Abstract:
A product performance integrated database apparatus and method collects product performance data, determines the root cause of detected product failures and develops corrective action to correct the detected failures. The method determines an initial degree of risk of selected product failures by determining the severity of the effect of each failure and the frequency of occurrence of the effect of each failure. The severity of the effect and the frequency of occurrence are ranked with different ranking values. An initial risk assessment of each failure is the product of the ranked severity value and the selected ranked frequency of occurrence of the failure. Failures exceeding a threshold preliminary risk assessment are subject to the root cause or detected product failure analysis. Once a corrective action for the root cause of failure is determined, a final risk assessment for each corrective action is determined by the product of the initial risk assessment and a determined failure correction validation value.

Description:
BACKGROUND  
         [0001]    The development of a product involves numerous steps and contributions from many people over a long period of time from initial conception and design through development of prototypes, testing, final product design, the development of manufacturing processes for the product, the final product approval and then the manufacturing and delivery of the product to customers. While each product can be viewed as a new entity, frequently, companies who specialize in a particular product actually develop a new product which contains many features which can be carried over from prior products.  
           [0002]    While it would be enviable to be able to develop a product without time and cost constraints in which each element of the product could be fully designed and completely tested at each stage of development; reality, however, imposes both time and cost constraints on any product development thereby requiring trade-offs in the amount of testing, and the available time and resources in terms of money, people, buildings, equipment, etc., which can be made available for a particular product development.  
           [0003]    It is also very common for product development people, including engineers, designers, financial analysts, etc., to be working on several product development projects at one time. When one project is completed, such individuals immediately move on to the next product or project. This process has a tendency to isolate the people involved in the development of product from the warranty problems which arise after the product is introduced into the marketplace. Such warranty problems resulting from product defects in design, materials or combinations thereof, are directed back to appropriate individuals in the manufacturing company for problem detection and correction. Frequently, the individuals responsible for such warranty claims and correction are not the same individuals who were involved in initial product development and who would find the problems, causes and solutions to be of immense value when designing future products which may have similar features.  
           [0004]    Despite the fact that large portions of the product development process are reduced to computer records, there usually exists no identifiable repository of manufacturing, engineering, and quality data which can be readily accessed and used for analysis and interpretation. Nor is there any linked databases which would allow for product performance traceability that is necessary for root cause investigations.  
           [0005]    While failure mode effect and analysis (FMEA) is used by many companies as a design review technique to focus the development or products and processes on prioritized actions to reduce the risk of product field failures and to document those actions and the entire review process, frequently, there is inadequate FMEA content and utilization for a totally accurate risk assessment. Further, there is usually no updated, direct link of failure mode to current root cause and corrective action.  
           [0006]    The current product development processes also lack any organized process to link the definition of engineering drawing characteristic or process control plan parameters to FMEA, root cause/corrective action, or supporting data. Such prior product development processes also lack any understanding of the quality cost elements (failure, appraisal, and prevent) that are attributable to the total cost of quality.  
           [0007]    Further, there usually is no design or process specific lessons learned database to refer to for future product development.  
           [0008]    Therefore, it is desirable to provide a product performance integrated database apparatus and methodology which has the following features:  
           [0009]    1. A systematic link of product design and process information for root cause and risk assessment decision making.  
           [0010]    2. Quality and reliability information traceability to all tasks and activities during the product development process.  
           [0011]    3. Just in time FMEA development and generation of design/process guidelines.  
           [0012]    4. Provides an understanding of the total cost of quality and its cost components.  
           [0013]    5. Provides the basis for new product/process risk analysis by accumulating updated design/process specific lessons learned.  
         SUMMARY  
         [0014]    The present invention is a product performance integrated database apparatus and method which uniquely enables product performance data to be analyzed, placed in a prioritized initial risk assessment ranking based on initial failure effect risk so as to subject only high risk assessment failures to a root cause and effect analysis to develop a corrective action for the product failure. The corrective action is validated prior to a final risk assessment being made from the product of the initial risk assessment times a ranked validation value.  
           [0015]    The present apparatus is embodied in a software program accessible through a telecommunication network. CPU based terminals provide prompts for acquiring, documenting and storing all product related performance data, risk assessment analysis, cause and effect analysis, and corrective actions.  
           [0016]    The method of the present invention is used to determine product performance. The method comprises the steps of:  
           [0017]    collecting product performance data;  
           [0018]    determining the failure mode of detected product failures;  
           [0019]    conducting a failure mode effect and analysis procedure to determine a degree of risk of a detected failure; and  
           [0020]    developing corrective action to correct the detected failures.  
           [0021]    The step of determining degree of risk includes the steps of determining the severity of the effect of each failure, and determining the frequency of occurrence of the effect of each failure. According to the method, the determined severity of effects of a plurality of different detected failures are ranked to generate a plurality of different severity ranking values. The frequency of occurrence of the plurality of different failures are also ranked in a ranked frequency of occurrence values.  
           [0022]    The method includes the step of determining a preliminary risk assessment of each failure as a multiplied product of the ranked severity value and the ranked frequency of occurrence value. The preliminary risk assessment is compared with the threshold to determine high risk assessments suitable for a root cause and effect analysis. The analysis determines the root cause of the detected product failure.  
           [0023]    The method and apparatus also include means and a process step for determining the cost of quality assessment. The total cost of quality assessment is determined by the sum of prevention costs, appraisal costs and failure costs.  
           [0024]    The product performance integrated database apparatus and method of the present invention affords many advantages over previously devised product development processes. The present method provides a linking of product design and process information for use in root cause and risk assessment decision making. All quality and reliability information is traceable to all tasks and activities during the product development process.  
           [0025]    The present method and apparatus also provides an understanding of the total cost of quality as well as the quality cost components. These costs as well as the stored lessons learned from each complete product development are stored for future use. This simplifies future product development programs by enabling quality issues to be shifted to the design and process development stage rather than later in the product prototype development or field use stages. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWING  
       [0026]    The various features, advantages and other uses of the present invention will become more apparent by referring to the following detailed description and drawing in which:  
         [0027]    [0027]FIG. 1 is a block diagram of the product performance integrated database apparatus and method of the present invention;  
         [0028]    [0028]FIG. 2 is a block diagram of the input database failure flow structure;  
         [0029]    FIGS.  3 A- 3 F are Pareto failure mode charts;  
         [0030]    FIGS.  4 A- 4 D are flow diagrams showing the sequence of the operation of the apparatus and method of the present invention;  
         [0031]    [0031]FIG. 5 is a block diagram of the main sections of the FMEA risk assessment apparatus and method of the present invention;  
         [0032]    [0032]FIGS. 6A, 6B and  6 C are pictorial spreadsheet representations of the operation of the FMEA portion of the present invention;  
         [0033]    [0033]FIGS. 7A and 7B are pictorial spreadsheet representations of the PDCA portion of the present invention;  
         [0034]    [0034]FIG. 8 is a fishbone chart used in the PDCA portion of the invention shown in FIGS. 7A and 7B; and  
         [0035]    [0035]FIG. 9 is a pictorial representation of a computer apparatus used to implement the present invention. 
     
