to meet its associated optimized cleaning process parameters. Therefore, the third cleaning process represented by subdomain 286A is therefore outside the optimized domain 280. This means that the cleaning process parameters sensed during the third cleaning process represented by subdomain 286A will not achieve a "clean" result. By adjusting the different cleaning process parameters, i.e., the designated cleaning process parameters y, as determined during the training or optimization phase, the third cleaning process can be brought back to domain 280, as represented by subdomain 286B. In this way, the cleaning machine can be programmed to self-adjust during the execution of the cleaning process to help ensure that satisfactory cleaning results are obtained even when certain cleaning process parameters fail to meet their optimization thresholds.

[0091] Figure 8 is a flow chart illustrating an example verification procedure (350) according to the present disclosure, which can be used to verify the effectiveness of a cleaning process in an automated cleaning machine by analyzing color data associated with a verification test strip.

[0092] To begin the cleaning process validation procedure (350), the user inserts one or more cleaning process validation test strips, e.g. Figure 1 The test strip 100 shown is placed in a cleaning chamber (352) of an automated cleaning machine. In some embodiments, the verification procedure is performed when the cleaning machine is empty; in other words, the verification procedure is performed when there are no items to be cleaned in the cleaning chamber of the cleaning machine. In other embodiments, the verification procedure is performed when there are items to be cleaned in the cleaning chamber during the verification procedure. In some embodiments, a cleaning process verification protocol established by an entity may specify whether there should be items to be cleaned during the cleaning process verification procedure.

[0093] The user may include one or more of the following: an employee of the organization where the cleaning machine is located, a service technician, a sales representative, or any other person responsible for running the cleaning process verification program. The cleaning process verification program (350) can be run periodically to confirm that items subjected to the cleaning process in the automated cleaning machine are adequately cleaned. Generally speaking, if the verification test strip does not indicate a "clean" result, the cleaning machine may not have achieved one or more optimized machine settings (also referred to herein as optimized cleaning process parameters or optimized wash cycle parameters), and corrective action may need to be taken.

[0094] The automated cleaning machine may include any type of dishwasher or utensil cleaning machine, including commercial dishwashers, utensil cleaning machines, sanitizers, high or low temperature cleaning machines, conveyor dishwashers, door dishwashers, undercounter dishwashers, glass cleaning machines, deep pot / pan / utensil cleaning machines, etc. The automated cleaning machine may also include any type of medical cleaning equipment, including cleaning machines / decontamination machines, steam sterilizers, autoclaves, ultrasonic cleaning machines, tunnel cleaning machines, cart cleaning machines, etc. The automated cleaning machine may also include a washing machine or any other type of cleaning machine. It should therefore be understood that the present disclosure is not limited to the type of automated cleaning machine or the items to be cleaned.

[0095] Once the verification test strips are placed in the cleaning chamber of the cleaning machine (352), the cleaning machine is run through the selected cleaning process (354). When the cleaning process is complete, the user removes the cleaning process verification test strips from the cleaning chamber of the cleaning machine (356). As a result of the cleaning process, the test indicator on each cleaning process verification test strip will be removed or changed in some way depending on the effectiveness of the cleaning process.

[0096] To validate the cleaning process (i.e. test or confirm the effectiveness of the cleaning process), a color sensor (e.g. Figure 4A The color sensor 208 in the verification test piece is used to scan the verification area (e.g. Figure 1 and Figure 2 The verification area 102 of the cleaning process is located and a color sensor reading associated with the verification area is obtained. The color sensor reading indicates the amount of test indicator (soil) remaining in the verification area after the cleaning process is completed (358).

[0097] For example, the color sensor may include a light source and one or more photodetectors. Each photodetector detects a certain amount of red, green, blue, and / or visible spectrum wavelengths reflected from the verification area and outputs a corresponding color sensor reading indicating the intensity of the detected reflected wavelength. The color sensor may also detect reflected light in the IR and / or UV wavelength ranges.

[0098] The color scan data is uploaded to a computing device (360), and a cleaning validation application on the computing device (e.g., cleaning validation module 206 in computing device 200) analyzes the received color sensor readings associated with the validation area. As part of the analysis, computing device 200 may generate color data based on the color sensor readings, including one or more of the following: a red / green ratio, a blue / green ratio, a red / blue ratio, a red percentage, a green percentage, a blue percentage, a FIJI gray value, or any other color data that can be used to characterize or quantify the amount of color present in the validation area. The results of the analysis and any associated cleaning score (e.g., "pass," "fail," or other determined clean or contaminated level) may be displayed on the user computing device (e.g., Figure 4B ), and the user can view these results (362). If the analysis of the color data indicates that the test indicator has been satisfactorily cleaned (the "yes" branch of 362), the cleaning validation application will verify the cleaning process and generate, for example, a "pass" indication for display. When the cleaning process is verified as satisfactory, no corrective action is required, and the validation process can be repeated as needed or as specified in the cleaning validation protocol (363).

