CHAPTER 4 FAILURE MODE AND EFFECTS ANALYSIS (FMEA) CASE STUDY

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1 55 CHAPTER 4 FAILURE MODE AND EFFECTS ANALYSIS (FMEA) CASE STUDY FMEA is a proactive analysis tool, allowing engineers to anticipate failure modes even before they happen, or even before a new product or process is released. It also helps the engineer to prevent the negative effects of these failure modes from reaching the customer, primarily by eliminating their causes and increasing the chances of detecting them before they can do any damage. The actions generated by a good FMEA cycle will also translate to better yield, quality, reliability and of course greater customer satisfaction. FMEA was being used around for a very long time. Before any documented format was developed, most of the inventors and process experts would try to anticipate what could go wrong with a design or process before it was developed. The trial and error alternative was both costly and time consuming. FMEA was formally introduced in the late 1940 s with the introduction of the military standard Being used for aerospace/rocket development, the FMEA was helpful in avoiding errors on small sample sizes of costly rocket technology. FMEA was encouraged in the 1960 s for space product development and served well on getting a man on the moon. Ford Motor Company reintroduced FMEA in the late 1970 s for safety and regulatory consideration. Ford Motor Company has used FMEA effectively for production improvement as well as design improvement.

2 56 The output of an FMEA cycle is the FMEA table, which documents how vulnerable a product or process is to its potential failure modes. The FMEA table also shows the level of risk attached to each potential failure mode, and the corrective actions needed (or already completed) to make the product or process more robust. The FMEA table generally consists of 16 to 17 columns, with each column corresponding to a piece of information required by FMEA. 4.1 PURPOSE OF FMEA The purpose of FMEA is to identify the different failures and modes of failure that can occur at the component, subsystem and system levels and to evaluate the consequences of these failures. FMEA is not a problem solver. It is used with problem solving tools. FMEA can be described as a systematic group of activities intended (i) (ii) (iii) to recognise and evaluate the potential failure of a product/ process and the effects of the failure. to identify action that could eliminate or reduce the chance of such potential failure occurring to document the entire process. 4.2 FMEA PREREQUISITES The prerequisites of FMEA are given below. (i) (ii) (iii) (iv) (v) Select proper team and organise members effectively. Select team for each product/services, process/system Create a ranking system Agree on format for FMEA Define the customer need

3 57 (vi) (vii) Design/process requirement Develop the process flow chart 4.3 UPDATING FMEA TABLE FMEA table is to be updated when (i) (ii) (iii) (iv) (v) (vi) a new product or process is being designed or introduced. a critical change in the operating conditions of the product or process occurs. the product or process itself undergoes a change a new regulation that affects the product or process customer complaints about the product or process are received an error in the FMEA table is discovered or new information that affects its contents comes to light. 4.4 BENEFITS OF FMEA FMEA is designed to assist the engineer to improve the quality and reliability of design. Properly used FMEA provides the engineer several benefits and they are given below. (i) (ii) (iii) (iv) (v) (vi) Improves product/process reliability and quality Increases customer satisfaction Helps for early identification and elimination of potential product/process failure Prioritises product/process deficiencies Captures engineering/organisation knowledge Emphasises problem prevention

4 58 (vii) (viii) (ix) (x) Documents risk and actions taken to reduce risk Provides focus for improved testing and development Minimises late changes and associated cost Serves as a catalyst for teamwork and idea exchange between functions. 4.5 KEY TERMS USED IN FMEA (i) Criticality Criticality rating is the mathematical product of severity and occurrence ratings. This number is used to place priority on items that require additional quality planning. (ii) Critical characteristics Critical characteristics are the special characteristics defined by Ford Motor Company that affect customers safety and/or could result in noncompliance with government regulations and thus require special controls to ensure 100% compliance. (iii) Causes A particular element of the design or process results in a failure mode, due to a cause. (iv) Failure mode Failure modes are sometimes described as categories of failure. A potential failure mode describes the way in which a product or process could fail to perform its function (design intent or performances requirement) as described by the needs, wants and expectations of internal and external customers.

