DESC:FIELD
The present disclosure relates to management of industrial assets and more specifically to management of metallic assets used by compression/ injection molding machines and stamping machines.
DEFINITIONS
As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used indicate otherwise.
Asset – The term “asset” used hereinafter in this specification refers to a mold or a tool that is used for production with compression / injection molding machines.
Edge Analytics –The expression “edge analytics” used hereinafter in this specification refers to, but is not limited to, collection, processing, and analysis of data at the edge of a network either at or close to sensor(s), a network switch or some other connected device.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
Injection Molding is an advanced manufacturing process used for production of complex, high volume components with a high production rate. This process is capable of producing intricate and small parts in high volume with a few shots as compared to other manufacturing/ fabrication processes. Injection /compression molding is considered as a special process and it is extremely critical to maintain the process parameters such as curing time, clamping pressure, top and bottom plate temperature, bumping cycles and bumping pressure throughout the production process.
The current practice is to measure and record these parameters for first, middle and last part manually. This practice is prone to human error and may result into rejection of partial or complete batch if the process parameters are not set and inspected properly. The need is therefore felt to continuously monitor the production process for every part and raise an alert to user in case of deviation from ideal set of parameters. It is also important to provide active intervention in terms of remote stop of machine in case of deviation from ideal process parameters to avoid wastage or supply of faulty parts.
One of the critical process parameters is maintenance status of the asset being used for production, as ill maintained asset will eventually result into manufacturing of defective parts, the need is therefore felt to generate shot and time based maintenance alerts to carry out preventive maintenance of the asset.
Being a special process it is important that machine is operated by trained operators. The need is therefore felt to authenticate the operators using the machine. One important aspect to meet the quality requirements is to establish a valid pair between asset and machine before the start of manufacturing. The need is therefore felt to ensure that the correct machine and asset pair is used for manufacturing. Apart from this it is also important to identify the location of an asset in production plant for accessibility and tracking.
Existing tool management systems do not provide a means for monitoring various critical process parameters like clamping and bumping pressures, number of bumps, bumping stay, bumping gap and temperature of the top and bottom plates of the molds used in the machines. Existing machine monitoring systems on the other hand do monitor some or all of the above mentioned parameters, but they have no mechanism to identify the asset and hence fail to determine the ideal process parameters thus making the system incomplete from the view point of process monitoring.
Moreover, existing systems do not facilitate online monitoring of various parameters and remote control of the machine. Further, the existing systems also do not provide any means of authorizing an operator before allowing the operator to use the machine. Moreover, real-time location and condition of the asset cannot be monitored using the prevailing asset management systems. Thus, manual monitoring of the system greatly restricts the production efficiency.
The existing systems do not require any clearance between the assets and the machine before starting the operation. Further, existing systems do not provide fault detection and notification to the authorized worker. Existing tool management systems also do not provide a combined GPS and UHF RFID tag based mechanism to monitor the location of an asset within production plant.
Therefore, there is felt, a need for an integrated system for management of assets in terms of life, location, maintenance and process monitoring that eliminates the above-mentioned drawbacks of the existing systems.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
It is an object of the present disclosure to ameliorate one or more problems of the prior art or to at least provide a useful alternative.
An object of the present disclosure is to provide systems and methods for managing and tracking assets.
Another object of the present disclosure is to provide a system that facilitates remote monitoring and control of machines.
Yet another object of the present disclosure is to provide a system that can monitor power consumption of machines used in manufacturing or fabrication processes.
Yet another object of the present disclosure is to provide an asset management system that does not allow starting of manufacturing/ fabrication process without obtaining clearance between the asset and the machine.
Yet another object of the present disclosure is to provide an asset management system that monitors temperature of the assets, clamping and bumping pressure and total shot count.
Yet another object of the present disclosure is to provide an asset management system that prevents unauthorized use of the machine.
Yet another object of the present disclosure is to provide an asset management system that detects faults in the machine and sends fault notifications to the authorized operators.
Yet another object of the present disclosure is to provide an asset tracking system for accurately tracking the location of an asset within a plant.
Yet another object of the present disclosure is to provide an asset management system that tracks the maintenance status of the mold and sends a maintenance due notification to authorised operator.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
In one aspect of the invention, a system for managing assets used in injection and compression molding machines is envisaged. Each of the assets is associated with a unique asset identifier and each of the molding machines is associated with a unique machine identifier. The system comprises an asset-mounted identification tag, an information management server, and a machine-mounted edge analytics unit. The identification tag comprises a local memory configured to store the associated unique asset identifier and a plurality of reference values of molding process parameters. The molding process parameters include mold temperature, injection pressure, clamping pressure, bumping pressure, number of bumps, bumping stay, bumping gap, curing time, and total number of shots produced at any specific point of time.
