US20070294093A1 - Preventative maintenance system - Google Patents
Preventative maintenance system Download PDFInfo
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- US20070294093A1 US20070294093A1 US11/454,713 US45471306A US2007294093A1 US 20070294093 A1 US20070294093 A1 US 20070294093A1 US 45471306 A US45471306 A US 45471306A US 2007294093 A1 US2007294093 A1 US 2007294093A1
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- preventative maintenance
- real time
- logic
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- communicates
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
- B22D17/00—Pressure die casting or injection die casting, i.e. casting in which the metal is forced into a mould under high pressure
- B22D17/20—Accessories: Details
- B22D17/32—Controlling equipment
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
- B22D46/00—Controlling, supervising, not restricted to casting covered by a single main group, e.g. for safety reasons
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C45/00—Injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould; Apparatus therefor
- B29C45/17—Component parts, details or accessories; Auxiliary operations
- B29C45/76—Measuring, controlling or regulating
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C45/00—Injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould; Apparatus therefor
- B29C45/17—Component parts, details or accessories; Auxiliary operations
- B29C45/76—Measuring, controlling or regulating
- B29C45/768—Detecting defective moulding conditions
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
- G06Q10/1093—Calendar-based scheduling for persons or groups
- G06Q10/1097—Task assignment
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76003—Measured parameter
- B29C2945/76163—Errors, malfunctioning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76929—Controlling method
- B29C2945/76939—Using stored or historical data sets
- B29C2945/76943—Using stored or historical data sets compare with thresholds
Definitions
- the present invention generally relates to maintenance of molding systems, and more specifically the present invention relates to real time preventative maintenance and repair of injection molding systems, components, and parts.
- injection molding system includes both plastic and metal injection molding systems.
- U.S. Pat. No. 6,738,748 to Wetzer and assigned to Accenture LLP relates to performing predictive maintenance on equipment.
- Wetzer discloses a data processing system and method to predict maintenance based upon one or more estimated parameters such as longevity, probability of failure (mean time between failure), and financial estimates.
- Sasaki discloses a data processing system and method for monitoring injection molding equipment where operational data is compared to theoretical estimated expected life data. For example, the hours of use may be compared to an expected life limit or, the maximum frequency of use may be compared to an expected life limit.
- U.S. Pat. No. 6,175,934 to Hershey et el assigned to the General Electric Company relates to a satellite based remote monitoring system.
- the system places remote equipment into a test mode to perform remote predictive assessment.
- a disadvantage of this approach is the requirement to take a piece of equipment off-line to conduct the test.
- U.S. Pat. No. 6,643,801 to Jammu et el and assigned to the General Electric Company relates to a method for analyzing fault log data and repair data to estimate time before a machine disabling failure occurs. Fault data and repair data are used to estimate the time before a failure occurs. Service information, performance information, and compartment failure information are analyzed to determine a performance deterioration rate to simulate a distribution of future service events. The system is based upon operational levels of vibration in contrast to ideal or acceptable levels of vibration.
- U.S. Pat. No. 6,799,154 to Aragones et el assigned to the General Electric Company relates to a system for predicting the timing of future service events of a product.
- a component or part may fail in advance of the estimated values and there is no warning or indication that a component or part may fail in advance of the estimate values.
- a component or part may be replaced when it still has a good useful life. Any of these situations cause unnecessary expense and maintenance.
- the estimated useful life of an oil filter in the hydraulic circuit of a power pack might be 10,000 hours of operation.
- the prior art systems simply record the number of hours of usage, and then schedule a replacement of the oil filter when the hours of usage approach or reach the limit of 10,000 hours.
- the oil filer could fail in advance of reaching the limit, potentially causing damage to other components in the hydraulic system and power pack.
- the prior art systems do not take into account different environmental aspects of operating equipment at different customer locations and different global locations around the world. For example, humidity, air temperature, cooling water quality, and altitude may impact the performance and reliability of a molding system. For example, some customers run equipment harder than other customers.
- the prior art systems do not take into account the aspect of supporting and maintaining such equipment on a global scale.
- the prior art approaches relate to predictive maintenance. Predictive maintenance attempts to maximize the use of a component or part based upon statistical predetermined information in advance of a theoretical point of failure. However, predictive maintenance does not take into account events or indicators that warn of a premature failure in advance of the theoretical point of failure.
- a method for real time preventative maintenance of a molding system Indicating an out of tolerance condition based upon a real time operational status, and creating a notice for preventative maintenance.
- an apparatus for real time preventative maintenance of a molding system including preventative maintenance logic, business system logic, service scheduling logic, and parts management logic.
- the preventative maintenance logic capable of receiving an indication for preventative maintenance based upon a real time operational status of said molding system under at least one of the following conditions:
- a technical effect, amongst other technical effects, of the present invention is real time sensing of operational data for assessment by the system to predict or indicate a potential failure in advance of actual failure. Indicating potential failures in advance of actual failures provides better up-time to customers.
- Other technical effects may also include any combination or permutation of proactive monitoring, diagnostics, and remote control of molding systems to assist with customer productivity, reduce unscheduled maintenance, and align with scheduled maintenance. For the manufacturer or customer service provider, better spare parts management and better access to the customer.
- Preventative maintenance of the present invention is different from the prior art approaches of predictive maintenance. Preventative maintenance monitors sensors in real time to identify indicators of early or premature failure of components or parts. Preventative maintenance also monitors other conditions that would lead to premature failure of components or parts. Upon identification of these indicators, preventative maintenance will determine the best fit to a manufacturing cycle for maintenance of the molding system.
- FIG. 1 is a schematic representation of an injection molding system
- FIG. 2 is a schematic representation of an injection unit with sensors
- FIG. 3 is a schematic representation of a clamp with sensors
- FIG. 4 is a schematic representation of a mold with sensors
- FIG. 5 is a schematic representation of a hot runner with sensors
- FIG. 6 is a schematic representation of a real time preventative maintenance system illustrating the pre-indicator portion of the system and
- FIG. 7 is also a schematic representation of a real time preventative maintenance system illustrating the post-indicator portion of the system.
- the molding system may be a metal molding system or a plastics molding system.
- the molding system includes an injection unit 108 for creating a shot of melt.
- a drive 118 provides operational power for rotating and translating a screw (not shown).
- the drive 118 may be electric, hydraulic, or a combination of hydraulic and electric.
- a barrel 109 of the injection unit 108 includes heaters (not shown) to assist melting the raw material.
- the injection unit 108 could comprise a well known shooting pot style of injection unit.
- a clamp is illustrated as 102 .
- the clamp includes a pair of platens 103 , 105 to receive a mold 104 .
- a drive 120 provides operational power to translate a moving platen 103 and to provide clamp tonnage.
- the drive 120 may be electric, hydraulic, or a combination of hydraulic and electric.
- the mold 104 includes a hot half 104 b and a cold half 104 a and provides at least one core and cavity (not shown) to form a molded part.
- the mold 104 includes a hot runner 106 for distributing melt within the mold 104 .
- the hot runner 106 includes electrical heaters (not shown) for keeping a melt at an elevated temperature.
- a power pack 110 is provided for the molding system 100 .
- the power pack 110 includes a control system 114 to control the molding system 100 , a hydraulic portion 112 to provide hydraulic power (if hydraulics are required).
- the control system is an Intel® based computer with a Windows® based operating system such at the Husky® Polaris® Control System.
- a hydraulic portion 112 is not required.
- the power pack 110 also includes electrical components (not shown) and circuitry 116 .
- the molding system 100 includes a connection to a supply 122 .
- the supply 122 provides electrical power and chilled water to the molding system 100 .
- the chilled water may be applied to keep other devices cool, for example electric motors and electrical components (not shown).
- raw material 124 is feed into the injection unit 108 .
- the injection unit creates a shot of melt.
- the clamp 102 closes the mold 104 and then applies tonnage to the mold 104 .
- the injection unit 108 injects the shot of melt into the mold 104 .
- the formed part 126 is cooled, it is removed from the mold 104 and the process repeats.
- Molding systems 100 are designed to run 7 days a week 24 hours a day producing molded parts, for example PET performs, or automotive parts.