5 59 (v) Severity Severity (S) is an assessment of how serious the effect of the potential failure mode is. A rating of 1 to 10 is chosen based on the severity. The severity ratings are given in the Table A2.1 in Appendix 2. (vi) Occurrence Occurrence (O) is an assessment of the likelihood that a particular cause will happen and result in failure mode during the life and use of a product. Occurrence rating is given from 1 to 10 which is to be chosen as given in the Table A2.2. (vii) Detection Detection (D) is an assessment of the likelihood that the current control (design and process) will detect the causes of failure mode or the failure mode itself, thus preventing it from reaching the customer. Detection rating of 1 to 10 is to be chosen as given in Table A2.3 in Appendix 2. (viii) Current control Current control (design and process) are the mechanisms that prevent the causes of failure mode from occurring, or which detect the failure before it reaches the customer. (ix) Risk Priority Number (RPN) The RPN is the mathematical product of the Severity (S), Occurrence (O) and Detection (D). RPN = S x O x D

6 CASE STUDY ON FMEA FMEA was carried out at an industry which is a leading manufacturer of Engine Valves. situated at Chennai, Tamilnadu, South India Process Flow Chart The process flow chart of an engine exhaust valve is shown in Figure A2.1. FMEA was carried out for the friction welding process of the engine exhaust valves Friction Welding Friction welding employs the heat produced due to friction welding and pressure to accomplish the fusion of materials. The basic operation is carried out by rotating one component and made to be in contact with the secondary component which is held stationary. Axial pressure is applied during the rotation which aids in generating heat. This process of pressurising and heating creates a bond at the interface of the two mating parts. It is significant that the metal at the interface does not melt, but rather becomes plastic. Welding heat is obtained at the joint by rotating one part against the other at a constant or varied RPM, with an axial force applied to the mating components. Energy is provided to this joint from a continuously running prime mover, directly connected to the machine spindle. This energy source is infinite with respect to time, and is supplied to the interface until the proper total heat is obtained. When this point is reached, the rotating member is stopped and a forging load is applied to the parts to be joined. Figure 4.1 shows the various components of a friction welding machine. The photograph of the friction welding machine that was used in this study is shown in Figure 4.2.

7 61 Figure 4.1 Components of a Friction Welding Machine Figure 4.2 Friction Welding Machine

8 Study of Key variables and process parameters The variables in friction welding process can essentially be divided into machine related variables and non-machine related variables. Nonmachine variables will include the material type to be welded and the part configuration and size. These variables like in any other welding process will determine the selection of welding parameters. The machine variables include friction and forge pressures, speed of rotation. The rotational speed and the pressure will control the ultimate quality of the weld. The rotational speed and pressure affect both the width and the shape of the heat-affected zone (HAZ). High pressures tend to compress the HAZ, especially at the center, heavily work the interfacial material and cause a notch effect at the junction. Higher speeds tend to increase the width of the HAZ and also the grain size. Subsequent use of high pressure forging after spindle stop is used to work the structure and refine the grain size. The parameters that can be selected and controlled will optimise the metallurgical condition. The process parameters of the friction welding process are soft force, soft force time, upset force, friction force, upset time, burn off, permissible shrinkage limit, slide home position, clamp open position and lube cycle Failure Report Failure reports of the various types of exhaust valves in passenger car line for two months have been collected and given in TableA2.4 and shown in Figure 4.3.

9 63 Figure 4.3 Various failure modes From the failure report it was observed that the majority of the failures are due to runout. Part Number has got the highest failure percentage. The prominent failure modes are weld crack and low tensile strength and part number has a production volume of more than 98% and hence part number was chosen for carrying out FMEA. Table 4.1 gives the specifications of the parts to be welded. Table 4.1 Specifications of the parts to be welded Structure Head Austenite 0.4 Composition in % C Si Mn Cr Ni P To 0.55 Stem Martensite 0.15 To To To 1.25 < To To 22 Dimensions in mm Before Friction Welding <0.6 <0.03 Dia To 12.5 Length-125 <0.04 Dia Length-63 Final Dimensio ns in mm Dia ±0.025 Length Failure modes and detection (i) Low tensile strength: The valve has to withstand a minimum tensile strength of 700N/mm 2. Tensile testing is