The information management server comprises a database configured to store a list of valid pairs of asset and machine identifiers and ideal values of process parameters associated with each of the valid pairs, and pre-determined identification information associated with operators authorized to operate the machines. The machine-mounted edge analytics unit is communicatively coupled to the information management server. The machine-mounted edge analytics unit comprises a repository and a validation module. The repository is configured to store the associated unique machine identifier. The validation module is configured to authorize an operator to operate the machine based on a received identification information and the pre-determined identification information, and is further configured to validate an asset for use in the machine based on the unique asset identifier and the valid pairs of identifiers. The analytical engine is configured to obtain reference values of process parameters from at least one of the information management server and the identification tag based on the asset identifier and machine identifier pair, obtain actual values of process parameters from a plurality of sensors located on the machine, determine usage schedules, idle time, and productivity of the asset, detect abnormal operating conditions and generate alerts based on the obtained actual and reference values, and transmit the obtained actual values to the information management server for facilitating remote monitoring and management of the asset.
The sensors include top mold plate temperature sensor, bottom mold plate temperature sensor, pressure sensor, shot counter, and curing time sensor.
In another aspect of the invention, the present disclosure envisages a system for tracking movement of assets within a pre-defined area. Each asset is carried by a fork lift and provided with an identification tag which stores a unique asset identifier in its local memory. The system comprises a plurality of floor-mounted identification tags, a pair of pallet detection sensors, a fork lift-mounted GPS module, an edge analytics unit, and an information management server. Each of the floor mounted identification tags is configured to store a unique location identifier. The pallet detection sensors are configured to detect presence or absence of the asset on the fork lift. The fork lift-mounted GPS module is configured to generate location coordinates of the fork lift. The edge analytics unit is mounted on the fork-lift. The edge analytics unit is configured to direct a fork-lift mounted RFID reader and antenna to read the asset mounted identification tag and extract the unique asset identifier, direct the fork-lift mounted RFID reader and antenna to read the floor mounted identification tags within its range, and extract the associated location identifier, and receive location coordinates of the fork lift from the GPS module. The information management server is communicatively coupled to the fork lift mounted edge analytics unit to receive the extracted asset identifier, the extracted location identifier, and the location coordinates. The information management server comprises a database and a location tracking module. The database is configured to store a list of asset identifiers, and a pre-determined list of location identifiers and landmarks in the pre-defined area associated with the location identifiers. The location tracking module is configured to cooperate with the repository to identify the asset based on the received asset identifier and determine location of the asset within the pre-defined area in terms of distance from a landmark based on the received location identifier and the location coordinates.
The present disclosure also envisages a method for managing assets used in molding machines and a method for tracking movement of assets within a pre-defined area, such as a plant.
Further, in accordance with yet another aspect of the invention, an assembly for mounting an identification tag on an asset is envisaged. The assembly comprises a metal plate welded to the asset. The thickness of the metal plate is 6mm. A plastic block is secured to the metal plate by means of a first set of fasteners. The thermal conductivity of the plastic block is less than 0.26 Watts per Meter-Kelvin. A second set of fasteners is used for securing the identification tag on to the plastic block. The assembly as disclosed herein helps in maintaining a pre-determined clearance between the surface of the asset and the identification tag for facilitating in situ detection of the asset at operating temperatures in the range of 180 – 200 degree Celsius.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
Systems and methods for managing and tracking assets of the present disclosure will now be described with the help of the accompanying drawing, in which:
Figure 1 illustrates a block diagram of a system for managing assets;
Figure 2a and Figure 2b illustrate a flow diagram depicting steps involved in a method for managing assets;
Figure 3 illustrates a block diagram of a system for tracking movement of assets;
Figures 4a, 4b, and 4c illustrate schematic front and side views of a modified fork lift used for tracking movement of asset within a pre-defined space;
Figures 5a, 5b, and 5c illustrate schematic front and side views of an asset mounted with an identification tag; and
Figures 6a and 6b illustrate a flow diagram of a method for tracking movement of assets.