- a PET perform system may have the capability to produce 192 preforms every 15 seconds and an unscheduled down-time can have a significant financial impact to business.
- known periodic maintenance can be planned for during an active production run and preventative maintenance can take advantage of known or scheduled down-times.
- the drive 118 may include sensors 202 .
- typical sensors 202 include those for temperature, voltage, and current.
- typical sensors 202 include those for temperature and hydraulic pressure.
- the injection unit 108 also includes sensors 204 along a length of the barrel 109 for sensing temperature.
- the sensors 204 are also capable of measuring voltage, and current supplied to the electrical barrel heaters.
- the injection unit 108 also includes pressure sensors 206 located upon a length of the barrel 109 to indicate pressure in the barrel 109 , and pressure differentials before and after the check valve (not shown) located on the screw (not shown) and within the barrel 109 of the injection unit 108 . Sensors 210 could also measure resin viscosity.
- Sensors 200 determine the dryness of the raw material that is provided into a feed throat (not shown) of the injection unit 108 .
- Sensors 212 could also measure the ambient air temperature and humidity (the operating environment around the molding system). Different raw materials require a different dryness in order to be processed and provide a good quality part.
- Sensors 208 monitor the temperature and flow rate of the supplied chilled water. Sensors 214 could also monitor the physical properties of chilled water. In addition, sensors 216 could monitor voltage and current of the supplied power.
- Sensors 200 , 208 , and 212 are intended to monitor external factors that could lead to damage of the molding system 100 , components, or molded parts (not shown). For example, dirty electricity, voltage/current spikes, poor water quality, poor quality hydraulic oil, air quality, pollution, and dust.
- the clamp 102 includes a drive 120 .
- the sensor 302 may monitor voltage, current, and temperature.
- the sensor 302 may monitor temperature and pressure.
- a hybrid drive would have a combination of sensors.
- the clamp 102 also includes various sensors 300 to monitor stress, strain, and positional alignment of the platens 103 , 105 .
- the mold 104 includes a cold half 104 a and a hot half 104 b .
- the hot runner 106 is mounted in a hot half 104 b .
- Sensors 400 monitor the temperature of the chilled water required to cool the part (not shown).
- Sensors 402 monitor the temperature of the hot half 104 b .
- Location of sensors 400 and 402 could be cavity by cavity, or regional within a single cavity (now shown). Additional sensors (not shown) may be applied to detect flash, or misalignment between the hot half 104 b and the cold half 104 a , or detect removal of the parts from the mold, or monitor post mold cooling.
- Sensors 500 monitor temperature of the melt and/or hot runner components (not shown) and sensors 502 monitor pressure of the melt in the hot runner system. Additional sensors 504 may be applied to determine the operation or position of a valve gate in a valve gated hot runner.
- Sensors 612 may include all or some of the sensors ( 200 , 202 , 204 , 206 , 208 , 210 , 212 , 214 , 216 , 300 , 302 , 400 , 402 , 500 , 502 , and 504 ) previously described.
- sensors 202 could be capable to monitor temperature and pressure. If the injection unit 108 drive 118 is electric, then sensors 202 could capable to monitor temperature, voltage, and current.
- a visioning system (not shown) to detect problems with the molded parts 126 that in turn relates to problems with the molding system 100 or components of the molding system 100 .
- the visioning system could detect the presence of a stringy gate which in turn relates to a potential temperature issue at a gate (not shown).
- sensors 612 are readily available. For example, a thermocouple will sense temperature. A transducer will sense pressure. A voltmeter will sense voltage and an ammeter will sense current. In addition, persons skilled in the art will also appreciate a combination of sensors 612 could be arranged to monitor and provide unique parameters.
- the real time preventive maintenance system 600 includes a comparator module 602 .
- the comparator 602 has access to the real time threshold status 616 data and the real time operational parameters 606 as measured by the sensors 612 .
- the real time threshold status 616 data may include one or more of:
- the real time operational parameters 606 may include real time measurements of voltage, current, pressure, temperature, humidity, acidity, alkinity, stress, strain, viscosity, fluid cleanliness, alignment, and mold part quality, amongst others, as measured in real time from the sensors 612 .
- Both the real time threshold status 616 data and the real time operational parameters 606 are correlated for each aspect of the molding system 100 . For example, they are correlated for the injection unit 108 , clamp 102 , mold 104 , hot runner 106 , raw materials 124 , and the supply 122 . The data and parameters could also be correlated for additional devices and options such as post mold cooling.
- the comparator 602 compares the real time operational parameters 606 with the real time threshold status 616 data to determine if a component is running within the normal range, below a minimum value, or above a maximum value, or a rate of change or frequency towards a limit.
- the comparator 602 determines the component is running below a minimum value, for the case wherein this is not allowed, the comparator 602 will trigger the indicator module 604 to indicate preventative maintenance. For the case where this is allowed for a period of time, or for a predefined number of occurrences without damage, then the comparator 602 checks the history 608 module to determine the frequency information and data to see if the maximum frequency has been exceeded and trigger the indicator module 604 to indicate preventative maintenance.
- the comparator 602 determines the component is running above a maximum value, for the case wherein this is not allowed, the comparator 602 will trigger the indicator module 604 to indicate preventative maintenance. For the case where this is allowed for a period of time, or for a predefined number of occurrences, then the comparator 602 checks the history 608 module to determine the frequency information to see if the maximum frequency has been exceeded and trigger the indicator module 604 to indicate preventative maintenance.
- the indicator 604 module may send preventative maintenance information to the human machine interface screen, to a central customer computer system, or to a remote manufacturer computer system or customer service computer system.
- the computer system communicates through a network (wire or wireless), the internet, or an intranet.
- Preventative maintenance information includes, but is not limited to, customer identification, molding system identification, component identification, dates, and real time operational parameters.
- the history module 608 receives real time operational parameters 606 .
- the history module 608 builds and maintains a frequency 624 database. For example, number of times, or length of time a component may be operating below the minimum value or above the maximum value.
- the history module 608 also contains the limit information for the system, sub-systems, components and parts.
- the history 608 module also builds and maintains a trends 610 database.
- the trends 610 database contains trend data with respect to the operation of the molding system 100 .
- the updater 614 module maintains the real time threshold status 616 database and may modify the real time threshold status 616 database.
- the manufacturer of a component, part, system, or sub-system provides the initial and present tense operational data such as the minimum real time threshold operational limits, the maximum real time threshold operational limits, and the normal operational range.
- operational data such as the minimum real time threshold operational limits, the maximum real time threshold operational limits, and the normal operational range.
- an amount of time, or an accumulated amount of time, or a frequency of occurrence may be provided to understand when a component has been damaged, but will continue to work for some limited amount of time without immediate failure.
- the system indicates trends towards a failure as well as failure when it occurs. For example, a drive may be operated at maximum horse power rating for 5 minutes and 75% of maximum power continuously without damage. But, if the drive is operated a maximum horse power for 8 minutes, it will be damaged but not necessarily to the point of immediate failure. Preventative maintenance is therefore required before failure of the drive.
- the future tense of operational data may change. For example, if a particular customer is known to operate the molding system 100 aggressively, the history of customer data 620 may modify the operational data to different limits for preventative maintenance.
- the updater 614 is adaptive and may modify the operational data based upon the customer data 620 .
- the future operational data may also change based upon a geographic location. For example, if a molding system is located in a high humidity or high altitude environment, the geographic location data 622 may modify the operational data to different limits for preventative maintenance. The updater 614 may modify the operational data based upon the geographic data 622 .
- the updater module 614 also receives data from the frequency module 624 and the trends module 610 and is adaptive to the environment to modify the data based upon real time use of the molding system 100 . For example, if an upper temperature limit was thought to be 400 degrees but later determined through use of the molding system 100 to be 350 degrees, then the real time threshold status 616 data would be updated accordingly.
- the updater module 614 takes customer data and geographic data to build a repository of system and component intelligence. This intelligence includes the same model of molding systems operated at different customer locations by different customers in different geographic locations.
- the update module 614 may be located or integrated with component parts as well as the complete molding system.
- a first updater module 614 may be located with a mold.
- a second updater module 614 could be located with a hot runner.