[0099] If the analysis of the color data indicates that the test indicator has not been satisfactorily cleaned (the "no" branch of 362), the cleaning validation application can generate, for example, a "failed" indication for display. The indication can also include one or more suggested corrective actions that can be taken to resolve any potential problems associated with one or more cleaning process variables (366). The suggested corrective actions can include one or more possible reasons for failure (e.g., mechanical failure, chemical failure, user error, or a combination of these) and / or corrective actions that can address the reasons for failure to help ensure that the cleaning machine is functioning properly or that adequate cleaning is performed in subsequent cycles. For example, a failure during a cleaning cycle may be due to a failure of one or more cleaning process parameters, including improper cleaning chemicals, improper cleaning chemical concentrations, insufficient water pressure, poor water quality (hardness or turbidity), incorrect washing or rinsing water temperature, incorrect washing or rinsing cycle duration, operator error, mechanical failure, and / or other factors. The validation procedure (368) can be repeated as needed or desired.

[0100] although Figure 8The example process (350) shown in is described as being at least partially manual in that a user places a verification test strip into a cleaning chamber of a washing machine, removes the verification test strip from the cleaning machine, and scans the verification test strip to obtain a color sensor reading associated with the amount of soil remaining on the test strip, but it should be understood that some or all of these processes may be automated and the present disclosure is not limited in this regard. For example, an automatic verification test strip feeder may advance the verification test strip into the cleaning chamber, and a color sensor may automatically capture a color sensor reading associated with a verification area of ​​the verification test strip when the cleaning process is complete. For example, Figure 3 The dishwasher controller 170 may include or interface with a color sensor that automatically captures color data associated with the verification area of ​​the verification test strip upon completion of the cleaning process.

[0101] Fig. 9 is a flow chart illustrating an example process (370) according to the present disclosure by which a computing device (e.g. Figure 4A And / or the computing device 200 shown in 4B) can verify the effect of the cleaning process by analyzing the color sensor readings associated with the verification test piece. The computing device may include one or more remotely located computing devices, such as a server computer or a computer group, which provides a cloud-based computing service that monitors / or manages the cleaning process performed by one or more automated cleaning machines. For example, the computing device can analyze the color sensor readings associated with one or more verification test pieces, determine the optimized cleaning process parameters, monitor whether the actual cleaning process meets the optimized parameters, determine the adjusted cleaning process parameters, and recommend corrective measures when the cleaning process parameters are not up to standard or when the analysis of the color sensor readings of the verification test piece indicates that the cleaning results are unsatisfactory, generate one or more reports on the data collected during the cleaning process or about the cleaning process, and / or perform any other cleaning process monitoring or management tasks. The computing device may also include a local computing device, such as a mobile computing device, a smart phone, a tablet computer, a laptop computer, a desktop computer, a server computer, a personal digital assistant (PDA), a portable gaming device, a portable media player, an e-book reader, a wearable computing device, a smart watch, a television platform, or any other type of computing device.

[0102] exist Fig. 9In an embodiment of the present invention, a computing device receives a cleaning process verification request (371). As part of the verification process, the computing device receives a color sensor reading associated with a verification area on a cleaning process verification test piece, the color sensor reading corresponding to the amount of test indicator (dirt) remaining after the cleaning process is completed (372). The computing device analyzes the color sensor reading to calculate color data associated with the verification test piece (374). The color data may include one or more RGB ratios, one or more percentage color values, FIJI gray values, one or more intensities, opacity, or any other type of color data. Each component or type of color data (e.g., RGB ratios, FIJI gray values, percentage color values, intensity, opacity, etc.) is compared to one or more corresponding thresholds indicating a satisfactory result of the cleaning process (376). The threshold may include one or more of a minimum threshold, a maximum threshold, a threshold range, etc. The type of threshold may be different for each component of the color data.

[0103] For example, the color data may include one or more of the red-green (RG) color ratio, the red-blue (RB) color ratio, the green-blue (GB) color ratio, and / or the CG color ratio. The color data may also include percentage color values ​​(%R, %B, and / or %G) and / or FIJI gray values. Each color ratio may be compared with one or more corresponding thresholds. Therefore, in this embodiment, the RG color ratio is compared with one or more corresponding RG thresholds, the RB color ratio is compared with one or more corresponding RB thresholds, the GB color ratio is compared with one or more corresponding GB thresholds, and the CG color ratio is compared with one or more corresponding CG color ratios. Similarly, the FIJI gray value may be compared with one or more corresponding FIJI gray thresholds. Similarly, if one or more percentage color values ​​are used in the analysis, %R is compared with the corresponding %R threshold, %G is compared with the corresponding %G threshold, and %B is compared with the corresponding %B threshold. Other types of color data calculations or combinations may also be compared with one or more corresponding color data thresholds, depending on which type of color data is statistically significant when evaluating the effect of the cleaning process for a specific type and color of the test indicator.

[0104] If the analysis of the color data satisfies the corresponding threshold value ("yes" branch of 378), this means that the test indicator was sufficiently removed by the cleaning process, and the computing device can verify that the cleaning process "passed" the verification procedure (380). The computing device can generate a "pass" indication for display on a user interface of the computing device (382), such as Figure 4B as shown in .

[0105] If the analysis of the color data does not satisfy the associated threshold (NO branch of 378), the test indicator was not adequately removed from the substrate by the cleaning process, and thus the cleaning process "failed" the verification procedure (384). The computing device may generate a "fail" indication for display on a user interface of the computing device (388), such as Figure 4B as shown in .

[0106] Additionally, in the event that the cleaning results are unsatisfactory, the computing device may further analyze the color data regarding the cleaning process parameters to identify potential reasons for the unsatisfactory cleaning process results (386). For example, failure of certain color data to meet one or more parameter-specific thresholds may indicate a potential problem with one or more cleaning process parameters. The failure indication (388) may also include an identification of a potential failure in the cleaning process and a suggested corrective action that may be taken to resolve the potential failure.