LIST OF REFERENCE NUMERALS
100 Asset management system
50 An assembly for mounting an identification tag
102, 102’, 102’’ Asset
104, 104’ Local memory of an identification tag
106 Machine
108, 108’, 108’’ Identification tag
110 LED unit
112 Terminal
114 Operator identification tag
116 Machine-mounted Edge analytics unit
116a Repository
116b Validation module
116c Analytical engine
118, 118’ Information management server
120 Asset management unit
122 Alert generation unit
124, 124’ Database
128 Top temperature sensor
130 Bottom temperature sensor
132 Pressure sensor
134 Shot counter
136 Curing time counter
138 Scanning unit
300 Asset location tracking system
302 Instrumented Fork Lift
304 Enclosure
306 Fork lift mounted Edge Analytics unit
308 UHF RFID reader Fork Lift
310 GPS Module
312 GPS Antenna
314 Communication Module
316 Location tracking module
318 Wide beam circularly polarized UHF RFID antenna
320 Pallet detection sensor-1
322 Pallet detection sensor-2
324 Factory Floor
326, 328 UHF RFID location tag embedded in factory floor
330 Local memory of an edge analytics unit
400 L shaped fabrication
402 Fix distance
404 C Metal Block
406 Fork lift base plate
500 Metal plate
502 Thickness of metal plate
504, 510-526 Nuts
506 Plastic block
508 Thickness of plastic block
528 Fixed isolation distance
DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details, are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a,” "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms "comprises," "comprising," “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, elements, modules, units and/or components, but do not forbid the presence or addition of one or more other features, elements, components, and/or groups thereof. The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
When an element is referred to as being "mounted on," “engaged to,” "connected to," or "coupled to" another element, it may be directly on, engaged, connected or coupled to the other element. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed elements.
The terms first, second, third, etc., should not be construed to limit the scope of the present disclosure as the aforementioned terms may be only used to distinguish one element, component, region, layer or section from another component, region, layer or section. Terms such as first, second, third etc., when used herein do not imply a specific sequence or order unless clearly suggested by the present disclosure.
Terms such as “inner,” “outer,” "beneath," "below," "lower," "above," "upper," and the like, may be used in the present disclosure to describe relationships between different elements as depicted from the figures.
The manufacturing and fabrication industries involve use of Injection/ compression molding machines which require critical monitoring and control of process parameters such as curing time, clamping pressure, top and bottom plate temperature, bumping cycles and bumping pressure throughout the production process. Most of the existing machine and asset management systems do not facilitate online monitoring of various process parameters and remote control of machines. Further, the prevailing systems also do not facilitate accurate location tracking of assets and other tools within a production plant. To avoid this, systems and methods for managing and tracking assets, of the present disclosure are now being described with reference to Figure 1 through Figure 6b.
In accordance with one aspect of the present disclosure, a system 100 for managing assets 102 used in molding machines 106 is disclosed. Each asset 102 is associated with a unique asset identifier and each molding machine 106 is associated with a unique machine identifier. Referring to Figure 1, the system 100 comprises an asset-mounted identification tag 108, an information management server 118, and a machine-mounted edge analytics unit 116. The asset-mounted identification tag comprises a local memory 104 configured to store the associated unique asset identifier and a plurality of reference values of molding process parameters. The molding process parameters include, but are not limited to, mold temperature, injection pressure, clamping pressure, bumping pressure, number of bumps, bumping stay, bumping gap, curing time, and total number of shots produced at any specific point of time.
The information management server 118 comprises a database 124 configured to store a list of valid pairs of asset and machine identifiers and ideal values of process parameters associated with each of the valid pairs, and pre-determined identification information associated with operators authorized to operate the machines 106. The machine-mounted edge analytics unit 116 is communicatively coupled to the information management server 118. The machine-mounted edge analytics unit 116 comprises a repository 116a, a validation module 116b, and an analytical engine 116c. The repository 116a is configured to store the associated unique machine identifier. The validation module 116b is configured to authorize an operator to operate the machine 106 based on a received identification information and the pre-determined identification information, and is further configured to validate an asset 102 for use in the machine 106 based on the unique asset identifier and the valid pairs of identifiers. The analytical engine 116c is configured to:
• obtain reference values of process parameters from at least one of the information management server 118 and the identification tag 108 based on said asset identifier and machine identifier pair;
• obtain actual values of process parameters from a plurality of sensors (128-136) located on the machine 106;
• determine usage schedules, idle time, and productivity of the asset 102, detect abnormal operating conditions and generate alerts based on the obtained actual and reference values; and
• transmit the obtained actual values to the information management server 118, for facilitating remote monitoring and management of the asset 102.
The sensors (128-136) include top mold plate temperature sensor 128, bottom mold plate temperature sensor 130, pressure sensor 132, shot counter 134, and curing time sensor 136.
In an embodiment, the machine-mounted edge analytics unit 116 is configured to display the alerts and the actual values of process parameters on a terminal 112 and give indication of detected abnormal conditions using a plurality of indicators 110.