- a third updater module 614 could be located with a power pack 110 . Then, the real time threshold status 616 information stays with the associated system, sub-system, or component part. If a mold 104 is removed from production, it can be re-introduced back into production with the last known operational data. In addition, if a hot runner 106 has to be refurbished, it contains the last known operational data.
- the comparator 602 , real time operational parameter 606 data, sensors 612 , and real time threshold operational limit 616 data may be combined to form a preventative maintenance Indicator System.
- the indicator system includes a comparator 602 , at least one real time threshold operational limit 616 data, and sensors 612 .
- the sensors provide at least one real time operational parameter 606 data.
- the comparator 602 comparing the at least one real time operational parameter 606 data with the at least one real time threshold operational limit 616 data to indicate operational status.
- the comparator indicating an out of tolerance condition if the operational status is either below a minimum real time operational limit or above a maximum real time threshold operational limit.
- historical data of real time operational parameters 608 may be available to the comparator 602 .
- the indicator system includes a method for sampling at least one real time operational parameter 606 data from at least one sensor 612 of a molding system. Comparing the at least one real time operational parameter 606 data with at least one real time threshold operational limit 616 data to indicate operational status.
- the comparator determines if this is not allowed or if a maximum limit has been reached and indicates preventative maintenance. In addition, if the operational status is above a maximum real time threshold operational limit, the comparator further determines if this is not allowed, or if a maximum limit has been reached and indicates preventative maintenance.
- Threshold operational limit data may include at least one maximum limit and/or one minimum limit. These limits may be based upon units of time, frequency of occurrence, or other pre-defined molding system parameters.
- the real time operational parameter 606 data and the real time operational threshold limit 616 data may include: voltages, currents, pressures, temperatures, humidity, acidity, alkinity, stress values, strain values, alignment information, viscosity, or molded part quality, amongst others. Additionally, the real time threshold operational limit data may include at least one of a normal operational range value, a minimum limit value, or a maximum limit value, amongst others.
- the comparator 602 may indicate preventative maintenance for at least one of a molding system, a subsystem of the molding system, a component part of the molding system, auxiliary or supply systems to the molding system, injection unit, power pack, clamp, mold, hot or cold half of the mold, or the hot runner.
- the real time threshold limit 616 data may pertain to at least one of the following, a particular customer, a geographic location, multiple customers, or multiple geographic locations.
- the updater 614 , history 608 data, frequency 624 data, trends 610 data, manufacturer 618 data, customer 620 data, and geographic location 622 data may be combined to form a preventative maintenance update system. This system keeps the real time threshold status 616 data up to date and current.
- the apparatus for updating preventative maintenance data of a molding system includes an updater 614 , and a real time threshold status 616 data.
- the updater having access to categories of history 608 data and the updater providing periodic updates to the real time threshold status 616 data.
- the updater may determine which categories are applied to update the real time threshold status 616 data.
- Access to history 608 data may be remote access, local access, or global access.
- the updater may modify at least one data parameter of the normal operational range value, or a minimum limit value, or a maximum limit value.
- the method for updating preventative maintenance data of a molding system includes receiving real time operational parameter 616 data and storing as history 608 data. Sorting the history 608 data into categories. Sending real time periodic updates to real time threshold status 616 data.
- the apparatus for updating preventative maintenance data of a molding system may be located with one of the following to include: molding system, power pack, injection unit, clamp, mold, hot half, cold half, hot runner, control system, or a molding system component. There may be one apparatus for updating preventative maintenance data of a molding system or a plurality of apparatus for updating preventative maintenance data of a molding system distributed around the system as previously described.
- the categories of history 608 data may include at least one of frequency 624 data, trends 610 data, manufacturer 618 data, and plurality of manufacturer 618 data, customer data 620 , plurality of customer's 620 data, geographic location 622 data, and plurality of geographic location 622 data.
- the indicator 604 module may send preventative maintenance information to a customer system 702 or a manufacturer (or customer service provider) having a predictive maintenance 700 capability. This event may occur from a plurality of customers, a plurality of molding systems 100 , or a plurality of geographic locations.
- the customer 702 may in turn provide the preventative maintenance information to the manufacturer for analysis and resolution.
- a general practitioner 714 customer service representative may become involved to assess the problem and take corrective action. If a general practioner 714 customer service representatives cannot resolve the problem nor take corrective action, then a specialist 718 customer service representative may become involved to assess the problem, assess the symptoms, and perform a root cause analysis to take corrective action or provide recommendations or actions to adjust the molding system process parameters.
- both the general practitioner 714 and the specialist 718 have access to customer's molding systems 100 through a remote control and diagnostic system 716 such as the Husky® ServiceLinkTM technology.
- the ServiceLinkTM technology provides a connection from a remote computer through a network/internet connection into the Polaris® molding system 100 control system.
- a service scheduler 702 receives the preventative information from the preventative maintenance 700 module. This may occur automatically to schedule preventative maintenance or may occur as a result of a customer service representative.
- the service scheduler 702 attempts to align preventative service with known customer down time or service time. For example, fit preventative service into known gaps in production cycles, or within scheduled down times. Essentially, create a match between the service provider and the customer when the service provider has personnel and parts ready at the same time the customer is not in an active production run.
- Service events and planning include upgrades, a change part date, scheduled service, and production cycle scheduled down time.
- a parts system 708 also receives preventative maintenance information.
- the parts system 708 ensures an available supply of parts through inventory management 712 .
- an inventory location 710 module ensures parts are either stored in a central repository, or a distributed repository based upon the geographic or customer information provided with the preventative maintenance information.
- the inventory management 712 module may also interact with other vendors and supply chain management software to better predict a supply of spare parts based upon the frequency and trend data available in the preventative maintenance information.
- a business system 706 provides the necessary financial and business level support as a result of the customer service and spare parts activity with a customer.
- the preventative maintenance 700 logic, business system logic 706 , service scheduler 702 logic and parts system 708 logic may be grouped to form a preventative maintenance system for a molding system.
- the preventative maintenance 700 logic may communicate an indication for preventative maintenance to a general practioner 714 for resolution.
- the general practioner 714 in turn may transfer the indication for preventative maintenance to a specialist.
- the preventative maintenance 700 log may communicate an indication for preventative maintenance directly to a specialist 718 .
- Both the general practioner 714 and specialist 718 may have access to remote control 716 logic for inspecting, or resolving the need for preventative maintenance. Confirmation may be passed back to the preventative maintenance 700 logic.
- the preventative maintenance 700 logic may communicate with business system 706 logic for invoicing and billing.
- the preventative maintenance 700 logic may also communicate with service scheduler 702 logic to schedule service. Scheduling service may be based upon fit into a service provider's schedule, or fit to a customer schedule, or fit to a per-determined existing customer maintenance schedule, or fit to availability of service personnel, or fit to the availability of service parts.
- the preventative maintenance 700 logic may also communicate with parts management logic to manage parts inventory with either a central parts inventory or a distributed parts inventory.
- the method for real time preventative maintenance of a molding system includes indicating an out of tolerance condition based upon a real time operational status, and creating a notice for preventative maintenance.
- the notice of preventative maintenance may be communicated directly to either a customer system of a service provider system.
- the customer system in turn may communicate with the service provider system.
- the preventative maintenance system may send communications to either a general practioner or a specialist for resolution.
- Either of the general practioner or specialist may have remote access and control of the molding system for conducting a preventative maintenance inspection and they may communicate the need for preventative maintenance.
- the preventative maintenance system may communicate with a service scheduler to schedule maintenance.
- the scheduler may determine a fit to a service provider's schedule, or fit to a customer schedule, or a pre-determined existing maintenance schedule, or fit to availability of service personnel, or fit to availability of service parts.
- the preventative maintenance system may communicate with a parts system for inventory management to provide a central parts inventory or a distributed parts inventory.
- the preventative maintenance system may also communicate with a business system for invoicing and billing.
- the real time preventative maintenance system 600 is embodied in the control system 114 of a molding system 100 .
- it may be embodied as a stand alone system at a customer's factory.
- it may be embodied as a stand alone system at an equipment manufacturer's site providing customer service.
- it may be partially embodied in the control system 114 of a molding system 100 and interacting with other software systems distributed at a customer site or a manufacturer's site.