[0107] Fig.10 400 is a block diagram of an example cleaning machine controller 400, which is programmed to automatically adjust one or more cleaning process parameters during the execution of the cleaning process to compensate for the sensed cleaning process parameters failing to meet the optimization parameter values ​​associated therewith. The controller 400 includes one or more processors 402, one or more user interface components 406, one or more communication interfaces 404, and a data storage medium 408. The user interface component 406 may include one or more audio or visual indicators and / or touch-based interface components, including, for example, a touch screen display, a button, a keypad, or other mechanisms that allow a user to interact with the cleaning machine. The communication interface 404 allows the controller 400 to communicate with other remote or local computing devices by wired and / or wireless connections. Wired and / or wireless communication may include communication, Bluetooth communication, near field communication, and / or the Internet, such as any type of local area network or wide area network including Wi-Fi networks. The data storage medium 408 includes a cleaning process control module 410, an optimized cleaning process parameter memory 412, and a data memory 414. The cleaning process control module 410 includes computer-readable instructions that, when executed by the one or more processors 402, cause the one or more processors 402 to control the operation of the cleaning process, analyze sensor data received during the cleaning process to determine whether any cleaning process parameters are out of specification with respect to each other, and automatically adjust one or more cleaning process parameters when any cleaning process parameter is determined to be out of specification (e.g., does not meet an optimized parameter value).

[0108] The cleaning machine controller 400 can receive input from one or more sensors 420, which sense the actual value of the cleaning process parameter during the actual cleaning process. The sensor 420 can include, for example, one or more temperature sensors, tank turbidity sensors, conductivity sensors, pH sensors, flow sensors, pressure sensors, or any other sensors capable of sensing the actual value of one or more cleaning process parameters during or associated with the cleaning process. According to the instructions contained in the cleaning process control module 410, the sensed cleaning process parameters can be compared with the optimized cleaning process parameters 412. If the controller 400 senses the difference between the optimized cleaning process parameters and any sensed (actual) cleaning process parameters, the cleaning process control module 410 can make the controller 400 automatically adjust one or more cleaning process parameters when executed by the one or more processors 402 to compensate for any non-optimized cleaning process parameters detected during the cleaning process. In this way, the automated cleaning machine can self-adjust to compensate for any non-optimized cleaning process parameters to help avoid potential unsatisfactory cleaning results.

[0109] Fig.11 is a flow chart illustrating an example process (420) in which a computing device (e.g. Fig.10 The cleaning machine controller 400 shown in the figure can automatically adjust one or more cleaning process parameters to compensate for one or more cleaning process parameters failing to meet their respective target parameter values ​​through the process. The computing device starts the cleaning process (422) and receives cleaning process parameter data from one or more sensors associated with the cleaning process. At least some of the sensed cleaning process parameter data have corresponding optimized cleaning process parameter values, and as long as the cleaning machine remains within the predefined optimization range of these cleaning process parameters, satisfactory cleaning results should be obtained. In order to help ensure satisfactory cleaning results, the computing device compares the sensed cleaning process parameter values ​​with the corresponding stored optimization parameter values ​​(426). If any sensed cleaning process parameters are out of specification (e.g., they are not within the target or threshold range or do not meet the target or threshold of the corresponding cleaning process parameters) (the "yes" branch of 428), the computing device can adjust one or more different cleaning process parameters to compensate for the cleaning process parameters failing to meet their optimized parameter values ​​(440).

[0110] For example, depending on which cleaning process parameter fails to meet its optimized parameter value, and / or how the cleaning process parameter fails to meet its optimized parameter value (e.g., sensed value is too high, sensed value is too low, etc.), the computing device may perform any one or more of the following operations: extend or increase the duration of the wash cycle; reduce the duration of the wash cycle; extend or increase the duration of the rinse cycle; reduce the duration of the rinse cycle; increase the detergent concentration; reduce the detergent concentration; increase the rinse aid concentration; reduce the rinse aid concentration; increase the wash (sump) water temperature; reduce the wash (sump) water temperature; increase the rinse water temperature; reduce the rinse water temperature; increase the inlet water temperature; reduce the inlet water temperature; initiate a sump water dump / fill cycle; initiate a dust removal cycle; and / or perform any other cleaning process parameter adjustments (442). The cleaning process then continues using the adjusted cleaning process parameters (444) to help ensure that satisfactory cleaning results are achieved even if certain cleaning process parameters do not meet their respective optimized parameter values.

[0111] If the sensed cleaning process parameters are within their respective target or threshold ranges or meet their respective targets or thresholds (the "No" branch of 428), the computing device continues the cleaning process using the current cleaning process parameters (430). The process continues (432) until the cleaning process is completed (434).

[0112] Fig.12 6 is a block diagram of a computing system environment 601 for analyzing color readings associated with one or more verification test strips according to the present disclosure. One or more enterprises 602A-602N each include one or more cleaning machines 604A-604N and one or more computing devices 606A-606N, respectively. The computing devices 606A-606N can receive color sensor readings obtained by color sensors 608A-608N from color scans of verification test strips 100A-100N, respectively. The color readings can be transmitted to a server computing device 650 via a network 640 for analysis.