In an embodiment, the information management server 118 includes an asset management unit 120 and an alert generation unit 122. The asset management unit 120 is configured to receive the actual values of process parameters and determine usage and productivity of the asset 102 based on the received actual values. The alert generation unit 122 is configured to detect abnormal operating conditions by comparing the received actual values with the reference values, and is further configured to generate alerts upon detection of abnormal conditions.
Advantageously, the information management server 118 facilitates a user to remotely turn OFF the machine 106 upon detection of abnormal conditions.
A method for managing assets 102 used in molding machines 106 is now being disclosed with reference to Figures 2a and 2b. Each asset 102 is associated with a unique asset identifier and each molding machine 106 is associated with a unique machine identifier. The method 200 comprises the following steps:
At Step 202, storing, in a local memory 104 of an asset-mounted identification tag 108, the associated unique asset identifier and a plurality of reference values of molding process parameters;
At Step 204, storing, in a database 124 located on an information management server 118 a list of valid pairs of asset and machine identifiers and ideal values of process parameters associated with each of the valid pairs, and pre-determined identification information associated with operators authorized to operate the machines 106;
At Step 206, communicatively coupling, a machine-mounted edge analytics unit 116 with the information management server 118;
At Step 208, storing, in a repository 116a of the machine-mounted edge analytics unit 116, the associated unique machine identifier;
At Step 210, validating, by a validation module 116b of the machine-mounted edge analytics unit 116, an asset 102 for use in the machine 106 based on the unique asset identifier and the valid pairs of identifiers;
At Step 212, authorizing, by the validation module 116b, an operator to operate the machine 106 based on a received identification information and the pre-determined identification information;
At Step 214, obtaining, by an analytical engine 116c of the machine-mounted edge analytics unit 116, reference values of process parameters from at least one of the information management server 118 and the identification tag 108 based on the asset identifier and machine identifier pair;
At Step 216, obtaining, by the analytical engine 116c, actual values of process parameters from a plurality of sensors (128-136) located on the machine 106;
At Step 218, determining, by the analytical engine 116c, usage schedules, idle time, and productivity of the asset 102, and abnormal operating conditions based on the obtained actual and reference values;
At Step 220, generating, by the analytical engine 116c, alerts upon detection of abnormal operating conditions; and
At Step 222, transmitting, by the analytical engine 116c, the obtained actual values to the information management server 118, for facilitating remote monitoring and management of the asset 102.
In an embodiment, the step 212 of authorizing, by the validation module 116b, an operator to operate the machine 106 based on a received identification information and the pre-determined identification information includes reading, using a scanning unit 138, identification information of the operator from an operator-identification tag 114 wore by the operator; and comparing, by a first comparator, the received identification information with the pre-determined identification information for authorizing the operator to operate the machine 106. The identification information, in this case, includes a unique code assigned to the operator. The operator-identification tag may include a radio frequency identification tag (RFID tag), a near field communication tag (NFC tag), and the like. Accordingly, the scanning unit 138 may include an RFID reader and antenna or an NFC reader and antenna.
In another embodiment, the step 212 of authorizing, by the validation module 116b, an operator to operate the machine 106 based on a received identification information and the pre-determined identification information include receiving, using a biometric scanning unit, biometric data of the operator; and comparing, by a second comparator, the received biometric data with the pre-determined identification information for authorizing the operator to operate the machine 106. Accordingly, the identification information includes a pre-stored biometric data of the authorized operators.
In accordance with another aspect of the present disclosure, a system 300 for tracking movement of assets 102’ within a pre-defined area is disclosed. Typically, the assets 102’ are carried by fork lifts 302. Each asset 102’ is provided with an identification tag 108’ which stores a unique asset identifier in its local memory 104’. Referring to Figure 3, the system 300 comprises a plurality of floor-mounted identification tags (326, 328), a pair of pallet detection sensors (320, 322), a fork lift-mounted GPS module 310, an edge analytics unit 306 mounted on the fork lift 302, and an information management server 118’. Each of the floor-mounted identification tags (326, 328) is configured to store a unique location identifier. The pallet detection sensors (320, 322) is configured to detect presence or absence of the asset 102’ on the fork lift 302. In an embodiment, the pallet detection sensors (320, 322) are inductive proximity sensors. The pallet detection sensors (320, 322) are mounted on the fork lift base plate 406 in such a way that they can detect movement of asset 102’ in or out of the fork lift base plate 406. When the asset 102’ is moved on the fork lift base plate 406, one pallet sensor 320 is triggered first followed by the second pallet sensor 322. When the asset 102’ is moved out of the fork lift base plate 406, the second pallet sensor 322 is triggered first followed by the first sensor 320. This triggering pattern of sensors (320, 322) allows the fork lift mounted edge analytics unit 306 to determine presence or absence of the asset 102’ on the base plate 406.