- the real time preventative maintenance system 600 may be implemented in hardware, firmware, software or a combination of hardware, firmware, and software.
- the preventative maintenance system 600 may be a single integrated system, or a distributed system, with one or many software/firmware modules, with one or many hardware components and one or many integrated or separate databases.
- the real time preventative maintenance system 600 is a data processing system that generates a preventative maintenance notice indicating an out of tolerance condition of a real time operational status of a molding system.
- the data processing system may further include a generating module for generating a preventative maintenance notice indicating an out of tolerance condition of a real time operational status of a molding system.
- an article of manufacture for directing a data processing system including a program-usable medium embodying one or more instructions executable by the data processing system.
- the one or more instructions include data processing system executable instructions for directing the data processing system to generate a preventative maintenance notice indicating an out of tolerance condition of a real time operational status of a molding system.
Abstract
Description
- The present invention generally relates to maintenance of molding systems, and more specifically the present invention relates to real time preventative maintenance and repair of injection molding systems, components, and parts. In the context of this invention, injection molding system includes both plastic and metal injection molding systems.
- U.S. Pat. No. 6,738,748 to Wetzer and assigned to Accenture LLP relates to performing predictive maintenance on equipment. Wetzer discloses a data processing system and method to predict maintenance based upon one or more estimated parameters such as longevity, probability of failure (mean time between failure), and financial estimates.
- United States Patent Application 2004/0148136 to Sasaki et el assigned to Toshiba Kikai Kabushiki Kaisha relates to a system for predictable maintenance of injection molding equipment. Sasaki discloses a data processing system and method for monitoring injection molding equipment where operational data is compared to theoretical estimated expected life data. For example, the hours of use may be compared to an expected life limit or, the maximum frequency of use may be compared to an expected life limit.
- U.S. Pat. No. 6,175,934 to Hershey et el assigned to the General Electric Company relates to a satellite based remote monitoring system. The system places remote equipment into a test mode to perform remote predictive assessment. A disadvantage of this approach is the requirement to take a piece of equipment off-line to conduct the test.
- U.S. Pat. No. 6,643,801 to Jammu et el and assigned to the General Electric Company relates to a method for analyzing fault log data and repair data to estimate time before a machine disabling failure occurs. Fault data and repair data are used to estimate the time before a failure occurs. Service information, performance information, and compartment failure information are analyzed to determine a performance deterioration rate to simulate a distribution of future service events. The system is based upon operational levels of vibration in contrast to ideal or acceptable levels of vibration.
- U.S. Pat. No. 6,192,325 to Piety et el and assigned to the CSI Technology Company and relates to a method and apparatus for establishing a predictive maintenance database.
- U.S. Pat. No. 6,799,154 to Aragones et el assigned to the General Electric Company relates to a system for predicting the timing of future service events of a product.
- However, problems remain with the known prior art approaches that apply estimated or theoretical values to predictive maintenance. A component or part may fail in advance of the estimated values and there is no warning or indication that a component or part may fail in advance of the estimate values. A component or part may be replaced when it still has a good useful life. Any of these situations cause unnecessary expense and maintenance.
- For example, the estimated useful life of an oil filter in the hydraulic circuit of a power pack might be 10,000 hours of operation. The prior art systems simply record the number of hours of usage, and then schedule a replacement of the oil filter when the hours of usage approach or reach the limit of 10,000 hours. However, if a seal fails or contaminants enter the oil system, the oil filer could fail in advance of reaching the limit, potentially causing damage to other components in the hydraulic system and power pack.
- In addition, the prior art systems do not take into account different environmental aspects of operating equipment at different customer locations and different global locations around the world. For example, humidity, air temperature, cooling water quality, and altitude may impact the performance and reliability of a molding system. For example, some customers run equipment harder than other customers. The prior art systems do not take into account the aspect of supporting and maintaining such equipment on a global scale.
- The prior art approaches relate to predictive maintenance. Predictive maintenance attempts to maximize the use of a component or part based upon statistical predetermined information in advance of a theoretical point of failure. However, predictive maintenance does not take into account events or indicators that warn of a premature failure in advance of the theoretical point of failure.
- According to a first aspect of the present invention, there is a method for real time preventative maintenance of a molding system. Indicating an out of tolerance condition based upon a real time operational status, and creating a notice for preventative maintenance.
- According to a second aspect of the present invention, there is an apparatus for real time preventative maintenance of a molding system including preventative maintenance logic, business system logic, service scheduling logic, and parts management logic. The preventative maintenance logic capable of receiving an indication for preventative maintenance based upon a real time operational status of said molding system under at least one of the following conditions:
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- (a) the operational status is below an absolute minimum real time threshold operation limit,
- (b) the operational status is below a minimum real time threshold operational limit and has reached the maximum accumulated duration for being below the real time threshold operational limit,
- (c) the operational status is above an absolute maximum real time threshold operational limit, or
- (d) the operational status is above a maximum real time threshold operational limit and has reached the maximum accumulated duration for being above the real time threshold operational limit.
- A technical effect, amongst other technical effects, of the present invention is real time sensing of operational data for assessment by the system to predict or indicate a potential failure in advance of actual failure. Indicating potential failures in advance of actual failures provides better up-time to customers. Other technical effects may also include any combination or permutation of proactive monitoring, diagnostics, and remote control of molding systems to assist with customer productivity, reduce unscheduled maintenance, and align with scheduled maintenance. For the manufacturer or customer service provider, better spare parts management and better access to the customer.
- Preventative maintenance of the present invention is different from the prior art approaches of predictive maintenance. Preventative maintenance monitors sensors in real time to identify indicators of early or premature failure of components or parts. Preventative maintenance also monitors other conditions that would lead to premature failure of components or parts. Upon identification of these indicators, preventative maintenance will determine the best fit to a manufacturing cycle for maintenance of the molding system.