10 64 used to detect the tensile strength of the valves. For every lot of 1000 numbers, 7 valves are subjected to tensile testing. (ii) (iii) (iv) Runout: Runout is the out of roundness of valves. A tolerance limit of mm is set as threshold and the valve which exceeds the threshold is scraped. Runout is detected in the process by the operator by random checking. The defective valves that pass through friction welding are detected in centre less grinding process by 100% inspection. Both the inspections are carried out by v-block and dial gauge assembly. Weld crack: Ultrasonic testing is used to detect the weld crack in the weld zone. The rejected valves are kept separately and examined again. The valves which show discontinuation are scraped. Overall bar length: The bar length for the valve should be 181 mm after friction welding. The length is randomly checked by the operator. The defective valves which pass through friction welding are detected during loading of valve in upsetting machine Estimation of Severity Ranking The severity of each failure can be estimated by interpreting the failure mode and effect diagram with the suggested severity evaluation. The failure mode and effect diagram is given in Figure 4.4. The estimation of severity ranking was done using Table A2.1 and is given in Table 4.2.

11 65 SCRAP POOR WELDING REJECTION IN C`LESS UNFIT FOR OTHER OPERATION REJECTION IN UPSETTING LOW TENSILE STRENGTH H RUNOUT WELD CRACK OVERALL LENGTH LOW/HIGH Figure 4.4 Failure Mode and Effect Diagram Table 4.2 Estimation of Severity Ranking S.No. Failure mode Effect Severity Severity ranking 1. Runout Scrap (<100%) Moderate 6 2. Low tensile strength Scrap Very high 8 3. Weld crack Scrap Very high 8 4. Overall bar length low/high Scrap (<100%) Moderate Estimation of Occurrence Ranking The occurrence of each failure can be estimated by interpreting the Cause and effect diagram with the suggested PFMEA occurrence evaluation from Table A2.2. The causes for the failures were arrived by Brain storming

12 66 the people concerned with the process and the probable causes are shown in Figure 4.5 and Figure 4.6. MISALIGNMENT OF JAWS WORN OUT JAWS COLLET WEAROUT RUNOUT Figure 4.5 Causes for runout IMPROPER BURN OFF IMPROPER UPSET TIME IMPROPER UPSET FORCE IMPROPER FRICTION FORCE OVERALL BAR LENGTH LOW TENSILE STRENGTH WELD CRACK Figure 4.6 Causes for other failures Occurrence of Failures Occurrence is ranked by calculating the failure occurring per 1000 components and using the TableA2.2. The estimation of occurrence ranking is given in Table 4.3.

13 67 Table 4.3 Estimation of Occurrence Ranking S.No. Failure mode Occurrence/ 1000 valves 1. Runout 314/ = Low tensile strength 186/ = Weld crack 40/ = Overall bar length low/high 132/ = 0.95 Occurrence criteria Occasional Failure Occasional Failure Relatively Low Failure Relatively Low Failure Occurrence ranking Estimation of Detection Ranking Estimation of detection ranking was made using the detection ranking table given in Table A2.3. Table 4.4 gives the detection ranking of the failure mode based on the detection methods. Table 4.4 Estimation of Detection Ranking S.No. Failure mode Detection method 1. Runout Error is detected in multi stages 2. Low tensile strength Error is detected in subsequent operations 3. Weld crack 100% inspection at UT 4. Overall bar length low/high In station error detection Detection criteria Detection ranking High 3 Low 4 Moderate 5 Very high 2

14 Estimation of Risk Priority Number (RPN) The priority of the problems is articulated via Risk Priority Number (RPN). It is the product of occurrence, severity, detection. Risk Priority Number = Occurrence(O) x Severity(S) x Detection(D) The initial RPN for the failure modes have been calculated and are shown in Table 4.5, the details of which are given in Table A2.5. Table 4.5 Initial RPN Sl.No. Failure Mode RPN 1 Low Tensile strength Weld crack Run out Bar length low/high 36 From the above failure modes, since the RPN for the failure modes of low tensile strength, weld crack and run out were high, they were given priority and the cause and effect diagrams were prepared which are shown in Figures 4.7 to 4.9.