[0113] The server computing device 650 can remotely receive and analyze color sensor readings associated with one or more cleaning processes collected by the local computing devices 606A-606N. In this sense, the server computing device 650 can provide a so-called cloud-based service for verifying the cleaning processes occurring at one or more locations or businesses 602A-602N associated with each computing device 606A-606N, respectively.

[0114] The server computing device 650, the local computing devices 606A-606N, and the remote computing device 630 communicate using one or more networks 640. The network 640 may include, for example, one or more of the following: a dial-up connection, a local area network (LAN), a wide area network (WAN), the Internet, a wireless Wi-Fi network, a mobile phone network, a satellite communication network, Bluetooth, ZigBee, near field communication (NFC), and / or any other short-range or long-range electronic communication method. Communications within the network 640 may be wired or wireless or any combination thereof. The remote computing device 630 may include, for example, one or more of the following: a server computing device, a desktop computing device, a laptop computing device, a tablet computing device, a mobile computing device (e.g., a smart phone), a personal digital assistant, a pager, or any other type of computing device.

[0115] Color sensors 608A-608N may be used to capture color sensor readings associated with one or more verification test strips 100A-100N and transmit the color sensor readings to an associated one of a plurality of local computing devices 606A-606N. In some embodiments, local computing devices 606A-606N may be associated with a single user, enterprise, business entity, or location. In other embodiments, some of local computing devices 606A-606N are associated with one enterprise, business entity, or location, while other local computing devices 606A-606N are associated with separate, unrelated enterprises, business entities, or locations. For example, in a chain restaurant environment, some of local computing devices 606A-606N may be associated with different locations of the chain restaurant, while each of local computing devices 606A-606N is associated with the same parent company or business enterprise. Meanwhile, other of the local computing devices 606A-606N may be associated with entirely separate and unrelated locations or business entities, such as one or more different restaurants, hotels, healthcare facilities, or other locations / business entities in which the validation test strips described herein are used to validate the cleaning process.

[0116] The server computing device 650 includes one or more processors 652 and one or more data storage media 658. The server computing device 650 may also include one or more user interface components 654 and one or more communication interface components 656. The communication interface components 656 allow the server computing device 650 to communicate with one or more of the computing devices 606A-606N and the remote / local computing devices 630 via the network 640.

[0117] The storage medium 658 includes a cleaning validation hosting module 660 , a cleaning validation analysis module 662 , enterprise / site data 664 , cleaning validation data 668 , an optimized parameter determination module 670 , optimized parameter data 672 , wash cycle data 674 , and storage for one or more reports 676 .

[0118] The cleaning validation hosting module 660 includes computer readable instructions that, when executed on the one or more processors 652, cause the processors 652 to host a cleaning process validation service for one or more of the computing devices 606A-606N. For example, the cleaning validation hosting module 660 may include instructions that enable the server computing device 650 to execute one or more cleaning process validation procedures (e.g., by analyzing color readings obtained from a color scan of a validation test strip exposed to a cleaning process), store the results, and transmit the results to the appropriate user computing devices 606A-606N or remote computing device 630.

[0119] The cleaning validation analysis module 662 includes computer readable instructions that, when executed on the one or more processors 652, cause the processors to receive and analyze color sensor readings received from the computing devices 606A-606N. The cleaning validation hosting module 660 may also include computer readable instructions that, when executed by the one or more processors 652, cause the one or more processors 652 to generate one or more notifications regarding the results of the cleaning process validation procedure for display, for example, on a user interface of an appropriate local computing device 606A-606N. For example, Figure 4B The notifications 216 and 218 on the touch screen display 222 in FIG. 2 may be generated remotely by the server computing device 650 hosting the cloud-based cleaning process validation service, rather than being generated locally by the user computing device 200 .

[0120] The enterprise / location data 664 may include data about each enterprise and / or location for which the server computing device 650 provides cleaning process validation services. For example, the enterprise / location data 664 may include company data related to the enterprise or location, location identification information, location type (e.g., restaurant, healthcare facility, etc.), types and identifiers of cleaning machines at each location, cleaning machine rack identifiers associated with each location, employee lists and identification information, data associating one or more computing devices (e.g., one or more of computing devices 606A-606N) with each location or enterprise, company and / or location cleaning process goals and tolerances, and other data related to the enterprise, the location, and / or the cleaning process at each location.

[0121] Cleaning validation data 668 may include color sensor readings received from computing devices 606A-606N and any associated data, such as data input by a user when scanning, date and time stamps associated with color sensor readings, etc. Cleaning validation data 668 may also include data generated by cleaning validation hosting module 660 or cleaning validation analysis module 662 in the process of executing cleaning process validation procedures. Washing cycle data 674 may include data obtained or generated for multiple washing cycles by cleaning machines 604A-604N present at each monitored location or enterprise 602A-602N. The washing cycle data of each washing cycle may include, for example, location identifier, rack identifier, rack type, cleaning machine identifier, date / time stamp, cycle time and length, water temperature setting, cleaning machine setting, chemical cleaning product dispenser setting, dispensing time and dispensing amount of chemical cleaning products, and any other data related to the washing cycle. Wash cycle data 674 may also include any sensed cleaning process parameter data, including wash and / or rinse cycle start and / or stop times, wash and / or rinse water temperature, sump temperature, pH, turbidity, conductivity, information related to detergent concentration or rinse aid concentration, or any other information sensed during the cleaning process.