- A better understanding of the exemplary embodiments of the present invention (including alternatives and/or variations thereof) may be obtained with reference to the detailed description of the exemplary embodiments along with the following drawings, in which:
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FIG. 1 is a schematic representation of an injection molding system; -
FIG. 2 is a schematic representation of an injection unit with sensors; -
FIG. 3 is a schematic representation of a clamp with sensors; -
FIG. 4 is a schematic representation of a mold with sensors; -
FIG. 5 is a schematic representation of a hot runner with sensors; -
FIG. 6 is a schematic representation of a real time preventative maintenance system illustrating the pre-indicator portion of the system and; -
FIG. 7 is also a schematic representation of a real time preventative maintenance system illustrating the post-indicator portion of the system. - Referring now to the schematic representation of a
molding system 100 as illustrated inFIG. 1 , the molding system may be a metal molding system or a plastics molding system. The molding system includes aninjection unit 108 for creating a shot of melt. Adrive 118 provides operational power for rotating and translating a screw (not shown). Thedrive 118 may be electric, hydraulic, or a combination of hydraulic and electric. Abarrel 109 of theinjection unit 108 includes heaters (not shown) to assist melting the raw material. Alternatively, theinjection unit 108 could comprise a well known shooting pot style of injection unit. - A clamp is illustrated as 102. The clamp includes a pair of
platens mold 104. Adrive 120 provides operational power to translate a movingplaten 103 and to provide clamp tonnage. Thedrive 120 may be electric, hydraulic, or a combination of hydraulic and electric. - The
mold 104 includes ahot half 104 b and acold half 104 a and provides at least one core and cavity (not shown) to form a molded part. Optionally, themold 104 includes ahot runner 106 for distributing melt within themold 104. Thehot runner 106 includes electrical heaters (not shown) for keeping a melt at an elevated temperature. - A
power pack 110 is provided for themolding system 100. Thepower pack 110 includes acontrol system 114 to control themolding system 100, ahydraulic portion 112 to provide hydraulic power (if hydraulics are required). Preferably, the control system is an Intel® based computer with a Windows® based operating system such at the Husky® Polaris® Control System. Optionally, in the case of an allelectric molding system 100, ahydraulic portion 112 is not required. Thepower pack 110 also includes electrical components (not shown) andcircuitry 116. - The
molding system 100 includes a connection to asupply 122. Thesupply 122 provides electrical power and chilled water to themolding system 100. Optionally, the chilled water may be applied to keep other devices cool, for example electric motors and electrical components (not shown). - In operation of the
molding system 100,raw material 124 is feed into theinjection unit 108. The injection unit creates a shot of melt. Theclamp 102 closes themold 104 and then applies tonnage to themold 104. Theinjection unit 108 injects the shot of melt into themold 104. When the formedpart 126 is cooled, it is removed from themold 104 and the process repeats. -
Molding systems 100 are designed to run 7 days a week 24 hours a day producing molded parts, for example PET performs, or automotive parts. For example, a PET perform system may have the capability to produce 192 preforms every 15 seconds and an unscheduled down-time can have a significant financial impact to business. At the same time, known periodic maintenance can be planned for during an active production run and preventative maintenance can take advantage of known or scheduled down-times. - Referring now to
FIG. 2 , theinjection unit 108 is further described. Thedrive 118 may includesensors 202. For an electric, drivetypical sensors 202 include those for temperature, voltage, and current. For a hydraulic drive,typical sensors 202 include those for temperature and hydraulic pressure. - The
injection unit 108 also includessensors 204 along a length of thebarrel 109 for sensing temperature. Thesensors 204 are also capable of measuring voltage, and current supplied to the electrical barrel heaters. - The
injection unit 108 also includespressure sensors 206 located upon a length of thebarrel 109 to indicate pressure in thebarrel 109, and pressure differentials before and after the check valve (not shown) located on the screw (not shown) and within thebarrel 109 of theinjection unit 108.Sensors 210 could also measure resin viscosity. - Sensors 200 determine the dryness of the raw material that is provided into a feed throat (not shown) of the
injection unit 108. Sensors 212 could also measure the ambient air temperature and humidity (the operating environment around the molding system). Different raw materials require a different dryness in order to be processed and provide a good quality part. -
Sensors 208 monitor the temperature and flow rate of the supplied chilled water.Sensors 214 could also monitor the physical properties of chilled water. In addition,sensors 216 could monitor voltage and current of the supplied power. -
Sensors 200, 208, and 212 are intended to monitor external factors that could lead to damage of themolding system 100, components, or molded parts (not shown). For example, dirty electricity, voltage/current spikes, poor water quality, poor quality hydraulic oil, air quality, pollution, and dust. - Referring now to
FIG. 3 , theclamp 102 is further described. Theclamp 102 includes adrive 120. For the case of an electric drive, thesensor 302 may monitor voltage, current, and temperature. For the case of a hydraulic drive, thesensor 302 may monitor temperature and pressure. A hybrid drive would have a combination of sensors. Theclamp 102 also includesvarious sensors 300 to monitor stress, strain, and positional alignment of theplatens - Referring now to
FIG. 4 , themold 104 is further described. Themold 104 includes acold half 104 a and ahot half 104 b. Thehot runner 106 is mounted in ahot half 104 b.Sensors 400 monitor the temperature of the chilled water required to cool the part (not shown).Sensors 402 monitor the temperature of thehot half 104 b. Location ofsensors hot half 104 b and thecold half 104 a, or detect removal of the parts from the mold, or monitor post mold cooling. - Referring now to
FIG. 5 , thehot runner 106 is further described.Sensors 500 monitor temperature of the melt and/or hot runner components (not shown) andsensors 502 monitor pressure of the melt in the hot runner system.Additional sensors 504 may be applied to determine the operation or position of a valve gate in a valve gated hot runner. - Referring now to
FIG. 6 , the real timepreventative maintenance system 600 in accordance with an embodiment of the present invention is described.Sensors 612 may include all or some of the sensors (200, 202, 204, 206, 208, 210, 212, 214, 216, 300, 302, 400, 402, 500, 502, and 504) previously described. - For example, if the
injection unit 108drive 118 is hydraulic, thensensors 202 could be capable to monitor temperature and pressure. If theinjection unit 108drive 118 is electric, thensensors 202 could capable to monitor temperature, voltage, and current. - If options or accessories are added to the
molding system 100, then additional sensors to monitor parameters for the options or accessories could be added. For example, a visioning system (not shown) to detect problems with the moldedparts 126 that in turn relates to problems with themolding system 100 or components of themolding system 100. As another example, the visioning system could detect the presence of a stringy gate which in turn relates to a potential temperature issue at a gate (not shown). - Persons skilled in the art will appreciate
sensors 612 are readily available. For example, a thermocouple will sense temperature. A transducer will sense pressure. A voltmeter will sense voltage and an ammeter will sense current. In addition, persons skilled in the art will also appreciate a combination ofsensors 612 could be arranged to monitor and provide unique parameters. - The real time
preventive maintenance system 600 includes acomparator module 602. Thecomparator 602 has access to the realtime threshold status 616 data and the real timeoperational parameters 606 as measured by thesensors 612. - The real
time threshold status 616 data may include one or more of: -
- (a) minimum threshold operational limit data,
- (b) normal operational data (range), and
- (c) maximum threshold operational limit data. This data may be voltage parameters, current parameters, pressure parameters, temperature parameters, humidity parameters, acidity parameters, alkinity parameters, stress parameters, strain parameters, viscosity parameters, alignment parameters, and molded part quality parameters.
- For example, with a particular drive, there are specifications for operating the drive under normal conditions. Optionally, there are limits (minimum and maximum) that provide a range of operational parameters for the drive. As another example, there are specifications for operating electrical heaters under normal conditions and optionally, limits (minimum and maximum) that provide a range of operational parameters for the heaters.
- The real time
operational parameters 606 may include real time measurements of voltage, current, pressure, temperature, humidity, acidity, alkinity, stress, strain, viscosity, fluid cleanliness, alignment, and mold part quality, amongst others, as measured in real time from thesensors 612. - Both the real
time threshold status 616 data and the real timeoperational parameters 606 are correlated for each aspect of themolding system 100. For example, they are correlated for theinjection unit 108,clamp 102,mold 104,hot runner 106,raw materials 124, and thesupply 122. The data and parameters could also be correlated for additional devices and options such as post mold cooling. - The
comparator 602 compares the real timeoperational parameters 606 with the realtime threshold status 616 data to determine if a component is running within the normal range, below a minimum value, or above a maximum value, or a rate of change or frequency towards a limit. - If the
comparator 602 determines the component is running below a minimum value, for the case wherein this is not allowed, thecomparator 602 will trigger theindicator module 604 to indicate preventative maintenance. For the case where this is allowed for a period of time, or for a predefined number of occurrences without damage, then thecomparator 602 checks thehistory 608 module to determine the frequency information and data to see if the maximum frequency has been exceeded and trigger theindicator module 604 to indicate preventative maintenance. - If the
comparator 602 determines the component is running above a maximum value, for the case wherein this is not allowed, thecomparator 602 will trigger theindicator module 604 to indicate preventative maintenance. For the case where this is allowed for a period of time, or for a predefined number of occurrences, then thecomparator 602 checks thehistory 608 module to determine the frequency information to see if the maximum frequency has been exceeded and trigger theindicator module 604 to indicate preventative maintenance. - The
indicator 604 module may send preventative maintenance information to the human machine interface screen, to a central customer computer system, or to a remote manufacturer computer system or customer service computer system. The computer system communicates through a network (wire or wireless), the internet, or an intranet. Preventative maintenance information includes, but is not limited to, customer identification, molding system identification, component identification, dates, and real time operational parameters. - The
history module 608 receives real timeoperational parameters 606. Thehistory module 608 builds and maintains afrequency 624 database. For example, number of times, or length of time a component may be operating below the minimum value or above the maximum value. Thehistory module 608 also contains the limit information for the system, sub-systems, components and parts. Thehistory 608 module also builds and maintains atrends 610 database. Thetrends 610 database contains trend data with respect to the operation of themolding system 100. - The
updater 614 module maintains the realtime threshold status 616 database and may modify the realtime threshold status 616 database. - Initially, the manufacturer of a component, part, system, or sub-system provides the initial and present tense operational data such as the minimum real time threshold operational limits, the maximum real time threshold operational limits, and the normal operational range. Optionally for the minimum and maximum limits, an amount of time, or an accumulated amount of time, or a frequency of occurrence may be provided to understand when a component has been damaged, but will continue to work for some limited amount of time without immediate failure. In addition, the system indicates trends towards a failure as well as failure when it occurs. For example, a drive may be operated at maximum horse power rating for 5 minutes and 75% of maximum power continuously without damage. But, if the drive is operated a maximum horse power for 8 minutes, it will be damaged but not necessarily to the point of immediate failure. Preventative maintenance is therefore required before failure of the drive.