Alternatively, the pallet detection sensors (320, 322) are infrared sensors or load sensors or ultrasonic sensors.
The fork lift-mounted GPS module 310 is configured to generate location coordinates of the fork lift 302. Upon detection of presence of the asset 102 on the fork lift 302, the fork lift mounted edge analytics unit 306 is configured to:
• direct a fork-lift mounted RFID reader and antenna (308, 318) to read the asset mounted identification tag 108’ and extract the unique asset identifier;
• direct the fork-lift mounted RFID reader and antenna (308, 318) to read the floor mounted identification tags (326, 328) within its range, and extract the associated location identifier; and
• receive location coordinates of the fork lift 302 from the GPS module 310.
The information management server 118’ is coupled to the fork lift mounted edge analytics unit 306 via a communication module 314. The communication module 314 may be selected from the group consisting of, but not limited to, a Wi-Fi module, a GPRS module, a CDMA module, a WCDMA module, a GSM module, and the like. The information management server 118’ receives the extracted asset identifier, the extracted location identifier, and the location coordinates from the fork lift mounted edge analytics unit 306. The information management server 118’ comprises a database 124’ and a location tracking module 316. The database 124’ is configured to store a list of asset identifiers; and a pre-determined list of location identifiers and landmarks in the pre-defined area associated with the location identifiers. The location tracking module 316 is configured to cooperate with the database 124’ to identify the asset 102’ based on the received asset identifier and determine location of the asset 102’ within the pre-defined area in terms of distance from a landmark based on the received location identifier and the location coordinates.
The fork lift 302 is modified to incorporate the RFID reader and antenna (308, 318), the pallet detection sensors (320, 322), the asset 102’, the edge analytics unit 306, and the GPS module 310. The modified fork lift 302 is as shown in Figure 4. The pallet detection sensors (320, 322) are mounted on a base plate 406 of the fork lift 302. An L-shaped metallic member 400 is mounted on the base plate 406 of the fork lift 302 with the help of a C-shaped metal block 404. The RFID antenna 318 is mounted on an operative lower surface of the L-shaped metallic member 400 in such a way that it maintains a pre-defined or a fixed distance from the fork lift base plate 406. An enclosure 304 is mounted over the L-shaped member 400. The enclosure 304 houses the edge analytics unit 306, the RFID reader 308, the GPS module with antenna (310, 312) and the communication module 314.
Referring to Figures 6a and 6b, a method 600 for tracking movement of assets 102’ within a pre-defined area is now described. The pre-defined area may be a factory area or specifically a production, manufacturing or fabrication plant space. The area can be provided with a plurality of floor mounted identification tags (326, 328) arranged at regular distances. Each floor-mounted identification tag (326, 328) can be configured to store a unique location identifier. The assets 102’ are moved from one location to another by a fork lift 302. Each asset 102’ is provided with an identification tag 108’ which stores a unique asset identifier in its local memory 104’. The method 600 comprises the following steps:
At Step 602, detecting, by a pair of pallet detection sensors (320, 322) disposed on said fork lift 302, presence or absence of the asset 102’ thereon;
Upon detecting presence of the asset 102’ on the fork lift 302,
At Step 604, directing, by an edge analytics unit 306 mounted on the fork-lift 302, a fork-lift mounted RFID reader and antenna (308, 318) to read the asset mounted identification tag 108’ and extract said unique asset identifier;
At Step 606, directing, by the edge analytics unit 306, the fork-lift mounted RFID reader and antenna (308, 318) to read the floor mounted identification tags (326, 328) within its range and extract the associated location identifier;
At Step 608, receiving, by the edge analytics unit 306, location coordinates of the fork lift 302 from a GPS module 312 mounted on the fork lift 302;
At Step 610, communicating, by the edge analytics unit 306, the extracted asset identifier, the extracted location identifier, and the location coordinates to an information management server 118’;
At Step 612, storing, in a database 124’ of the information management server 118’, a list of asset identifiers, and a pre-determined list of location identifiers and landmarks in the pre-defined area associated with the location identifiers; and
At Step 614, identifying 614, by a location tracking module 316 of the information management server 118’, the asset 102’ based on the received asset identifier; and
At Step 616, determining, by the location tracking module 316, location of the asset 102’ within the area in terms of distance from a landmark based on the received location identifier and location coordinates.