15 69 MAN MACHINE NOT FOLLOWING SOP OPERATOR SKILL HARDNESS VARIATION MICRO STRUCTURE VARIATION MATERIAL OIL TIME VARIATION LOAD CELL MALFUNCTIONING BAR MIX UP VARIATION METHOD SPINDLE SPEED VARIATION LOW CLAMPING IMPROPER UPSET FORCE IMPROPER FRICTION FORCE IMPROPER BURN OFF WELD CRACK IMPROPER SPINDLE SPEED Figure 4.7 Cause and Effect Diagram for weld crack

16 70 MAN MACHINE OPERATOR SKILL NOT FOLLOWING SOP SPINDLE SPEED VARIATION LOAD CELL MALFUNCTIONING LOW TENSILE STRENGTH HARDNESS VARIATION MICRO STRUCTURE VARIATION BAR MIX UP IMPROPER UPSET FORCE IMPROPER FRICTION FORCE IMPROPER BURN OFF MATERIAL METHOD Figure 4.8 Cause and Effect Diagram for low tensile strength

17 71 MAN VARIATION IN UPSET FORCE FC VALVE IN DEFLASH BAD FACEPLATE CONDITION MACHINE POOR AXES ALIGNMENT END STOPPER ROD WEAR AND TEAR IMPROPER GRIP OF MULTIBORE COLLET BY THE RUNOUT MULTI BORE COLLET WEAR PRECISION COLLET WEAR DEFLECTION UNIT SET LENGTH HIGH V BLOCK WEAR STEM AND HEAD HARDNESS VARIATION MATERIAL METHOD Figure 4.9 Cause and Effect Diagram for runout 4.7 REDUCTION OF RPN Tensile Strength and Weld Crack The reduction of RPN with respect to low tensile strength and weld crack can be achieved by optimising the process parameters. In order to optimise the process parameters, Design of Experiments (DOE) was used as explained below.

18 72 Upset force, friction force, burn off and spindle speed are the major causes of weld crack and low tensile strength. These parameters were optimised using 2 level DOE involving multiple factors. The experimental factors of the DOE are upset force, friction force, burn off length and spindle speed. The factors and the levels are shown in Table 4.6. Table 4.6 Factors and levels of DOE Factors/Levels Upset force (Tons) Friction force (Tons) Burn off (mm) Spindle speed (rpm) A B C D Experimental results Crack free micro structure, Tensile strength of minimum 700N/sq.mm and HAZ on head and stem are the response variables of the DOE. A full factorial DOE was carried out and the experimental results are shown in Table A Column effects method This approach was suggested by Taguchi as a simplified ANOVA to subjectively point out factors which have large influence on the response. The sum of the data associated with the first level is subtracted from the sum of the data associated with the second level for each column of the array. The magnitudes of the differences are compared to each other to find out the relatively large effects. The relative magnitudes indicate the relative power of

19 73 the factors in affecting the results. The strongest factors or interaction will have the largest differences. Table 4.7 shows the column effects analysis method summary. Looking at the difference row, factor B has the largest effect and considered as the most critical factor while the other factors have a moderate effect on the response. Considering tensile strength, weld crack and HAZ the selection of process parameters by Columns effects method is shown in Table 4.8. Table 4.7 Number of defects Trial No. A B C D No. of defects SUM SUM Difference

20 74 Table 4.8 Selection of process parameters by Column effects method Factors Level Parameter Upset force T Friction force T Burn off mm Spindle speed rpm Anaysis of Variance (ANOVA) ANOVA is a statistically based, objective decision making tool for detecting any differences in average performance of group of items tested. A sample of 30 valves was taken and the four way ANOVA was carried out for four factors A, B, C and D at two levels. The number of defects with respect to the factors and their levels are given in Table 4.9 and the summary of the four way ANOVA is given in Table Table 4.9 ANOVA Table indicating the defects Factors with their levels A 1 A 2 B 1 B 2 B 1 B 2 D C 1 D D C 2 D

21 75 Table 4.10 Four way ANOVA Table Factors Sum of Squares Degrees of Freedom Mean Sum of Squares F Percent Contribution A B C D A*B A*C A*D B*C B*D C*D A*B*C A*B*D A*C*D B*C*D Error Total Pooling up estimates of error values The pooling up strategy entails F-testing the smallest column effect against the next larger one to see if significance exists. If no significance exists, then these two effects are pooled together to test the next larger column effect until some significant F ratio exists.

22 76 Table 4.11 Pooling error variance ANOVA summary table Factors Sum of Squares Degrees of Freedom Mean Sum of Squares F Percent contribution B C*D B*C*D Error Total From Table 4.11, it is found that the factor A does not affect the final table and hence HAZ effect at level 2 is selected. B is the most critical factor of all and the interactions of C, D and B, C and D are also considered to be critical. The mean values of the occurrence of the defect for 30 valves under the combination of influential factors (B, C and D) are given in Table Table 4.12 Mean value of defects D 1 D 2 C B 1 C C B2 C The levels B 2, C 2 and D 1 give less mean value and hence these are selected. The optimised parameters are given in Table 4.13.