- However, once the
molding system 100 has been in operational use, the future tense of operational data may change. For example, if a particular customer is known to operate themolding system 100 aggressively, the history ofcustomer data 620 may modify the operational data to different limits for preventative maintenance. Theupdater 614 is adaptive and may modify the operational data based upon thecustomer data 620. - The future operational data may also change based upon a geographic location. For example, if a molding system is located in a high humidity or high altitude environment, the
geographic location data 622 may modify the operational data to different limits for preventative maintenance. Theupdater 614 may modify the operational data based upon thegeographic data 622. - The
updater module 614 also receives data from thefrequency module 624 and thetrends module 610 and is adaptive to the environment to modify the data based upon real time use of themolding system 100. For example, if an upper temperature limit was thought to be 400 degrees but later determined through use of themolding system 100 to be 350 degrees, then the realtime threshold status 616 data would be updated accordingly. In addition, theupdater module 614 takes customer data and geographic data to build a repository of system and component intelligence. This intelligence includes the same model of molding systems operated at different customer locations by different customers in different geographic locations. - The
update module 614, associated logic, circuitry, and data may be located or integrated with component parts as well as the complete molding system. For example, afirst updater module 614 may be located with a mold. Asecond updater module 614 could be located with a hot runner. Athird updater module 614 could be located with apower pack 110. Then, the realtime threshold status 616 information stays with the associated system, sub-system, or component part. If amold 104 is removed from production, it can be re-introduced back into production with the last known operational data. In addition, if ahot runner 106 has to be refurbished, it contains the last known operational data. - The
comparator 602, real timeoperational parameter 606 data,sensors 612, and real time thresholdoperational limit 616 data may be combined to form a preventative maintenance Indicator System. - In an embodiment of the invention the indicator system includes a
comparator 602, at least one real time thresholdoperational limit 616 data, andsensors 612. The sensors provide at least one real timeoperational parameter 606 data. Thecomparator 602 comparing the at least one real timeoperational parameter 606 data with the at least one real time thresholdoperational limit 616 data to indicate operational status. The comparator indicating an out of tolerance condition if the operational status is either below a minimum real time operational limit or above a maximum real time threshold operational limit. - Additionally, historical data of real time
operational parameters 608 may be available to thecomparator 602. - In an embodiment of the invention, the indicator system includes a method for sampling at least one real time
operational parameter 606 data from at least onesensor 612 of a molding system. Comparing the at least one real timeoperational parameter 606 data with at least one real time thresholdoperational limit 616 data to indicate operational status. - If the operational status is below a minimum real time threshold operational limit, the comparator further determines if this is not allowed or if a maximum limit has been reached and indicates preventative maintenance. In addition, if the operational status is above a maximum real time threshold operational limit, the comparator further determines if this is not allowed, or if a maximum limit has been reached and indicates preventative maintenance.
- Threshold operational limit data may include at least one maximum limit and/or one minimum limit. These limits may be based upon units of time, frequency of occurrence, or other pre-defined molding system parameters.
- The real time
operational parameter 606 data and the real timeoperational threshold limit 616 data may include: voltages, currents, pressures, temperatures, humidity, acidity, alkinity, stress values, strain values, alignment information, viscosity, or molded part quality, amongst others. Additionally, the real time threshold operational limit data may include at least one of a normal operational range value, a minimum limit value, or a maximum limit value, amongst others. - The
comparator 602 may indicate preventative maintenance for at least one of a molding system, a subsystem of the molding system, a component part of the molding system, auxiliary or supply systems to the molding system, injection unit, power pack, clamp, mold, hot or cold half of the mold, or the hot runner. - The real
time threshold limit 616 data may pertain to at least one of the following, a particular customer, a geographic location, multiple customers, or multiple geographic locations. - The
updater 614,history 608 data,frequency 624 data,trends 610 data,manufacturer 618 data,customer 620 data, andgeographic location 622 data may be combined to form a preventative maintenance update system. This system keeps the realtime threshold status 616 data up to date and current. - In an embodiment of the invention the apparatus for updating preventative maintenance data of a molding system includes an
updater 614, and a realtime threshold status 616 data. The updater having access to categories ofhistory 608 data and the updater providing periodic updates to the realtime threshold status 616 data. The updater may determine which categories are applied to update the realtime threshold status 616 data. Access tohistory 608 data may be remote access, local access, or global access. The updater may modify at least one data parameter of the normal operational range value, or a minimum limit value, or a maximum limit value. - In an embodiment of the invention, the method for updating preventative maintenance data of a molding system includes receiving real time
operational parameter 616 data and storing ashistory 608 data. Sorting thehistory 608 data into categories. Sending real time periodic updates to realtime threshold status 616 data. - The apparatus for updating preventative maintenance data of a molding system may be located with one of the following to include: molding system, power pack, injection unit, clamp, mold, hot half, cold half, hot runner, control system, or a molding system component. There may be one apparatus for updating preventative maintenance data of a molding system or a plurality of apparatus for updating preventative maintenance data of a molding system distributed around the system as previously described.
- The categories of
history 608 data may include at least one offrequency 624 data,trends 610 data,manufacturer 618 data, and plurality ofmanufacturer 618 data,customer data 620, plurality of customer's 620 data,geographic location 622 data, and plurality ofgeographic location 622 data. - Referring now to
FIG. 7 , thepreventative maintenance system 600 is further described. As previously stated, theindicator 604 module may send preventative maintenance information to acustomer system 702 or a manufacturer (or customer service provider) having apredictive maintenance 700 capability. This event may occur from a plurality of customers, a plurality ofmolding systems 100, or a plurality of geographic locations. Optionally, thecustomer 702 may in turn provide the preventative maintenance information to the manufacturer for analysis and resolution. - Upon receipt of preventative maintenance information, a
general practitioner 714 customer service representative may become involved to assess the problem and take corrective action. If ageneral practioner 714 customer service representatives cannot resolve the problem nor take corrective action, then a specialist 718 customer service representative may become involved to assess the problem, assess the symptoms, and perform a root cause analysis to take corrective action or provide recommendations or actions to adjust the molding system process parameters. Optionally, both thegeneral practitioner 714 and the specialist 718 have access to customer'smolding systems 100 through a remote control anddiagnostic system 716 such as the Husky® ServiceLink™ technology. The ServiceLink™ technology provides a connection from a remote computer through a network/internet connection into the Polaris® molding system 100 control system. - A
service scheduler 702 receives the preventative information from thepreventative maintenance 700 module. This may occur automatically to schedule preventative maintenance or may occur as a result of a customer service representative. Theservice scheduler 702 attempts to align preventative service with known customer down time or service time. For example, fit preventative service into known gaps in production cycles, or within scheduled down times. Essentially, create a match between the service provider and the customer when the service provider has personnel and parts ready at the same time the customer is not in an active production run. - Service events and planning include upgrades, a change part date, scheduled service, and production cycle scheduled down time.
