Designing Capable and Reliable Products Episode 4 pot

important. For example, tolerances on a dimension, a surface roughness require- ment or some intricate geometry on a component. These important characteristics need to be controlled and understood. The `quality' inherent in manufacturing a component is essentially dictated by the designer, and can be accounted for by the level of knowledge in the following design/manufacture interface issues: ± Process precision and tolerance capability, t p . ± Material to process compatibility, m p . ± Component geometry to process limitations, g p . ± Surface roughness and detail capability, s p . ± Surface engineering process suitability, k p . From consideration of these issues, risk indices can be formulated using charts to re¯ect the limits of variability set by the design which can be achieved by the application of best practice in manufacturing. The analysis ultimately returns a Component Manufacturing Variability Risk, q m . The underlying notion of q m is that an ideal design exists with regard to tolerance where the risk index is unity, indicating that variability is in control. Risk indices greater than unity exhibit a greater potential for variability during manufacture. Central to the determination of q m is the use of the process capability maps showing the relationship between the achievable tolerance and the characteristic dimension for a number of manufac- turing processes and material combinations. . Component Assembly Variability Risks Analysis ± Too often, assembly is overlooked when assessing the robustness of a design. DFA techniques oer the opportunity for part count reduction through a structured analysis of the assembly sequence, but they do not speci®cally address variability within assembly processes. A com- ponent's assembly situation involves the following process issues: ± Handling characteristics, h p . ± Fitting (placing and insertion) characteristics, f p . ± Additional assembly considerations (welding, soldering, etc.), a p . ± Whether the process is performed manually or automatically. Again, the notion is that an ideal component assembly design exists. Using expert knowledge, charts for a handling process risk, ®tting process risk and additional processes question the assembly situation of the component, accruing penalties if the design has increased potential for variability to return the Component Assembly Variability Risk, q a . . Eects of non-conformance ± The link between the component variability risks, q m and q a , and FMEA Severity (S) is made through the Conformability Map. Research into the eects of non-conformance and associated costs of failure has found that an area of acceptable design can be de®ned for a component character- istic on a graph of Occurrence versus Severity. It is possible to plot points on this graph and construct lines of equal failure cost. These isocosts in the non-safety critical region (FMEA Severity Rating 5) come from a sample of businesses and assume levels of cost at internal failure, returns from customer inspection or test and warranty returns. The isocosts in the safety critical region (FMEA Severity Rating >5) are based on allowances for failure investigations, legal actions and product recall, but do not include elements for loss of current or future business which can be considerable. The costs in the safety critical area have been more Objectives, application and guidance for an analysis 75 dicult to assess and have a greater margin of error. In essence, as failures get more severe, they cost more, so the only approach available to a business is to reduce the probability of occurrence. 2.6.1 Objectives CA is primarily a team-based product design technique that, through simple struc- tured analysis, gives the information required by designers to achieve the following: . Determine the potential process capability associated with the component and/or assembly characteristics . Assess the acceptability of a design characteristic against the likely failure severity . Estimate the costs of failure for the product . Specify appropriate C pk targets for in-house manufacturing or outside supply. 2.6.2 Application modes The case studies that follow have mainly come from `live' product development projects in industry. Whilst not all case studies require the methodology to predict an absolute capability, a common way of applying CA is by evaluating and com- paring a number of design schemes and selecting the one with the most acceptable performance measure, either estimated C pk , assembly risk or failure cost. In some cases, commercial con®dence precludes the inclusion of detailed drawings of the com- ponents used in the analyses. CA has been used in industry in a number of dierent ways. Some of these are discussed below: . Variability prediction ± A key objective of the analysis is predicting, in the early stages of the product development process, the likely levels of out of tolerance variation when in production. . Tolerance stack analysis ± Tolerances on components that are assembled together to achieve an overall design tolerance across an assembly can be individually analysed, their potential variability predicted and their combined eect on the overall conformance determined. The analysis can be used to optimize the design through the explorations of alternative tolerances, processes and materials with the goal of minimizing the costs of non-conformance. This topic is discussed in depth in Chapter 3. . Evaluating and comparing designs ± CA may be used to evaluate alternative concepts or schemes that are generated to meet the speci®cation requirements. It highlights the problem areas of the design, and calculates the failure cost of each, which acts as a measure of quality for the design. Since the vast majority of cost is built into a component in the early stages of the design process, it is advantageous to appraise the design as honestly and as soon as possible to justify choice in selecting a particular design scheme. . Requirements de®nition ± Where designers require tighter tolerances than normal, they must ®nd out how this can be achieved, which secondary processes/process 76 Designing capable components and assemblies developments are needed and what special control action is necessary to give the required level of capability. This must be validated in some way. The variability risks analysis described previously is