    
     DETAILED DESCRIPTION  
       [0036]    The present product performance integrated database apparatus and method can be implemented via a suitable computer based local or wide area network or combinations thereof The plurality of computer based workstations  7  or PC&#39;s can access the product performance databases in memory  8  under program control to review, input, calculate and/or provide notifications as necessary to a central server or workstation containing such databases, processing units, memory, etc. Any suitable communication network  9  can be employed as part of the present apparatus, including land lines, microwaves, Internet, and combinations thereof  
         [0037]    The following description of the methodology of the present invention is to be understood to implement in a software control program accessible from a central workstation or server by each individual terminal. Although not specifically described, suitable access verification, and a tiered hierarchy of authorized access levels, passwords, encryption, etc., may be employed to provide security for the entire process as well as to enable only authorized individuals to have access to certain functions, databases, etc.  
         [0038]    Referring now to FIG. 1, there is depicted a general flow diagram of the apparatus and method of the present product performance integrated database apparatus. The present apparatus includes three main sections: a product performance input database and analysis section  10 , a root cause and corrective action (PDCA) section  12 , and a general function mode and effect analysis section (VFMEA).  
         [0039]    In the product performance input data analysis section  10 , a plurality of databases shown in the following Table A are provided to receive various inputs on product performance and engineering/manufacturing changes. The failure recognition of a product or any component of a product are input into the various databases shown in Table A as a failure recognition.  
                             TABLE A                       Product Performance (PP) or       Eng./Manufacturing Change (PCR) Database List                                     1.   Field Performance-PP               A-Launch (0 miles)               B-Containment               C-Warranty (&gt; 0 miles)               D-Extended Mileage (&gt; warranty period)            2.   Product Change Requests-PCR               A-Engineering Change               B-Manufacturing Change            3.   Manufacturing Performance-PP               A-EOLT (End of line test rejects)               B-In-process               C-Audit            4.   Validation Performance               A-DV (design verification)               B-PV (process verification)               C-CC (continuing conformance)            5.   Proto/Pilot Bld. Inspection-PP               A-Prototype component               B-Pilot component               C-Prototype asm.               D-Pilot asm.            6.   Measurement System Performance-PP               A-Development Test Equipment               B-Manufacturing Process Equipment               C-Incoming insp. tool/gages               D-Component supplier gage            7.   Simulation-PCR               A-Electrical E-Mold flow               B-Mechanical F-EMI/EMC               C-Thermal G-Geometric               D-Fluid flow            8.   Supplier Dev. Performance-PP            9.   Process Control-PP           10.   Production Process Capability Performance-PP           11.   Manuf. Preventative Maintenance-PP           12.   PPAD (Supplier &amp; Company)-PCR           13.   Engineering Dev. Test Performance-PP           14.   Lessons Learned (General practices)           15.   Engineering Calculation-PCR           16.   Dimensional Tolerance Stack-up (Manual)-PCR           17.   Internal/External part interface-PCR           18.   New customer requirement-PCR           19.   Supplier Requirement-PCR           20.   Cost improvement-PCR           21.   Drawing change-PCR               A-Print to Part               B-Part list               C-Print dim. error           22.   Tool Wear-PP                      
 