- In summary, when an out of tolerance condition is detected by the
comparator 602 which could lead to an instability or failure of themolding system 100, preventative maintenance of this issue is scheduled into the next available service event. - A
parts system 708 also receives preventative maintenance information. Theparts system 708 ensures an available supply of parts throughinventory management 712. In addition, aninventory location 710 module ensures parts are either stored in a central repository, or a distributed repository based upon the geographic or customer information provided with the preventative maintenance information. Theinventory management 712 module may also interact with other vendors and supply chain management software to better predict a supply of spare parts based upon the frequency and trend data available in the preventative maintenance information. - A
business system 706 provides the necessary financial and business level support as a result of the customer service and spare parts activity with a customer. - The
preventative maintenance 700 logic,business system logic 706,service scheduler 702 logic andparts system 708 logic may be grouped to form a preventative maintenance system for a molding system. - In an embodiment of the invention, the
preventative maintenance 700 logic may communicate an indication for preventative maintenance to ageneral practioner 714 for resolution. Thegeneral practioner 714 in turn may transfer the indication for preventative maintenance to a specialist. Alternatively, thepreventative maintenance 700 log may communicate an indication for preventative maintenance directly to aspecialist 718. - Both the
general practioner 714 andspecialist 718 may have access toremote control 716 logic for inspecting, or resolving the need for preventative maintenance. Confirmation may be passed back to thepreventative maintenance 700 logic. - The
preventative maintenance 700 logic may communicate withbusiness system 706 logic for invoicing and billing. - The
preventative maintenance 700 logic may also communicate withservice scheduler 702 logic to schedule service. Scheduling service may be based upon fit into a service provider's schedule, or fit to a customer schedule, or fit to a per-determined existing customer maintenance schedule, or fit to availability of service personnel, or fit to the availability of service parts. - The
preventative maintenance 700 logic may also communicate with parts management logic to manage parts inventory with either a central parts inventory or a distributed parts inventory. - In an embodiment of the invention, the method for real time preventative maintenance of a molding system includes indicating an out of tolerance condition based upon a real time operational status, and creating a notice for preventative maintenance.
- The notice of preventative maintenance may be communicated directly to either a customer system of a service provider system. The customer system in turn may communicate with the service provider system.
- The preventative maintenance system may send communications to either a general practioner or a specialist for resolution. Either of the general practioner or specialist may have remote access and control of the molding system for conducting a preventative maintenance inspection and they may communicate the need for preventative maintenance.
- The preventative maintenance system may communicate with a service scheduler to schedule maintenance. The scheduler may determine a fit to a service provider's schedule, or fit to a customer schedule, or a pre-determined existing maintenance schedule, or fit to availability of service personnel, or fit to availability of service parts.
- The preventative maintenance system may communicate with a parts system for inventory management to provide a central parts inventory or a distributed parts inventory.
- The preventative maintenance system may also communicate with a business system for invoicing and billing.
- In an embodiment of the invention, the real time
preventative maintenance system 600 is embodied in thecontrol system 114 of amolding system 100. Alternatively, it may be embodied as a stand alone system at a customer's factory. Alternatively, it may be embodied as a stand alone system at an equipment manufacturer's site providing customer service. Alternatively, it may be partially embodied in thecontrol system 114 of amolding system 100 and interacting with other software systems distributed at a customer site or a manufacturer's site. The real timepreventative maintenance system 600 may be implemented in hardware, firmware, software or a combination of hardware, firmware, and software. Persons skilled in the art will also appreciate that thepreventative maintenance system 600 may be a single integrated system, or a distributed system, with one or many software/firmware modules, with one or many hardware components and one or many integrated or separate databases. - In another embodiment of the invention, the real time
preventative maintenance system 600 is a data processing system that generates a preventative maintenance notice indicating an out of tolerance condition of a real time operational status of a molding system. The data processing system may further include a generating module for generating a preventative maintenance notice indicating an out of tolerance condition of a real time operational status of a molding system. - In another embodiment of the invention, there is an article of manufacture for directing a data processing system, including a program-usable medium embodying one or more instructions executable by the data processing system. The one or more instructions include data processing system executable instructions for directing the data processing system to generate a preventative maintenance notice indicating an out of tolerance condition of a real time operational status of a molding system.
- The description of the exemplary embodiments provides examples of the present invention, and these examples do not limit the scope of the present invention. It is understood that the scope of the present invention is limited by the claims. Having thus described the exemplary embodiments, it will be apparent that modifications and enhancements are possible without departing from the concepts as described.
Claims (43)
Priority Applications (10)
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PCT/CA2007/000917 WO2007143811A1 (en) | 2006-06-16 | 2007-05-28 | Preventative maintenance system |
US11/763,460 US9975172B2 (en) | 2006-06-16 | 2007-06-15 | Preventative maintenance system |
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CA2653178A CA2653178C (en) | 2006-06-16 | 2007-06-15 | Preventative maintenance system |
PCT/CA2007/001078 WO2007143855A1 (en) | 2006-06-16 | 2007-06-15 | Preventative maintenance system |
CN2007800225145A CN101472724B (en) | 2006-06-16 | 2007-06-15 | Preventative maintenance system |
EP07719994A EP2035208B1 (en) | 2006-06-16 | 2007-06-15 | Preventative maintenance system |
CN201210145068.XA CN102672932B (en) | 2006-06-16 | 2007-06-15 | preventative maintenance system |
TW096122101A TWI351347B (en) | 2006-06-16 | 2007-06-20 | Preventative maintenance system |
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EP (1) | EP2035208B1 (en) |
CN (2) | CN101472724B (en) |
CA (1) | CA2653178C (en) |
DE (1) | DE202007019440U1 (en) |
TW (1) | TWI351347B (en) |
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DE18206431T1 (en) | 2018-02-08 | 2019-12-24 | Geotab Inc. | Telematics prediction vehicle component monitoring system |
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Citations (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3750134A (en) * | 1971-02-11 | 1973-07-31 | Package Machinery Co | Plastic injection molding machine monitor |
US5149193A (en) * | 1991-01-15 | 1992-09-22 | Crompton & Knowles Corporation | Extruder temperature controller and method for controlling extruder temperature |
US5309369A (en) * | 1990-06-18 | 1994-05-03 | Fanuc, Ltd. | Operating state monitoring method for injection molding machines |
US5316707A (en) * | 1991-09-05 | 1994-05-31 | Tempcraft, Inc. | Injection molding apparatus control system and method of injection molding |
US5972256A (en) * | 1994-12-09 | 1999-10-26 | Rjg Technologies, Inc. | Method for determining deflection of mold core-pin |
US6175934B1 (en) * | 1997-12-15 | 2001-01-16 | General Electric Company | Method and apparatus for enhanced service quality through remote diagnostics |
US6192325B1 (en) * | 1998-09-15 | 2001-02-20 | Csi Technology, Inc. | Method and apparatus for establishing a predictive maintenance database |
US6275741B1 (en) * | 1998-10-05 | 2001-08-14 | Husky Injection Molding Systems Ltd. | Integrated control platform for injection molding system |
US6311101B1 (en) * | 1997-11-14 | 2001-10-30 | Engel Maschinenbau Gesellschaft M.B.H. | Method of operating an injection molding machine |