[0122] The cleaning validation hosting module 660 may also include a reporting function by which the server computing device 650 may generate one or more reports regarding the cleaning process validation data 668, the enterprise / location data 664, and / or the wash cycle data 674 for transmission to and / or display by one of the computing devices 606A-606N and / or the remote computing device 630. For example, Figure 4B Activation of notification 216 on touch screen 222 may result in generation by server computing device 650 of a more detailed report for display on touch screen 222 regarding the cleaning process performed on August 7, 2018 using verification test strip serial number A10456-52 and receiving a “fail”.

[0123] The following is an example detailed report for a cleaning process corresponding to validation coupon serial number A10456-52, including example cleaning process validation data and associated example wash cycle data.

[0124] Cleaning cycle overview

[0125] Date / Time August 7, 2018 02:35:14 Place Store 302, St. Paul, Minnesota Verification test piece Serial number A10456-52 Cleaning Validation Scoring Failed Test piece type Food Dirt 3 Machine Type Single rack / high temperature Shelf Type tableware Cycle Type tableware Employee ID 555-5555

[0126] Cleaning cycle details

[0127]

[0128]

[0129] In this example, the water temperatures for both the wash cycle and the sanitizer rinse cycle were too low (the wash water temperature for the clean cycle was 128°F, with a target water temperature of 155°F minimum, and the sanitizer rinse water temperature for the clean cycle was 145°F, with a target sanitizer rinse water temperature of 180°F minimum). Therefore, the reason the clean cycle failed the validation procedure may be that the wash cycle and sanitizer rinse water temperatures were too low. The last column of the detailed report includes possible reasons / causes for the failure and / or methods to resolve the failure.

[0130] As another example, one or more remote computing devices 630 may request a report that includes data corresponding to one or more specific cleaning processes, or data regarding cleaning processes at one or more specific locations, dates, times, employees, cleaning scores, etc. Such data may be used to identify trends, areas for improvement, or otherwise help personnel responsible for ensuring the effectiveness of the cleaning processes identify and resolve problems in the cleaning processes.

[0131] Described report can comprise the information of one or more cleaning processes / cycles, and the data of each cleaning process can comprise for example the following information: the date and time of cleaning process, the unique identification of cleaning process, the unique identification of the personnel of operation cleaning process and / or cleaning verification program, the type of article cleaned during cleaning process, the type of shelf or tray used during cleaning process, the type of article cleaned during cleaning process, the type and quantity of chemical products dispensed during each cycle of cleaning process, the amount of water dispensed during each cycle of cleaning process, the "passing" or "failed" indication of cleaning process, the image of cleaning process verification test piece, or other information relevant to cleaning process or cleaning process verification program.Report can also comprise the information about how many test indicators have been removed and / or how many test indicators remain.Report can also comprise the information about determined color data corresponding to verification program.Report can also comprise the information about the possible reasons that cleaning process fails (for example, be hardware-related failure, chemical-related failure or possible user error), and / or be used to solve the suggestion correction that fails. The report may also include information regarding: location; business entity / enterprise; company cleaning validation goals and tolerances; cleaning scores by location, zone, machine type, date / time, employee, and / or cleaning chemical type; energy costs; chemical product costs; and / or any other cleaning process data collected or generated by the system or requested by the user.

[0132] The cleaning validation hosting module 660 and the cleaning validation analysis module 662 include computer readable instructions that, when executed by the processor 652, cause the processor 652 to receive color data associated with the validation test strips 100A-100N. The cleaning validation hosting module 660 includes computer readable instructions that, when executed on one or more processors 652, cause the processor 652 to provide cleaning process validation services and, in doing so, perform a plurality of cleaning process validation procedures. In some embodiments, the cleaning validation hosting module 660 includes computer readable instructions that are configured to execute on one or more processors 652 to perform the same as described above. Figure 6 A process similar to the example process (250) shown in FIG. Fig. 9 A process similar to the example process (370) shown in FIG. Fig.11 The example process (420) shown is similar to the process.

[0133] For example, the server computing device 650 can execute the hosting module 660 to manage the communication between the server computing device 650 and one or more user computing devices 606A-606N, and execute the cleaning process verification program between the user computing devices 606A-606N and the server computing device 300. For example, the server computing device 650 can receive a request for the cleaning process verification program and related color data from one or more computing devices in the computing devices 606A-606N (371). The color data from each computing device 606A-606N may include a color sensor reading associated with a verification area of ​​the verification test piece. The server computing device 650 can use, for example, a cleaning verification analysis module 662 to analyze the color sensor reading. The analysis module 662 can generate color data (374) based on the received color sensor reading. The analysis module 662 can further analyze the color data by, for example, comparing the color data with one or more thresholds (376, 378), and determine or verify the effect of the cleaning process based on the analysis of the color data.

[0134] If the analysis indicates that the color data meets one or more thresholds (378), the results of the cleaning process can be verified to be satisfactory (380). The server computing device can generate and store and / or transmit a pass indication for display by an associated user computing device in the user computing devices 606A-606N. Alternatively, if the analysis indicates that the color data does not meet one or more thresholds, the results of the cleaning process are unsatisfactory (384). The server computing device can further identify potential failures and recommended corrective actions that can be taken to resolve the potential failures (386). The server computing device 650 can generate and transmit a fail indication for display by an associated user computing device in the user computing devices 606A-606N (388).