         [0040]    The present method takes the output of the failure indication from any of the input databases shown by reference number  16  in FIG. 2 and prepares summary statistics as shown by block  18 . Table B shows the summary statistics which are calculated for the first seven failure recognition database features.  
                         TABLE B                           Summary Statistics            Source (failure recognition)   Summary Statistics               1. Field Performance   Fourteen product profiles that address: what,           who, where, when, and quantity (see new field           performance module)       2. Product Change Requests   (within PDCA)       3. Manufacturing Performance   Frequency of rejects per time (work, mos) and           shift number. Function and/or failure mode           reject types per above time interval       4. Validation Test Performance   Life test reliability demo           Total test success prob.           Function and/or failure mode reject types/test           and their frequency       5. Prototype/Pilot Build Inspection Perf.   Component Cp and Cpk by parametric           Asm bld yield           Asm function/failure mode reject types       6. Measurement Systems Performance   Calibration (% accuracy)           Gage Total R + R %       7. Simulation Performance   Frequency of failure mechanism per number of           simulation sample runs           Failure mechanism type recognized per           simulation           Failure mechanism/mode probability                  
 
         [0041]    The output of the summary of statistics section  18  is used to create a Pareto chart of function/failure mode shown by reference number  20  in FIG. 2. A detailed example of a Pareto chart is shown in FIGS.  3 A- 3 F for six different failures along with the number of occurrences of the failure modes of each reported failure. The number of failures in the chart can be varied as needed.  
         [0042]    A procedure sequence is shown in FIGS.  4 A- 4 D. Upon issuance of a start instruction  31 , the sequence advances to a query in step  33  of whether an input is requested for a failure condition by a particular product line. A “yes” answer causes a tracking number to be assigned to the failure condition in step  35 .  
         [0043]    Next, the process confirms the failure condition in step  37 . The output of this decision step  37  is either that an indication that a hard failure has occurred and has been confirmed or, alternately, that a hard failure has occurred, but is one which is not confirmed. Next, the reported failure condition is input in step  37  into the appropriate input database shown in Table A.  
         [0044]    At periodic intervals, or at certain time tables during the product development process, the failures are analyzed and a Pareto chart of the top failures, based on number of failures, is prepared in step  41  as described above and shown in FIGS.  3 A- 3 F. The Pareto chart of top failures is based on function and failure modes.  
         [0045]    In the present method, control then switches to the FMEA section  14  shown in FIG. 1. The failure function and mode analysis, data and numbers from the Pareto chart are input to the FMEA section.  
         [0046]    As shown in FIG. 5, the output  46  from the failure input data as contained in the Pareto function/failure chart is input to a failure definition section  21  in the FMEA section  14  for risk assessment.  
         [0047]    As shown in FIGS. 6A, 6B and  6 C some of the initial information used in the (VFMBA) process is obtained from the input databases  10  as shown in FIG. 5. The (VFMEA) process  14  includes four main sections: failure definitions  21 , ranked failure elements  22 , root cause and control  24 , and risk assessment  26 .  
         [0048]    In the failure definition section  21 , a functional description  28  includes an input of an item number in step  30 , a functional description  32  selected from the list shown in Table C and a function description code, also from the list shown in Table C, but not shown.  
                         TABLE C                       Multifunction Switch Function                                Left turn signal   Wash operation       Right turn signal   Low beam       Turn signal cancel   High beam       Headlamp switch   Cruise control on/off       Park lamp switch   Cruise control set/coast       Fog lamp switch   Cruise control resume/accel       Beam change (flash to pass)   Wiper delay - low speed mode       switch       Hazard switch   Wiper delay - high speed mode       Dimmer switch   Wiper delay - intermittent speed modes       Mist operation                  
 