In accordance with yet another aspect of the invention, referring to Figure 5, an assembly 50 for mounting an identification tag 108’’ on an asset 102’’ is disclosed. The assembly 50 comprises a metal plate 500 which is welded to the asset 102’’. The thickness of the metal plate 500 may be 6mm. A plastic block 506 is secured to the metal plate 500 by means of a first set of fasteners (504, 510, 516, 518, 524, 526). The thermal conductivity of the plastic block 506 is less than 0.26 Watts per Meter-Kelvin. A second set of fasteners (512, 514, 520, 522) is used for securing the identification tag (108’’) on the plastic block 506. This arrangement/assembly of identification tag 108’’ on the asset 102’’ helps in maintaining a pre-determined or a fixed clearance between the surface of the asset 102’’ and the identification tag 108’’ for facilitating in situ detection of the asset 102’’ at operating temperatures in the range of 180 – 200 degree Celsius.
The present disclosure also envisages an integrated asset management and tracking system, which includes an information management server (118, 118’), an asset-mounted identification tag (108, 108’, 108’’), a machine-mounted edge analytics unit 116, a fork lift mounted edge analytics unit 306, a plurality of floor-mounted identification tags (326, 328), a pair of pallet detection sensors (320, 322) on fork lift 302, a fork lift-mounted GPS module 310, and a fork lift mounted RFID reader and antenna (308, 318). The information management server 118, in this case, will include an asset management unit 120, an alert generation unit 122, a database (124, 124’), and a location tracking module 316. The integrated system (100, 300) is capable of facilitating monitoring, management and tracking of assets (102, 102’, 102’’).
Advantageously, both the machine mounted edge analytics unit 116 and the fork lift mounted edge analytics unit 306 are implemented using one or more processors. The processor(s) described herein above may be general-purpose processor, Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), and/or the like. The processor may be configured to retrieve data from and/or write data to the memory. The memory may be, for example, a random-access memory (RAM), a memory buffer, a hard drive, a database, an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM), a read only memory (ROM), a flash memory, a hard disk, a floppy disk, cloud storage, and/or so forth
The foregoing description of the embodiments has been provided for purposes of illustration and not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but, are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of systems and methods for managing and tracking assets that:
• facilitate remote monitoring and control of machines;
• facilitate monitoring of power consumption of the machines;
• prevent unauthorized use of the machines;
• facilitate monitoring of operating parameters such as temperature of the asset, clamping and bumping pressure and total shot count; and
• accurately tracks the location of an asset within a plant; and
• tracks the maintenance status of the mold and sends a maintenance due notification to authorised operator; and
• detect faults in the machines and sends a fault notification to the authorized operator.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
Any discussion of documents, acts, materials, devices, articles or the like that has been included in this specification is solely for the purpose of providing a context for the disclosure. It is not to be taken as an admission that any or all of these matters form a part of the prior art base or were common general knowledge in the field relevant to the disclosure as it existed anywhere before the priority date of this application.
The numerical values mentioned for the various physical parameters, dimensions or quantities are only approximations and it is envisaged that the values higher/lower than the numerical values assigned to the parameters, dimensions or quantities fall within the scope of the disclosure, unless there is a statement in the specification specific to the contrary.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation.
,CLAIMS:WE CLAIM:
1. A system (100) for managing assets (102) used in molding machines (106), each asset (102) associated with a unique asset identifier and each molding machine (106) associated with a unique machine identifier, said system (100) comprising:
• an asset-mounted identification tag (108) comprising a local memory (104) configured to store said associated unique asset identifier and a plurality of reference values of molding process parameters;
• an information management server (118) comprising a database (124) configured to store:
i. a list of valid pairs of asset and machine identifiers and ideal values of process parameters associated with each of said valid pairs; and
ii. pre-determined identification information associated with operators authorized to operate said machines (106), and
• a machine-mounted edge analytics unit (116) communicatively coupled to said information management server (118), said machine-mounted edge analytics unit (116) comprising:
i. a repository (116a) configured to store said associated unique machine identifier;
ii. a validation module (116b) configured to authorize an operator to operate said machine (106) based on a received identification information and said pre-determined identification information, and further configured to validate an asset (102) for use in said machine (106) based on said unique asset identifier and said valid pairs of identifiers; and
iii. an analytical engine (116c) configured to:
• obtain reference values of process parameters from at least one of said information management server (118) and said identification tag (108) based on said asset identifier and machine identifier pair;
• obtain actual values of process parameters from a plurality of sensors (128-136) located on said machine (106);
• determine usage schedules, idle time, and productivity of said asset (102), detect abnormal operating conditions and generate alerts based on said obtained actual and reference values; and
• transmit said obtained actual values to said information management server (118), for facilitating remote monitoring and management of said asset (102).