US20020143443A1 (en) * | 2001-03-28 | 2002-10-03 | Pt Holdings Ltd. | System and method of analyzing aircraft removal data for preventative maintenance |
US20020161674A1 (en) * | 2001-01-22 | 2002-10-31 | Scheer Robert H. | Method for fulfilling an order in an integrated supply chain management system |
US6522939B1 (en) * | 1996-07-01 | 2003-02-18 | Robert D. Strauch | Computer system for quality control correlation |
US6643801B1 (en) * | 1999-10-28 | 2003-11-04 | General Electric Company | Method and system for estimating time of occurrence of machine-disabling failures |
US6738748B2 (en) * | 2001-04-03 | 2004-05-18 | Accenture Llp | Performing predictive maintenance on equipment |
US20040148136A1 (en) * | 2002-11-08 | 2004-07-29 | Toshiba Kikai Kabushiki Kaisha | Management supporting apparatus, management supporting system, management supporting method, management supporting program, and a recording medium with the program recorded therein |
US6799154B1 (en) * | 2000-05-25 | 2004-09-28 | General Electric Comapny | System and method for predicting the timing of future service events of a product |
US20050004821A1 (en) * | 2000-10-17 | 2005-01-06 | Garrow Gary R. | Performing predictive maintenance based on a predictive maintenance target |
US6862555B2 (en) * | 2002-11-27 | 2005-03-01 | Taiwan Semiconductor Manufacturing Co., Ltd | Enhanced preventative maintenance system and method of use |
US6957687B2 (en) * | 2001-08-06 | 2005-10-25 | Sintokogio, Ltd. | Method and system for monitoring a molding machine |
Family Cites Families (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH02265723A (en) | 1989-04-07 | 1990-10-30 | Japan Steel Works Ltd:The | Method and apparatus for preventing screw from seizing in injection molding machine |
JPH0474627A (en) | 1990-07-17 | 1992-03-10 | Sumitomo Heavy Ind Ltd | Acceptance inspecting device of molded product |
US6260427B1 (en) * | 1997-07-28 | 2001-07-17 | Tri-Way Machine Ltd. | Diagnostic rule tool condition monitoring system |
US6425293B1 (en) * | 1999-03-13 | 2002-07-30 | Textron Systems Corporation | Sensor plug |
US6446123B1 (en) * | 1999-03-31 | 2002-09-03 | Nortel Networks Limited | Tool for monitoring health of networks |
JP2001058342A (en) | 1999-08-20 | 2001-03-06 | Sumitomo Heavy Ind Ltd | Method for detecting damage in ball screw for driving motor-driven injection molding machine and maintenance method |
US6792040B1 (en) * | 1999-10-29 | 2004-09-14 | International Business Machines Corporation | Modems having a dual power mode capability and methods of operating same |
JP3410426B2 (en) * | 2000-04-07 | 2003-05-26 | 新東工業株式会社 | Equipment maintenance support method and system |
JP3751192B2 (en) * | 2000-08-23 | 2006-03-01 | 株式会社日立製作所 | Remote maintenance system for clinical testing equipment |
JP2003177815A (en) * | 2001-12-07 | 2003-06-27 | Komatsu Ltd | Maintenance system for industrial machine |
US20030158770A1 (en) * | 2002-02-19 | 2003-08-21 | Seh America, Inc. | Method and system for assigning and reporting preventative maintenance workorders |
US20040073468A1 (en) * | 2002-10-10 | 2004-04-15 | Caterpillar Inc. | System and method of managing a fleet of machines |
US7584165B2 (en) * | 2003-01-30 | 2009-09-01 | Landmark Graphics Corporation | Support apparatus, method and system for real time operations and maintenance |
US6874470B2 (en) * | 2003-03-04 | 2005-04-05 | Visteon Global Technologies, Inc. | Powered default position for motorized throttle |
CN2605982Y (en) * | 2003-04-03 | 2004-03-10 | 深圳市珊星电脑有限公司 | Alarming protector for injection machine load controlling circuit |
CN100439081C (en) | 2003-05-02 | 2008-12-03 | 日精树脂工业株式会社 | Mold-clamping control method for injection molding machine |
US7215037B2 (en) * | 2004-11-19 | 2007-05-08 | Saverio Scalzi | Protective wind energy conversion chamber |
US7562234B2 (en) * | 2005-08-25 | 2009-07-14 | Apple Inc. | Methods and apparatuses for dynamic power control |
JP2007090477A (en) * | 2005-09-28 | 2007-04-12 | Toshiba Mach Co Ltd | Repairs advance notice method and device for motor-driven injection molding machine |
-
2006
- 2006-06-16 US US11/454,713 patent/US20070294093A1/en not_active Abandoned
-
2007
- 2007-05-28 WO PCT/CA2007/000917 patent/WO2007143811A1/en active Application Filing
- 2007-06-15 US US11/763,460 patent/US9975172B2/en active Active
- 2007-06-15 CN CN2007800225145A patent/CN101472724B/en active Active
- 2007-06-15 EP EP07719994A patent/EP2035208B1/en active Active
- 2007-06-15 WO PCT/CA2007/001078 patent/WO2007143855A1/en active Application Filing
- 2007-06-15 CA CA2653178A patent/CA2653178C/en active Active
- 2007-06-15 DE DE202007019440U patent/DE202007019440U1/en not_active Expired - Lifetime
- 2007-06-15 CN CN201210145068.XA patent/CN102672932B/en active Active
- 2007-06-20 TW TW096122101A patent/TWI351347B/en not_active IP Right Cessation
Patent Citations (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3750134A (en) * | 1971-02-11 | 1973-07-31 | Package Machinery Co | Plastic injection molding machine monitor |
US5309369A (en) * | 1990-06-18 | 1994-05-03 | Fanuc, Ltd. | Operating state monitoring method for injection molding machines |
US5149193A (en) * | 1991-01-15 | 1992-09-22 | Crompton & Knowles Corporation | Extruder temperature controller and method for controlling extruder temperature |
US5316707A (en) * | 1991-09-05 | 1994-05-31 | Tempcraft, Inc. | Injection molding apparatus control system and method of injection molding |
US5972256A (en) * | 1994-12-09 | 1999-10-26 | Rjg Technologies, Inc. | Method for determining deflection of mold core-pin |
US6522939B1 (en) * | 1996-07-01 | 2003-02-18 | Robert D. Strauch | Computer system for quality control correlation |
US6311101B1 (en) * | 1997-11-14 | 2001-10-30 | Engel Maschinenbau Gesellschaft M.B.H. | Method of operating an injection molding machine |
US6175934B1 (en) * | 1997-12-15 | 2001-01-16 | General Electric Company | Method and apparatus for enhanced service quality through remote diagnostics |
US6192325B1 (en) * | 1998-09-15 | 2001-02-20 | Csi Technology, Inc. | Method and apparatus for establishing a predictive maintenance database |
US6275741B1 (en) * | 1998-10-05 | 2001-08-14 | Husky Injection Molding Systems Ltd. | Integrated control platform for injection molding system |
US6643801B1 (en) * | 1999-10-28 | 2003-11-04 | General Electric Company | Method and system for estimating time of occurrence of machine-disabling failures |
US6799154B1 (en) * | 2000-05-25 | 2004-09-28 | General Electric Comapny | System and method for predicting the timing of future service events of a product |
US20050004821A1 (en) * | 2000-10-17 | 2005-01-06 | Garrow Gary R. | Performing predictive maintenance based on a predictive maintenance target |
US20020161674A1 (en) * | 2001-01-22 | 2002-10-31 | Scheer Robert H. | Method for fulfilling an order in an integrated supply chain management system |
US20020143443A1 (en) * | 2001-03-28 | 2002-10-03 | Pt Holdings Ltd. | System and method of analyzing aircraft removal data for preventative maintenance |
US6738748B2 (en) * | 2001-04-03 | 2004-05-18 | Accenture Llp | Performing predictive maintenance on equipment |
US6957687B2 (en) * | 2001-08-06 | 2005-10-25 | Sintokogio, Ltd. | Method and system for monitoring a molding machine |
US20040148136A1 (en) * | 2002-11-08 | 2004-07-29 | Toshiba Kikai Kabushiki Kaisha | Management supporting apparatus, management supporting system, management supporting method, management supporting program, and a recording medium with the program recorded therein |
US6862555B2 (en) * | 2002-11-27 | 2005-03-01 | Taiwan Semiconductor Manufacturing Co., Ltd | Enhanced preventative maintenance system and method of use |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2015057974A3 (en) * | 2013-10-16 | 2015-11-12 | Milacron Llc | Remote machine monitoring systems and services |
CN107315396A (en) * | 2017-05-27 | 2017-11-03 | 中国电子科技集团公司第三十六研究所 | A kind of state monitor maintenance and predictive maintenance Combined maintenance method and system for planning |
CN108171435A (en) * | 2018-01-09 | 2018-06-15 | 上海交通大学 | A kind of production schedule decision-making technique for considering preventive maintenance |
CN109933890A (en) * | 2019-03-11 | 2019-06-25 | 中国电子科技集团公司第三十六研究所 | A kind of product comprehensive maintenance method and apparatus |
Also Published As
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CN101472724B (en) | 2012-07-04 |
EP2035208B1 (en) | 2012-08-15 |
TWI351347B (en) | 2011-11-01 |
CA2653178A1 (en) | 2007-12-21 |
CN102672932B (en) | 2016-08-03 |
WO2007143855A1 (en) | 2007-12-21 |
CN102672932A (en) | 2012-09-19 |
CN101472724A (en) | 2009-07-01 |
US9975172B2 (en) | 2018-05-22 |
TW200809665A (en) | 2008-02-16 |
WO2007143811A1 (en) | 2007-12-21 |
EP2035208A4 (en) | 2009-07-01 |
DE202007019440U1 (en) | 2012-07-23 |
US20070294121A1 (en) | 2007-12-20 |
EP2035208A1 (en) | 2009-03-18 |
CA2653178C (en) | 2011-10-11 |
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