         [0049]    Next, in section  34 , a degree of complexity number is input based on the number of components supporting the particular functional description. The performance specification and section number reference from the product function performance specification library  36  or the failure class  38 , namely, (a) for (FMVSS), (b) for major and (c) for minor is input into sections  40 ,  42 .  
         [0050]    Next, the problem is confirmed by an indication of a function failure occurrence in section  44 . This function failure confirmation status is selected from the list shown in Table D.  
         [0051]    Within the present invention, the term “failure” means not only that a product or component has catastrophically failed, i.e, breaks, burns, cracks, etc., but also a product failure where the product does not meet some functional or dimensional design or process specification, or does not meet some visual inspection specification criteria, violates any industry or government standards, and, also a product design or process characteristic which meets specification criteria but exhibits significant variation within the criteria.  
                                             TABLE D                       Failure Criterion       The following are definitions for the three different types of failure classifications which are       possible based on variable or attribute type date collected for either a product design or       manufacturing process.                   1 - Hard and confirmed failure-HC            A hard and confirmed failure is defined as a product which exhibits at least one of the following       failure conditions and has been verified at least once after the initial complaint was registered:       A. Does not meet some functional or dimensional design/process specification criteria       B. Does not meet some visual inspection specification criteria       C. Violates any FMVSS or emission governmental standards.       D. Catastrophically fails (breaks, burns, cracks, etc.)            2 - Hard Failure and No Trouble Found (HNTF)            A hard and no trouble found failure is defined as a product which exhibits at least one of the       following failure conditions and has not successfully been verified at least once after the initial       complaint registered:       A. Does not initially meet some functional design/process specification criteria       B. Does not meet some visual inspection specification criteria       C. Violates any FMVSS or emission governmental standards            3 - NTF-NTF (NTF)       4 - Soft Failure            A soft failure is defined as a product design or process characteristic which meets specification       criteria but exhibits significant variation within these criteria. A violation of any of the following       statistical criteria constitutes a soft failure condition:       A. Pp (pre-production level) &lt; 1.33       B. Ppk (pre-production level) &lt; 1.33       C. Cp (production level) &lt; 1.67       D. Cpk (production level) &lt; 1.67                  
 
         [0052]    The failure mode is then defined in section  50 . The description is entered in step  52  of the particular failure mode as selected from the list shown in Table E.  
                             TABLE E                       Switch Product Line Design and Process Failure Modes       This list applies to all electromechanical switch products       (multifunction, ignition, IP, door alarm, deck lid, hazard, etc.)                                Electrical Function (E)   Noise (N)   Missing ID       Open circuit (high resistance)   BSR (buzz, squeak, or rattle)   Wrong ID       Short circuit (low resistance)   upon no function actuation   Wrong location       Intermittent circuit   BSR upon function actuation   No key way       High leakage current   Measurement (R)   Incorrect key way location       Mechanical Function (M)   Failed parts determined as   Wrong potting (adhesive)       No mechanical actuation   good   material       Erratic mechanical actuation   Good parts determined as   Misplaced component within       High mechanical force effort   failures   assembly       Low mechanical force effort   Visual - fit or form (V)   No wire crimp       Lack of mechanical force   Features warped   Inadequate wire crimp       effort   Misaligned components   Over-crimped (damage)       Binding/drag   Excessive gap   Inadequate wiring tinning       Unable to rotate/jams   Loose component   No wire tinning       Sticks upon rotation   Cracked   Excessive wire tinning       Excessive play   Broken   Burned appearance       Unable to latch/fasten   Wrong part/feature   Parts jams in fixture       Unable to unlatch   Wrong color   Part does not fit in fixture       Weak snap   Wrong texture   Lack of potting (adhesive)       Inadequate pre-load force   Missing component/feature   Excessive potting (adhesive)       No pre-load   Missing graphics   No illumination       Misindexing   Scratched   Intermittent illumination       Loss of function spring return   Chipped   Feel (F)       Early function actuation   Flash   High insertion force       Late function actuation   Cannot be connected/fastened   Low insertion force       Inadequate mechanical   Excessive grease   Variable insertion force       retention   Missing seal   High removal force       Overtravel   Exposed copper   Low removal force       Undertravel   Misplaced component/feature   Variable removal force       Will not change function states   Bent/deformed component   High temperature (overheat)       Loss of sealing capability   Sheared   Low temperature (too cold)       High mechanical torque   Wrong texture   Irregular surface smoothness       Low mechanical torque   Surface irregularities   Odor (O)       Inadequate fluid pressure   Mispositioned component   Burnt smell       Excessive fluid pressure   within system       No fluid pressure   Foreign residue/particles                  
 