[0135] Although the embodiments presented herein are described with respect to automated cleaning machines for medical or food preparation / processing applications, it should be understood that the cleaning process validation techniques described herein may be applied to a variety of other applications. Such applications may include, for example, laundry applications, agricultural applications, hotel applications, and / or any other application in which cleaning, sterilizing, or disinfecting of items may be useful.

[0136] In one or more embodiments, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include: computer-readable storage media corresponding to tangible media such as data storage media, or communication media, including any media that facilitates, for example, transferring a computer program from one place to another according to a communication protocol. In this manner, computer-readable media may generally correspond to (1) non-temporary tangible computer-readable storage media, or (2) communication media such as signals or carrier waves. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, codes, and / or data structures for implementing the techniques described in the present disclosure. A computer program product may include a computer-readable medium.

[0137] By way of example and not limitation, such computer-readable storage media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage devices, magnetic disk storage devices or other magnetic storage devices, flash memory, or any other medium that can be used to store the desired program code in the form of instructions or data structures and can be accessed by a computer. Moreover, any connection is appropriately referred to as a computer-readable medium. For example, if a coaxial cable, optical fiber cable, twisted pair, digital subscriber line (DSL) or wireless technologies such as infrared, radio and microwave are used to transmit instructions from a website, server or other remote source, then the coaxial cable, optical fiber cable, twisted pair, DSL or wireless technologies such as infrared, radio and microwave are included in the definition of the medium. However, it should be understood that computer-readable storage media and data storage media do not include connections, carrier waves, signals or other temporary media, but rather relate to non-temporary tangible storage media. As used, disks and optical disks include compact disks (CDs), laser optical disks, optical disks, digital versatile disks (DVDs), floppy disks and blue-ray disks, wherein disks usually reproduce data magnetically, and optical disks reproduce data optically with lasers. The above combination should also be included in the scope of computer-readable media.

[0138] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuit systems. Thus, the term "processor" as used may refer to any of the foregoing structures or any other structure suitable for implementing the described techniques. Additionally, in some embodiments, the described functionality may be provided within dedicated hardware and / or software modules. Moreover, the techniques may be fully implemented in one or more circuits or logic elements.

[0139] The techniques of the present disclosure may be implemented in a variety of devices or apparatuses, including wireless handheld devices, integrated circuits (ICs) or groups of ICs (e.g., chipsets). Various components, modules, or units are described in this disclosure to emphasize the functional aspects of devices configured to perform the disclosed techniques, but do not necessarily need to be implemented by different hardware units. Instead, as described above, in conjunction with suitable software and / or firmware, the various units may be combined in a hardware unit or provided by a series of interoperating hardware units including one or more processors as described above.

[0140] It should be appreciated that, depending on the embodiment, certain actions or events of any of the methods described herein may be performed in a different order, may be added, combined, or omitted entirely (e.g., not all described actions or events are required to practice the methods). In addition, in some embodiments, actions or events may be performed simultaneously rather than sequentially, such as through multithreading, interrupt processing, or multiple processors.

[0141] In some embodiments, computer-readable storage media may include non-transitory media. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier wave or propagating signal. In some embodiments, non-transitory storage media may store data that may change over time (e.g., in RAM or cache memory).

[0142] Example

[0143] Embodiment 1. A system for determining effectiveness of a cleaning process based on color data from a validation coupon exposed to the cleaning process, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value.

[0144] Embodiment 2. A method of determining effectiveness of a cleaning process based on color data from a validation coupon exposed to the cleaning process, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value.

[0145] Embodiment 3. A method for training a computer system to determine the effectiveness of a cleaning process based on color data from multiple validation test strips exposed to multiple experimental cleaning processes, wherein the color data includes at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value.

[0146] Embodiment 4. An automated cleaning machine, which receives sensed values ​​of one or more cleaning process parameters during execution of a cleaning process, determines whether one or more of the sensed values ​​do not satisfy their respective optimized cleaning process parameter values, and adjusts the cleaning machine settings associated with a different one of the cleaning process parameters to ensure satisfactory cleaning results during execution of a subsequent cleaning process.

[0147] Embodiment 5. An automated cleaning machine, comprising: at least one processor; at least one sensor that senses information about one or more cleaning process parameters during execution of a cleaning process in a cleaning chamber of the cleaning machine; and a storage device that includes instructions executable by the at least one processor to perform the following operations: receiving sensed information about the one or more cleaning process parameters during execution of the cleaning process; determining, based on the sensed information, whether one or more of the cleaning process parameters sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values; and adjusting a cleaning machine setting associated with a different one of the cleaning process parameters.

[0148] Embodiment 6. The system of Embodiment 5, wherein the one or more cleaning process parameters sensed during execution of the cleaning process include wash cycle duration, rinse cycle duration, detergent concentration, wash water temperature, and rinse water temperature.

[0149] Embodiment 7. The system of Embodiment 5, wherein the one or more cleaning process parameters sensed during performance of the cleaning process include rinse aid concentration or inlet water temperature.

[0150] Embodiment 8. The system of Embodiment 5, wherein the one or more cleaning process parameters include wash water temperature, and wherein the adjusted cleaning machine setting includes wash cycle duration.