2. The system (100) as claimed in claim 1, wherein the molding process parameters include mold temperature, injection pressure, clamping pressure, bumping pressure, number of bumps, bumping stay, bumping gap, curing time, and total number of shots produced at any specific point of time.
3. The system (100) as claimed in claim 1, wherein said sensors (128-136) include top mold plate temperature sensor (128), bottom mold plate temperature sensor (130), pressure sensor (132), shot counter (134), and curing time sensor (136).
4. The system (100) as claimed in claim 1, wherein said information management server (118) includes an asset management unit (120) configured to receive said actual values of process parameters and determine usage and productivity of said asset (102) based on said received actual values.
5. The system (100) as claimed in claim 1, wherein said information management server (118) includes an alert generation unit (122) configured to detect abnormal operating conditions by comparing said received actual values with said reference values, and further configured to generate alerts upon detection of abnormal conditions.
6. The system (100) as claimed in claim 1, wherein said machine-mounted edge analytics unit (116) is configured to display said alerts and said actual values of process parameters on a terminal (112) and give indication of detected abnormal conditions using a plurality of indicators (110).
7. The system (100) as claimed in claim 1, wherein said information management server (118) facilitates a user to remotely turn OFF said machine (106) upon detection of abnormal conditions.
8. A method (200) for managing assets (102) used in molding machines (106), each asset (102) associated with a unique asset identifier and each molding machine (106) associated with a unique machine identifier, said method (200) comprising the following steps:
• storing (202), in a local memory (104) of an asset-mounted identification tag (108), said associated unique asset identifier and a plurality of reference values of molding process parameters;
• storing (204), in a database (124) located on an information management server (118):
i. a list of valid pairs of asset and machine identifiers and ideal values of process parameters associated with each of said valid pairs; and
ii. pre-determined identification information associated with operators authorized to operate said machines (106),
• communicatively coupling (206), a machine-mounted edge analytics unit (116) with said information management server (118);
• storing (208), in a repository (116a) of said machine-mounted edge analytics unit (116), said associated unique machine identifier;
• validating (210), by a validation module (116b) of said machine-mounted edge analytics unit (116), an asset (102) for use in said machine (106) based on said unique asset identifier and said valid pairs of identifiers;
• authorizing (212), by said validation module (116b), an operator to operate said machine (106) based on a received identification information and said pre-determined identification information;
• obtaining (214), by an analytical engine (116c) of said machine-mounted edge analytics unit (116), reference values of process parameters from at least one of said information management server (118) and said identification tag (108) based on said asset identifier and machine identifier pair;
• obtaining (216), by said analytical engine (116c), actual values of process parameters from a plurality of sensors (128-136) located on said machine (106);
• determining (218), by said analytical engine (116c), usage schedules, idle time, and productivity of said asset (102), and abnormal operating conditions based on said obtained actual and reference values;
• generating (220), by said analytical engine (116c), alerts upon detection of abnormal operating conditions; and
• transmitting (222), by said analytical engine (116c), said obtained actual values to said information management server (118), for facilitating remote monitoring and management of said asset (102).
9. The method (200) as claimed in claim 8, wherein the step of authorizing (212), by said validation module (116b), an operator to operate said machine (106) based on a received identification information and said pre-determined identification information includes:
• reading, using a scanning unit (138), identification information of said operator from an operator-identification tag (114) wore by said operator; and
• comparing, by a first comparator, said received identification information with said pre-determined identification information for authorizing said operator to operate said machine (106).
10. The method (200) as claimed in claim 8, wherein the step of authorizing (212), by said validation module (116b), an operator to operate said machine (106) based on a received identification information and said pre-determined identification information includes:
• receiving, using a biometric scanning unit, biometric data of said operator; and
• comparing, by a second comparator, said received biometric data with said pre-determined identification information for authorizing said operator to operate said machine (106).