         [0053]    A code is assigned to the particular failure mode in step  54 . Next, the source of the function or failure mode is entered in step  54  from Table A.  
         [0054]    Referring back to FIG. 4B, in step  60 , the function/failure mode probability of occurrence, defined as P(O)=the number of failures divided by the number of units shipped or tested, is calculated. The shipment volumes or test sample size are obtained from manufacturing shipment and test specification sample reference library databases. The value of P(O) is applied to a probability of occurrence/ranking look-up table, with separate tables being provided for design and process failure modes, as shown in Tables F and G. The ranking value associated with the particular possible failure rate is entered in column  62  in FIG. 6A.  
                         TABLE F                           Frequency or Probability of Occurrence            O   DSDSA Criteria               1   Defect not present on existing or similar products used in similar functions and conditions.           No incident known among customers. x ≦ 1/1,500,000 [x ≦ .67 ppm] and for measured           parametric Cp ≧ 1.67 and Cpk ≧ 1.67       2   1/1,500,000 &lt; x ≦ 1/150,000 [0.67 ppm &lt; x ≦ 6.67 ppm] and for measured parametric 1.5 &lt;           Cp ≦ 1.67 and 1.45 &lt; Cpk ≦ 1.67       3   Few defects on existing or similar products used in similar functions and conditions. Very           few incidents known among customers. 1/150,000 &lt; x ≦ 1/15,000 [6.67 ppm &lt; x ≦ 66.67 ppm]           and for measured parametric 1.33 &lt; Cp ≦ 1.5 and 1.27 &lt; Cpk ≦ 1.45       4   1/15,000 &lt; x ≦ 1/2,000 [66.67 ppm &lt; x ≦ 500 ppm] and for measured parametric 1.16 &lt; Cp           ≦ 1.33 and 1.10 &lt; Cpk ≦ 1.27       5   Defect that appeared occasionally on existing or similar products used in similar functions           and conditions. A few incidents known among customers. 1/2,000 &lt; x ≦ 1/500 [500 ppm &lt;           x ≦ 2,000 ppm] and for measured parametric 1.03 &lt; Cp ≦ 1.16 and 0.96 &lt; Cpk ≦ 1.10       6   1/500 &lt; x ≦ 1/200 [2,000 ppm &lt; x ≦ 5,000 ppm] and for measured parametric 0.94 &lt; Cp ≦ 1.03           and 0.86 &lt; Cpk ≦ 0.96       7   Defect that appeared frequently on existing or similar products used in similar functions and           conditions. Numerous incidents known among customers. 1/200 &lt; x ≦ 1/100 [5,000 ppm &lt;           x &lt; 10,000 ppm] and for measured parametric 0.86 &lt; Cp ≦ 0.94 and 0.78 &lt; Cpk ≦ 0.86       8   1/100 &lt; x ≦ 1/50 [10,000 ppm &lt; x ≦ 20,000 ppm] and for measured parametric 0.78 &lt; Cp ≦ 0.86           and 0.69 &lt; Cpk ≦ 0.78       9   Defect appeared more often. Risk that vehicles have to be recalled 1/50 &lt; x ≦ 1/20 [20,000 ppm           &lt; x ≦ 50,000 ppm] and for measured parametric 0.64 &lt; Cp ≦ 0.78 and 0.55 &lt; Cpk ≦ 0.69                  
 
         [0055]    [0055]                                                   TABLE G                           Suggested Evaluation Criteria: (Process)                Possible Failure               Probability of Failure   Rates   Cpk   Ranking                    Very High: Failure is almost   ≧1 in 2   &lt;0.33   10       inevitable   1 in 3   ≧0.33   9       High: Generally associated with   1 in 8   ≧0.51   8       processes similar to previous   1 in 20   ≧0.67   7       processes that have often failed       Moderate: Generally associated   1 in 80   ≧0.83   6       with processes similar to previous   1 in 400   ≧1.00   5       processes which have experienced   1 in 2,000   ≧1.17   4       occasional failures, but not       in major proportions.       Low: Isolated failures associated   1 in 15,000   ≧1.33   3       with similar processes.       Very Low: Only isolated failures   1 in 150,000   ≧1.50   2       associated with almost identical       processes.       Remote: Failure is unlikely. No   ≦1 in 1,500,000   ≧1.67   1       failures ever associated with almost       identical processes.                    
         [0056]    Concurrent with, or subsequent to, the calculation of the probability of occurrence of value P(O), the particular severity ranking is determined by describing in step  64  in the failure mode section, the particular effect of the specific failure. Example of severity effect is shown in FIG. 6B.  
         [0057]    Next, step  66  generates a severity ranking for either a design or process failure selected from Tables H and I, respectively. A particular severity ranking is the input in step  66 .  
                                   TABLE H                           Severity of Effect (Design)            S   Criteria                    1   No discernible effect       2   Failure effect noticed by discriminating users. No loss of function       3   Intermittent out-of-range function, fit or audible performance       4   Continuous out-of-range function, fit or audible performance       5   Loss of single convenience/comfort function (single UPA sensor not working single tell-tale           signal not working, etc.)       6   Loss of multiple convenience/comfort functions (all channels down, all tell-tales not working           etc.)       7   Intermittent loss of critical function, e.g. power-supply       8   Loss of critical function, e.g. power-supply       9   Intermittent loss of function related to safety or regulatory items, e.g. headlamps, lock-           unlock, wiper control, etc.       10   Sudden loss of function related to safety or regulatory items: headlamps, lock-unlock, wiper           control, etc.                  
 