23 77 Table 4.13 Selection of process parameters by ANOVA Factors Level Parameter Upset force T Friction force T Burn off mm Spindle speed rpm Runout Causes for runout The various causes for runout were analysed by brain storming and the causes and the remarks are given in Table Table 4.14 Causes for runout Sl. No. Factor 1 Poor axes alignment in m/c Is it a significant cause for the defect? No Remarks Machine was tested by the manufacturer to ensure 2 V block wear No SOP says clearly about the frequency of change of V Block unit 3 Multi bore collet wear 4 Precision collet wear 5 End stopper rod wear and tear No No No SOP says clearly the frequency of change of Crawford Collet SOP says clearly the frequency of change of precision collet Stopper rod is reground properly in case of wear and tear

24 78 Table 4.14 (Continued) Sl. No. Factor 6 Bad face plate condition 7 Improper grip of multibore collet by the adaptor 8 Variation in upset force 9 Flow control valve at deflash unit 10 Deflection unit traverse high 11 Stem and head hardness variation Is it a significant cause for the defect? Yes Yes No No No No Remarks To be studied further To be studied further Machine is built with closed loop system There is a provision to avoid misuse. Periodical maintenance is carried out There is matching mark with which the limit switch is set to control the traverse length Receiving inspection is clear at the raw material stage by metallurgical lab 12 Operator Yes To be studied further From Table 4.14, it was identified that face plate wear, multi bore collet and operator may be the causes to be analysed and studied further Operator Five operators were studied to find out whether there is any significant difference in their ability to cause the runout and it was found that operator was not a major cause.

25 Face plate wear In order to find whether the wear of face plate is a significant cause for the failure, trials have been made with the worn out and new face plate. Table 4.15 and Table 4.16 give the details of the occurrence of the runout with a worn out face plate and with a new face plate respectively and it was found that face plate wear is not a major cause for runout. Table 4.15 Runout defects with a worn out face plate Trial No. Day Shift No. of defects No. of components produced 1 A B C A B C A B C Table 4.16 Runout defects with a new face plate Trial No. Day Shift No. of defects No. of components produced 1 A B C A B C A B C

26 Multi bore collet adaptor The multi bore collet and face plate assembly is shown in Figure To find whether the wear of the collet adaptor is a major cause for the runout, trials were made with a new adaptor and the runout defects are given in Table It was found that there is a considerable decrease in the number of defects by using a new adaptor. (a) (b) (c) Figure 4.10 Multi bore collet and face plate assembly (a) Multi Bore collet Adaptor (b) Multi Bore collet with face plate (c) Assembly of (a) and (b) Table 4.17 Runout defects with a new adaptor Sl. No. Day Shift Defects No. of components produced 1 A B C A B C

27 81 Table 4.17 (Continued) Sl. No. Day Shift Defects No. of components produced 7 A B C A B C A B C A B C Total IMPLEMENTATION AND REVIEW OF THE RECOMMENDED ACTIONS Tensile Strength and Weld Crack The recommended actions were incorporated and trials have been taken. A trial batch of valves of passenger car exhaust valve line was examined and the results of the implemented parameters are given in Table It was found that none of the valves was rejected due to micro crack in ultrasonic testing. The tensile strength was well over the limit of 700N/mm 2.

28 82 Table 4.18 Results of the implemented parameters Day Head HAZ Stem HAZ Tensile strength Weld crack Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil Runout The wornout collet adaptor was replaced with a new one and the spindle runout is below 100 micron. 4.9 IMPROVED RPN The improved occurrence ranking is shown in Table The details of improved RPN are given in Table A2.7. The comparison of the initial RPN and the improved RPN for the three failure modes is shown in Table 4.20.

29 83 Table 4.19 Improved Occurrence Ranking Sl. No. Failure Mode Occurrence per 1000 valves Occurrence Ranking Before After Before After 1 Runout Low Tensile Strength 1.34 Nil Weld crack 0.29 Nil 3 1 Table 4.20 Initial RPN and Improved RPN Sl.No. Failure Mode Initial RPN Improved RPN 1 Low Tensile strength Weld crack Run out