11. A system (300) for tracking movement of assets (102’) within a pre-defined area, each asset (102’) being carried by a fork lift (302) and provided with an identification tag (108’) which stores a unique asset identifier in its local memory (104’), said system (300) comprising:
• a plurality of floor-mounted identification tags (326, 328), each of said floor-mounted identification tags (326, 328) configured to store a unique location identifier;
• a pair of pallet detection sensors (320, 322) configured to detect presence or absence of said asset (102’) on said fork lift (302);
• a fork lift-mounted GPS module (310) configured to generate location coordinates of said fork lift (302);
• an edge analytics unit (306) mounted on said fork-lift (302), said edge analytics unit (306) configured, upon detection of presence of the asset (102’) on said fork loft (302), to:
i. direct a fork-lift mounted RFID reader and antenna (308, 318) to read said asset mounted identification tag (108’) and extract said unique asset identifier;
ii. direct said fork-lift mounted RFID reader and antenna (308, 318) to read said floor mounted identification tags (326, 328) within its range, and extract said associated location identifier; and
iii. receive location coordinates of said fork lift (302) from said GPS module (310),
• an information management server (118’) communicatively coupled to said fork lift mounted edge analytics unit (306) to receive said extracted asset identifier, said extracted location identifier, and said location coordinates, said information management server (118’) comprising:
i. a database (124’) configured to store:
o a list of asset identifiers; and
o a pre-determined list of location identifiers and landmarks in said pre-defined area associated with said location identifiers,
ii. a location tracking module (316) configured to cooperate with said database (124’) to identify said asset (102’) based on said received asset identifier and determine location of said asset (102’) within said pre-defined area in terms of distance from a landmark based on said received location identifier and said location coordinates.
12. The system (300) as claimed in claim 11, wherein said pallet detection sensors (320, 322) are mounted on a base plate (406) of said fork lift (302).
13. The system (300) as claimed in claim 12, wherein an L-shaped metallic member (400) is mounted on said base plate (406) of said fork lift (302) with the help of a C-shaped metal block (404).
14. The system (300) as claimed in claim 13, said RFID antenna (318) is mounted on an operative lower surface of said L-shaped member (400) in such a way that it maintains a pre-defined distance from said fork lift base plate (406).
15. The system (300) as claimed in claim 11, wherein said pallet detection sensors (320, 322) are selected from the group consisting of ultrasonic sensors, infrared sensors, and load sensors.
16. The system (300) as claimed in claim 11, which includes a communication module (314) mounted on said fork lift (302), wherein said communication module (314) is selected from the group consisting of GPRS module, Wi-Fi module, and GSM module.
17. A method (600) for tracking movement of assets (102’) within a pre-defined area, said area being provided with a plurality of floor mounted identification tags (326, 328), each floor-mounted identification tag (326, 328) configured to store a unique location identifier, each of assets (102’) being carried by a fork lift (302) and provided with an identification tag (108’) which stores a unique asset identifier in its local memory (104’), said method (600) comprising the following steps:
• detecting (602), by a pair of pallet detection sensors (320, 322) disposed on said fork lift (302), presence or absence of said asset (102’) thereon;
• upon detecting presence of said asset (102’) on said fork lift (302),
i. directing (604), by an edge analytics unit (306) mounted on said fork-lift (302), a fork-lift mounted RFID reader and antenna (308, 318) to read said asset mounted identification tag (108’) and extract said unique asset identifier;
ii. directing (606), by said edge analytics unit (306), said fork-lift mounted RFID reader and antenna (308, 318) to read said floor mounted identification tags within its range and extract said associated location identifier;
iii. receiving (608), by said edge analytics unit (306), location coordinates of said fork lift (302) from a GPS module (312) mounted on said fork lift (302);
iv. communicating (610), by said edge analytics unit (306), said extracted asset identifier, said extracted location identifier, and said location coordinates to an information management server (118’);
v. storing (612), in a database (124’) of said information management server (118’), a list of asset identifiers, and a pre-determined list of location identifiers and landmarks in said pre-defined area associated with said location identifiers; and
vi. identifying (614), by a location tracking module (316) of said information management server (118’), said asset (102’) based on said received asset identifier; and
vii. determining (616), by said location tracking module (316), location of said asset (102’) within said area in terms of distance from a landmark based on said received location identifier and location coordinates.
18. An assembly (50) for mounting an identification tag (108’’) on an asset (102’’), said assembly (50) comprising:
• a metal plate (500) welded to said asset (102’’);
• a plastic block (506) secured to said metal plate (500) by means of a first set of fasteners (504, 510, 516, 518, 524, 526); and
• a second set of fasteners (512, 514, 520, 522) for securing said identification tag (108’’) on said plastic block (506).
19. The assembly (50) as claimed in claim 18, wherein the thickness of said metal plate (500) is 6mm.
20. The assembly (50) as claimed in claim 18, wherein the thermal conductivity of said plastic block (506) is less than 0.26 Watts per Meter-Kelvin.
21. The assembly (50) as claimed in claim 18, which maintains a pre-determined clearance between the surface of said asset (102’’) and said identification tag (108’’) for facilitating in situ detection of said asset (102’’) at operating temperatures in the range of 180 – 200 degree Celsius.