         [0058]    [0058]                                           TABLE I                           Suggested Evaluation Criteria: (Process)            Effect   Criteria   Ranking                    Hazardous - without   May endanger machine or assembly operator. Very high   10       warning   severity ranking when a potential failure mode affects safe           vehicle operation and/or involves noncompliance with           government regulation. Failure will occur without warning.       Hazardous - with   May endanger machine or assembly operator. Very high   9       warning   severity ranking when a potential failure mode affects safe           vehicle operation and/or involves noncompliance with           government regulation. Failure will occur with warning.       Very High   Major disruption to production line. 100% of product may   8           have to be scrapped. Vehicle/item is inoperable, with loss of           primary function. Customer very dissatisfied.       High   Minor disruption to production line. Product may have to be   7           sorted and a portion (&lt;100%) scrapped. Vehicle/item is           operable, but at reduced level of performance. Customer           dissatisfied.       Moderate   Minor disruption to production line. A portion (&lt;100%) of the   6           product may have to be scrapped (no sorting). Vehicle/item is           operable, but Comfort/Convenience item(s) inoperable.           Customer experiences discomfort.       Low   Minor disruption to production line. 100% of product may   5           have to be reworked. Vehicle/item is operable, but           Comfort/Convenience item(s) inoperable at reduced level of           performance. Customer experiences some dissatisfaction.       Very Low   Minor disruption to production line. The product may have to   4           be sorted and a portion (&lt;100%) reworked. Fit           &amp;Finish/Squeak &amp; Rattle item does not conform. Defect           noticed by most customers.       Minor   Minor disruption to production line. Fit &amp;Finish/Squeak &amp;   3           Rattle item does not conform. Defect noticed by average           customers.       Very Minor   Minor disruption to production line. A portion (&lt;100%) of   2           the product may have to be reworked on-line but in-station.           Fit &amp;Finish/Squeak &amp; Rattle item does not conform. Defect           noticed by discriminating customers.       None   No effect.   1                    
         [0059]    Next, in step  68 , an initial risk calculation is made (S×O) for each function/failure mode from the Pareto chart  20 . The product of (S×O) is input into the database. Next, as shown in FIG. 4B, the initial risk of assessment value is compared with an initial risk assessment threshold in step  70 . Several criteria are involved in this determination. First, the initial risk assessment value is compared with the threshold, for example, at the threshold of  20 . Risk assessments greater than or equal to 20 are considered a high risk assessment and are flagged for immediate action. Risk assessments less than 20 are of lesser priority and can be considered after failures having higher risk assessment values are addressed. Alternately, a high priority risk assessment can be assigned to any severity ranking greater than a different threshold, such as a threshold of 7, by example only.  
         [0060]    A failure mechanism or root cause analysis (PDCA) is then started for high priority risk assessments. Some of the information from this section can be obtained from (PDCA) data defined separately in the above-described steps. For example, a particular failure mechanism category input is provided in step  80  in FIG. 6B. The particular specific failure mechanism is then described in step  82 . A code is assigned to the failure mechanism described in step  82 . The fishbone diagram shown in FIG. 8 is then employed to help brainstorm and identify the root cause category for the particular failure mode in question. Other inputs include the responsible component name or process step description in step  84 , the component part number or process step number in step  86  and whether the root cause is a design or process failure in step  88 .  
         [0061]    A more complete PDCA process can be implemented as shown in FIGS. 7A and 7B. The formal PDCA procedure involves the following steps:  
         [0062]    1. Prioritize;  
         [0063]    2. Brainstorm root causes(s) (Fishbone Diagram);  
         [0064]    3. Justify causes with available supporting data;  
         [0065]    4. Isolate most significant cause(s);  
         [0066]    5. Institute design or process corrective action;  
         [0067]    6. Validate;  
         [0068]    7. Open/close status; and  
         [0069]    8. Assess cost of quality.  
         [0070]    The following Table J is a list which helps to establish a prioritization scheme for directing failure root cause and corrective action activity as defined in the PDCA database. This priority scheme is followed once significant risk is established (see procedure flow chart and Risk Assessment Guide Sheet). A lower number/letter combination for a specific product failure condition represents higher priority given to initiating the PDCA process. These failure conditions would originate from one of the specific input databases:  
                                             TABLE J                       PDCA Prioritization Criterion                   1 - Hard and confirmed failure-HC            A. Engineering/Manufacturing Changes (internal to PDCA)       B. Product Launch Failures       C. Field (at the customer assembly plant) Failures       D. Field (through the dealership and in the field) Failures       E. Manufacturing Yield and Rework Failures (EOLT and in-process defects)       F. Continuing Conformance Failures - Validation database       G. DV or PV Test Failures - Validation database       H. Measurements Systems Capability (total gage R&amp;R &lt; 30%)       I. Simulation Failures            2 - Hard and No Trouble Found (NTF) Failures            A. Product Launch Failures       B. Field (at the customer assembly plant) Failures       C. Field (through the dealership and in the field) Failures       D. Manufacturing Yield and Rework Failures (EOLT and in-process defects)       E. Continuing Conformance Failures - Validation database       F. DV or PV Test Failures - Validation database            4 - Soft Failure            A. Process Control (process characteristics exceed process control limits)       B. Process Capability (incapable process characteristics)       C. Supplier Performance (incoming inspection or Supplier outgoing inspection incapability)       D. Prototype inspection (incapable key component/assembly characteristics)                  
 