[0151] Embodiment 9. The system of Embodiment 5, wherein the one or more cleaning process parameters include detergent concentration, and wherein the adjusted cleaning machine setting includes wash cycle duration.

[0152] Embodiment 10. The system of Embodiment 5, wherein the one or more cleaning process parameters include wash water temperature, and wherein the adjusted cleaning machine setting includes detergent concentration.

[0153] Example 11. The system of Example 5, wherein the storage device further comprises instructions executable by the at least one processor to initiate a sump water dump / fill cycle.

[0154] Embodiment 12. The system of embodiment 5, wherein the storage device further comprises instructions executable by the at least one processor to initiate an ash removal cycle.

[0155] Embodiment 13. The automated cleaning machine of embodiment 5, wherein the storage device further comprises instructions executable by the at least one processor to perform the following operations: generating a notification indicating that one or more of the cleaning process parameter values ​​sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values.

[0156] Embodiment 14. An automated cleaning machine of embodiment 13, wherein the storage device further comprises instructions executable by the at least one processor to perform the following operations: generating a notification comprising one or more corrective measures, which may be taken to resolve a failure of the one or more cleaning process parameters to satisfy the corresponding optimized cleaning process parameter values.

[0157] Embodiment 15. The automated cleaning machine of embodiment 5, wherein the storage device further comprises instructions executable by the at least one processor to perform the following operations: applying the adjusted cleaning process parameters during execution of the cleaning process.

[0158] Embodiment 16. The automated cleaning machine of embodiment 5, wherein the storage device further comprises instructions executable by the at least one processor to perform the following operations: applying the adjusted cleaning process parameters during execution of a subsequent cleaning process.

[0159] Embodiment 17. A non-volatile computer-readable storage medium storing instructions which, when executed, cause one or more processors to: receive sensed information about one or more cleaning process parameters during execution of a cleaning process in a cleaning chamber of a cleaning machine; determine, based on the sensed information, that one or more of the cleaning process parameters sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values; and adjust a cleaning machine setting associated with a different one of the cleaning process parameters.

[0160] Embodiment 18. A system comprising: an automated cleaning machine, comprising: at least one processor; at least one sensor that senses information about one or more cleaning process parameters during execution of a cleaning process in a cleaning chamber of the cleaning machine; and a storage device that includes instructions executable by the at least one processor to perform the following operations: receiving sensed information about the one or more cleaning process parameters during execution of the cleaning process; determining, based on the sensed information, whether one or more of the cleaning process parameters sensed during execution of the cleaning process do not satisfy corresponding optimized cleaning process parameter values; and adjusting a cleaning machine setting associated with a different one of the cleaning process parameters.

[0161] Embodiment 19. The system of embodiment 18 further includes: a computing device comprising: at least one processor; a storage device comprising instructions executable by the at least one processor of the computing device to perform the following operations: obtaining color data from a verification test strip exposed to the cleaning process, wherein the color data comprises at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value; and determining the effectiveness of the cleaning process based on the color data.

[0162] Embodiment 20. The system of embodiment 19, wherein the characteristic soil comprises a food-based soil.

[0163] Example 21. The system of Example 19, wherein the characteristic foulant includes organic foulant.

[0164] Various embodiments have been described. These and other embodiments are within the scope of the following claims.

Claims

1. An automatic cleaning machine, comprising: Washing room; at least one processor; at least one sensor; as well as A memory device comprising instructions executable by the at least one processor to: performing a first plurality of cleaning processes in the cleaning chamber; obtaining color sensor readings of a plurality of validation test strips exposed to the first plurality of cleaning processes, wherein one or more values ​​of cleaning process parameters are adjusted between each cleaning process of the first plurality of cleaning processes, and wherein the cleaning process parameters include at least a first cleaning process parameter and a second cleaning process parameter different from the first cleaning process parameter; generating color data from color sensor readings of the plurality of verification test strips; determining one or more optimized values ​​for the cleaning process parameters of the automated cleaning machine based on the color data generated from the color sensor readings, wherein determining the one or more optimized values ​​for the cleaning process parameters comprises: determining, based on the color data, the optimized values ​​for the cleaning process parameters to produce clean results for items subjected to the first plurality of cleaning processes, wherein the optimized values ​​for the cleaning process parameters include the optimized value for the first cleaning process parameter; performing a second cleaning process in a cleaning chamber of the automated cleaning machine, wherein the second cleaning process occurs in a time period after the first plurality of cleaning processes; receiving sensed information about at least the first cleaning process parameter from the at least one sensor during performance of the second cleaning process; determining, based on the sensed information, that a value of the first cleaning process parameter sensed during execution of the second cleaning process does not satisfy an optimized value of the first cleaning process parameter; adjusting a cleaning machine setting associated with the second cleaning process parameter based on the value of the first cleaning process parameter not satisfying the optimized value of the first cleaning process parameter; and The adjusted cleaning machine settings associated with the second cleaning process parameters are applied during performance of the second cleaning process to obtain a cleaning result.

2. The automated cleaning machine of claim 1, wherein the cleaning process parameters include at least one of a wash cycle duration, a rinse cycle duration, a detergent concentration, a wash water temperature, and a rinse water temperature. 3 . The automated cleaning machine according to claim 1 , wherein the cleaning process parameter comprises a rinse aid concentration or an inlet water temperature.