         [0071]    Before the various formal procedural steps shown in FIG. 4C can take place, certain background data must be assembled. As shown in FIG. 7A, the background data consists of three main sections, namely, product identification  156 , source of input  164  and failure description  172 .  
         [0072]    The product identification section  156  includes a number of categories, including the (PDCA) tracking number  158  and a product line description  160 . The following Table K shows an example of a product line description for section  160 .  
                         TABLE K                       Product Line Descriptions                                    Sensors           Ultrasonic Park Assist (UPA)           Crankshaft           Camshaft           Rain           Steering Angle           Electromechanical Switches           Multifunction           Door Alarm           Door Ajar           Ignition           Hazard           Instrument Panel Switch           Clockspring           Key Alarm           Decklid           Passenger Switch Inflatable Restraint (PSIR)           Electric Control Modules           Body           Wiper           UPA           Rain           Climate           Rear Integrated Module (RIM) - body control           Others           UPA Speaker           Wiper Motor           Wiper Actuator                      
 
         [0073]    A code in section  162  is assigned to each of the product line descriptions. A part number and a revision level are also assigned. Next, the customer is identified by code which can be provided in Table K. The event date of the failure or failure input is then recorded in section  163 .  
                             TABLE L                           Customer List                OEM   1st Tier                       Company A   Company F           Company B   Company G           Company C   Company H           Company D   Company I           Company E                      
 
         [0074]    The next section  164  determines the source of the failure recognition input. In section  166 , a determination is made whether the failure mode is a product performance input (PP) or an engineering/manufacturing change (PCR) these inputs are received from the input databases shown in Table A.  
         [0075]    Next, in section  168 , the source for corrective action activity is defined from Table A. Finally, the location in the (VSDP) phase is defined in section  170 .  
         [0076]    Next, in the failure description section  172 , the function description of the failure is defined in step  174  from Table C and assigned a function code in section  176 . An example of typical function descriptions for a multi-function switch, described by way of example only, is provided in Table C. Next, in section  178 , a failure mode description and a failure mode code in step  180  is assigned to each failure description. Table E gives an example of failure modes for a switch product line design and process failure. It will be understood that this is only an example of failure modes for switches. Other failure modes will be defined for other components.  
         [0077]    Next, section  180  is used to define the root cause of the failure mechanism. First, a failure mechanism category is selected in step  182  and assigned a code in step  184 . FIG. 8 depicts a fishbone diagram of design and process failure mechanism categories for input into section  182 . One example of a failure mechanism category is shown by “dimensional instability” in FIG. 7B. The fishbone diagram brings together individuals in different disciplines to brainstorm as to the particular failure mechanism which is the root cause of the reported failure.  
         [0078]    The output of the brainstorming session, either at one meeting or after further review and investigation, should result in the definition of a specific failure mechanism in section  186 . One example of such a description is shown in FIG. 7B. Next, the reporting process includes an identification of the particular component name or process step in section  188  followed by a part number in step  190  and an indication of whether the specific failure mechanism is a design or process in step  192 .  
         [0079]    Sections  188  and  190  make reference to databases which store bill of material reference library and a process flow diagram library to determine component names and part numbers or process step descriptions and step numbers.  
         [0080]    These (PDCA) contribution steps are summarized in FIG. 4C in which the assignment of the (PDCA) number in step  158  is the initial step in the (PDCA) procedure which then continues to define prioritization for (PDCA) activity in step  159 . Next, in step  161 , the (PDCA) is executed to determine the root cause and provide design/process control methods or corrective action.  
         [0081]    Referring back to FIG. 7B, in a specific section labeled current control for corrective action shown by reference number  194 , a description is entered as to the current design or process control description in step  196  along with a particular current control category code in step  198 . One example of a control description is shown in FIG. 7B.  
         [0082]    The next section  200  is validation. Whether or not validation has been made is input in step  202 . The test method type is then input in step  204  from the following Table M:  
                         TABLE M                       Test Method Type                                    1. DV           2. PV           3. CC           4. Dimensional stack           5. Engineering calculation           6. FEA simulation           7. Prototype inspection           8. Pilot build inspector                      
 
         [0083]    The particular test specification and section number from the reference library is supplied in step  204 . Next, the particular validation test to be employed to validate the corrective action is input in step  206  from a list shown in the following Table N.  
                       TABLE N                                        1. Thermal soak            2. Thermal cycling            3. Random mechanical vibration            4. Mechanical shock            5. Thermal shock            6. Sinusoidal Mechanical vibration            7. Humidity soak            8. Humidity cycling            9. Fluids compatibility           10. EMI           11. EMC (electromagnetic compatibility)           12. ESD (electro-static discharge)           13. Voltage transients           14. Mechanical pull test           15. Life cycle (combined environments)           16. Electrical functionals           A-voltage           B-current           C-resistance           D-electric field strength           E-power           F-capacitance           G-inductance           H-frequency           I-impedance           17. Mechanical functionals           A-force           B-displacement           C-torque           D-mass           E-work           F-energy           G-horsepower           18. Illuminance functionals           A-Light intensity (CP)           B-Wavelength           19. Audible functionals           A-gain           B-frequency response                      
 
         [0084]    As shown by step  208  in FIGS. 4C and 7B, the next input is the current (PDCA) status in section  210 . An input is entered as to the open or closed status of the (PDCA) along with the (PDCA) open date and the (PDCA) close date.  
         [0085]    Finally, an initial cost of quality assessment is made in section  218 . A cost category description is entered in step  220  from the following Table O along with an estimate in step  222  of the quality costs.  
                       TABLE O                       Prevention Costs   Appraisal Costs   Failure Costs                   Design Reviews   Prototype Inspection-PP   Engineering Change Order-       Risk Assessment   Pilot Build Inspection-PP   PCR       Simulation-PCR   Product/process Verification   Redesign       Specification Review   Test-PP   Purchasing Change Order-PCR       Product Qualification   Incoming and Outgoing   Scrap (in process or EOLT)-       Drawing Checkout   Inspection   PCR       Process Control Plan   Measurement Evaluation and   Rework (in process or EOLT)-       Process Performance and   Test-PP   PCR       Capability Studies-PP   Process Control Acceptance   Warranty-PP       Tool and Equipment Studies-   Packaging Inspection   Extended Mileage-PP       PP   Supplier Audit-PP   Product Liability       Product Acceptance Planning   Company Manufacturing   Service       Product Assurance Planning   Audit-PP   Containment (Sort)-PP       Operator Training       Quality and Reliability       Training                          
 
         [0086]    Next, as shown in FIG. 6C for the FMEA module, the current design/process control sequence  90  is implemented. This sequence involves an input of the corrective function action description action in step  92  along with a code assigned to the particular action in step  93 . Next, the validation test method selected by product development group is selected from the test method list described above. The particular test specification and section number from the reference library is then input in step  95 . The test description, such as life cycle, for example only, is selected from the list shown in Table N. Next, a detection ranking is determined by the development group from the detection ranking criteria for designs in Table P or for processes in Table Q.  
                                                     TABLE P                           New DFMEA Detection Ranking Methodology (Design)       Location of Verification Method Activity per Valeo Structured Development Process                    Engineering   Development   Prototype   DV   Pilot Build   PV           Test Method   Simulation   Calculation   Testing   Inspection   Testing   Inspection   Testing       Characteristics   (Phase 2)   (Phase 2)   (Phase 2)   (Phase 2)   (Phase 2)   (Phase 3)   (Phase 3)   None               Validates* (with GRR)**,   1   2   3   4   4   5    6   10       high sample size, and       time non-terminated***       Validates (with GRR),   1   2   4   4   5   5    7   10       high sample size, and       time-terminated       Validates (with GRR),   1   2   4   5   5   6    7   10       low sample size, and       time non-terminated       Validates (with GRR),   1   2   5   5   6   6    8   10       low sample size, and       time-terminated       Validates w/o GRR,   N/A   N/A   6   6   7   7    9   10       high sample size, and       time non-terminated       Validate w/o GRR,   N/A   N/A   7   6   8   7    9   10       high sample size, and       time terminated       Validates w/o GRR,   N/A   N/A   7   7   8   8   10   10       low sample size, and       time non-terminated       Validates w/o GRR,   N/A   N/A   8   7   9   8   10   10       low sample size, and       time terminated                                                  
 
         [0087]    [0087]                                                     TABLE Q                           Process Determination       Location of Verification Method Activity per Valeo Structured Development Process                        Statistical                                       Process   Incoming                       Pre-Production   Control   Inspection   In-Process   In-Process               Demonstration   (Variable/   (Measured   Inspection   Inspection   EOL       Test Method   Simulation   Evaluation   Attribute)   &amp; Visual)   (Measured)   (Visual)   Testing       Characteristics   (Phase 3)   (Phase 2)   (Phase 4A)   (Phase 4B)   (Phase 4B)   (Phase 4B)   (Phase 4B)   None               Validates* (with GRR)**,   1   2   3   4   4   5    6   10       high sample size, and       time-terminated       Validates (with GRR),   1   2   4   4   5   5    7   10       high sample size, and       time-terminated       Validates (with GRR),   1   3   4   5   5   6    7   10       low sample size, and       time non-terminated       Validates (with GRR),   1   3   5   5   6   6    8   10       low sample size, and       time-terminated       Validates w/o GRR,   N/A   4   6   6   7   7    9   10       high sample size, and       time non-terminated       Validates w/o GRR,   N/A   4   7   6   8   7    9   10       high sample size, and       time terminated       Validates w/o GRR,   N/A   5   7   7   8   8   10   10       low sample size, and       time non-terminated       Validates w/o GRR,   N/A   5   8   7   9   8   10   10       low sample size, and       time terminated                                                    
         [0088]    With the detection ranking value, the final risk assessment can be made in section  97 . The total risk assessment number (RPN) is calculated by the equation (RPN=S×O×D) is then calculated in step  98 . The total risk assessment (RPN) can be compared with a threshold as shown in step  99  in FIG. 4D, such as  125  for example. Any values of (RPN) for a particular failure greater than this threshold can be used as an indication that the particular root cause does not reduce substantially the failure risk for the product. Control can be routed back to the (PDCA) section  18  for a determination of a new failure effect root cause.  
         [0089]    Finally, design control is transferred to (DFMEA) and process control to (PFMEA) for updating of part drawings or process control plans.