4. The automated cleaning machine of claim 1, wherein the cleaning process parameters include wash water temperature, and wherein the adjusted cleaning machine settings include wash cycle duration.

5. The automated cleaning machine of claim 1, wherein the cleaning process parameters include detergent concentration, and wherein the adjusted cleaning machine settings include wash cycle duration.

6. The automated cleaning machine of claim 1, wherein the cleaning process parameters include wash water temperature, and wherein the adjusted cleaning machine settings include detergent concentration.

7. The automated cleaning machine of claim 1, wherein the memory device further comprises instructions executable by the at least one processor to initiate a sump water dump / fill cycle.

8. The automated cleaning machine of claim 1, wherein the memory device further comprises instructions executable by the at least one processor to initiate a dust removal cycle.

9. The automated cleaning machine of claim 1 , wherein the storage device further comprises instructions executable by the at least one processor to: A notification is generated indicating that a value of the first cleaning process parameter sensed during execution of the second cleaning process does not satisfy an optimized value of the first cleaning process parameter.

10. The automated cleaning machine of claim 9, wherein the storage device further comprises instructions executable by the at least one processor to: A notification is generated that includes one or more corrective actions that can be taken to address the failure of the value of the first cleaning process parameter to meet the optimized value of the first cleaning process parameter.

11. The automated cleaning machine of claim 1 , wherein the storage device further comprises instructions executable by the at least one processor to: The adjusted cleaning machine settings are applied during a cleaning process that is subsequent to performing the second cleaning process.

12. A non-transitory computer-readable storage medium storing instructions that, when executed, cause one or more processors to: performing one or more of a first plurality of cleaning processes in a cleaning chamber of an automated cleaning machine; obtaining color sensor readings of a plurality of validation coupons exposed to the first plurality of cleaning processes, wherein: adjusting one or more values ​​of cleaning process parameters between each cleaning process of the first plurality of cleaning processes, wherein the cleaning process parameters include at least a first cleaning process parameter and a second cleaning process parameter different from the first cleaning process parameter; generating color data from color sensor readings of the plurality of verification test strips; determining one or more optimized values ​​for the cleaning process parameters of the automated cleaning machine based on the color data generated from the color sensor readings, wherein determining the one or more optimized values ​​for the cleaning process parameters comprises: determining, based on the color data, the optimized values ​​for the cleaning process parameters to produce clean results for items subjected to the first plurality of cleaning processes, wherein the optimized values ​​for the cleaning process parameters include the optimized value for the first cleaning process parameter; performing a second cleaning process in a cleaning chamber of the automated cleaning machine, wherein the second cleaning process occurs in a time period after the first plurality of cleaning processes; receiving sensed information about at least the first cleaning process parameter from the at least one sensor during performance of the second cleaning process; determining, based on the sensed information, that a value of the first cleaning process parameter sensed during execution of the second cleaning process does not satisfy an optimized value of the first cleaning process parameter; adjusting a cleaning machine setting associated with the second cleaning process parameter based on the value of the first cleaning process parameter not satisfying the optimized value of the first cleaning process parameter; and The adjusted cleaning machine settings associated with the second cleaning process parameters are applied during performance of the second cleaning process to obtain a cleaning result.

13. A system comprising: An automated cleaning machine comprising: at least one processor; at least one sensor that senses information about one or more cleaning process parameters during a cleaning process performed in a cleaning chamber of the automated cleaning machine; and A memory device comprising instructions executable by the at least one processor to: performing one or more of a first plurality of cleaning processes in a cleaning chamber of an automated cleaning machine; obtaining color sensor readings of a plurality of validation test strips exposed to the first plurality of cleaning processes, wherein one or more values ​​of cleaning process parameters are adjusted between each cleaning process of the first plurality of cleaning processes, and wherein the cleaning process parameters include at least a first cleaning process parameter and a second cleaning process parameter different from the first cleaning process parameter; generating color data from color sensor readings of the plurality of verification test strips; determining one or more optimized values ​​for the cleaning process parameters of the automated cleaning machine based on the color data generated from the color sensor readings, wherein determining the one or more optimized values ​​for the cleaning process parameters comprises: determining, based on the color data, the optimized values ​​for the cleaning process parameters to produce clean results for items subjected to the first plurality of cleaning processes, wherein the optimized values ​​for the cleaning process parameters include the optimized value for the first cleaning process parameter; performing a second cleaning process in a cleaning chamber of the automated cleaning machine, wherein the second cleaning process occurs in a time period after the first plurality of cleaning processes; receiving sensed information about at least the first cleaning process parameter from the at least one sensor during performance of the second cleaning process; determining, based on the sensed information, that a value of the first cleaning process parameter sensed during execution of the second cleaning process does not satisfy an optimized value of the first cleaning process parameter; adjusting a cleaning machine setting associated with the second cleaning process parameter based on the value of the first cleaning process parameter not satisfying the optimized value of the first cleaning process parameter; and The adjusted cleaning machine settings associated with the second cleaning process parameters are applied during performance of the second cleaning process to obtain a cleaning result.

14. The system of claim 13, further comprising: A computing device comprising: at least one processor; A storage device comprising instructions executable by the at least one processor of the computing device to: obtaining the color data, wherein the color data comprises at least one of a red-to-green ratio, a blue-to-green ratio, a red-to-blue ratio, or a percentage color value; and The effectiveness of the cleaning process is determined based on the color data.

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