useful in this connection. It provides systema- tic questioning of a design regarding the important factors that drive variability. It estimates quantities that can be related to potential C pk values, and identi®es those areas where redesign eort is best focused. The results serve as a good basis for component supplier dialogue, communicating the requirements that lead to a process capable design. . Generation mode ± The process capability knowledge used in CA to facilitate an analysis can be used in the early stages of product design to generate process capable dimensional tolerances and surface roughness values when the material and geometry eects are minimal. Similarly, the assembly charts can be used to generate an improved assembly by avoiding features known to exhibit high risk. 2.6.3 Analysis procedure The procedure is shown in ¯ow chart form in Figure 2.25. In order to obtain the best results, the following points should be clearly understood before starting to evaluate a component's manufacturing or assembly situation: . Read through Chapter 2 of this book carefully before attempting a design analysis. . It is important that the product development team be familiar with the main capabilities and characteristics of the manufacturing and assembly methods selected, as well as the materials considered, in order to obtain the full bene®t from the methodology. Technical and economic knowledge for some common manufacturing processes can also be found in Swift and Booker (1997). . The analysis requires the declaration of a sequence of assembly work, so familiarity with this supporting method is essential. . When analysing a component or assembly process, complete all columns of the Variability Risks Results Table (see later for an example) and write additional notes and comments in the results table whenever possible. The table is a con- venient means of recording the analysis for individual component manufacturing and assembly variability risks (q m , q a ). It is recommended that the results table provided is used every time the analysis is applied to minimize possible errors. . The Conformability Matrix (see later for an example) primarily drives assessment of the variability eects. The Conformability Matrix requires the declaration of FMEA Severity Ratings and descriptions of the likely failure mode(s). It is helpful in this respect to have the results from a design FMEA for the product. 2.6.4 Example ± Component Manufacturing Variability Risks Analysis Figure 2.26 shows the design details of a bracket, called a cover support leg. A critical characteristic is the distance from the hole centre to the opposite edge, dimension `A' Objectives, application and guidance for an analysis 77 Figure 2.25 Conformability Analysis procedure ¯owchart 78 Designing capable components and assemblies Figure 2.26 Component Manufacturing Variability Risks Analysis of a cover support leg Objectives, application and guidance for an analysis 79 on the bracket, which must be 50 Æ0: 5 mm to eectively operate in an automated assembly machine. The assembly machine is used to produce the ®nal product, of which the support leg is a key component. Failure to achieve this speci®cation would cause a major disruption to the production line due to factors including feeder jams, fastener insertion and securing. Through an analysis using CA, high material and geometry variability risks were highlighted which could reduce the ®nal capability of the characteristic. The Component Manufacturing Variability Risk, q m , for the characteristic is calculated to be q m  9, this being determined from the adjusted tolerance using the process capability map for bending, as shown. This gives a predicted process capability index, C pk  0:05. In fact, the component was already in production when it was realized that the dimensions on most of the components were out of tolerance. A process capability analysis of the manufacturing process was conducted, and the results are shown in Figure 2.27. The calculated process capability index was found to be C pk  0:03, from equation 3 in Appendix II, which relates to approximately half the components falling out of speci®cation, assuming a Normal distribution. C pk  j ÿL n j 3 2:14 µ = 49.575 mm = 49.5 mm σ = 0.861 mm =41 Superimposed Normal distribution 47 47.5 48 48.5 49 49.5 50 50.5 51 51.5 52 52.5 53 Frequency 12 10 8 6 4 2 0 Figure 2.27 Statistical process data for dimension `A' of the cover support leg 80 Designing capable components and assemblies where:   mean of distribution L n  nearest tolerance limit   standard deviation: Therefore: C pk  j49:575 ÿ49:5j 3 Â0:861  0:03 As a result of poor capability, a high level of machine downtime was experienced, and the company which manufactured the assembly machine were involved in an expen- sive legal dispute with their customer. Although a third party manufactured the cover support leg, liability, it was claimed, lay with the ®nal assembly machine manufac- turer. This resulted in severe commercial problems for the company, from which it never fully recovered. An analysis using CA at an early design stage would have highlighted the risks associated with using a spring steel and long unsupported sections in the design, which were the main tolerance reducing variabilities. With reference to the bending process capability map, the initial tolerance set at Æ0:5 mm was just within acceptable limits at a nominal dimension of 50 mm. However, the variability risks m p and g p decreased the probability of obtaining it substantially. Completing a variability risks table A variability risk table (as shown in Figure 2.28 for the cover support leg analysis above) is a more ecient and traceable way of presenting the results of the ®rst part of the analysis. A blank variability risks results table is provided in Appendix VII. It catalogues all the important design information, such as the tolerance placed on the characteristic, the characteristic dimension itself, surface roughness value, and then allows the practitioner to input the results determined from the variability risks analysis, both manufacturing and assembly. The documentation of the risks for each component and assembly operation follows the determination of the assembly sequence diagram, if appropriate, when the product consists of more than a single component. Every critical component characteristic or assembly stage is analysed through the use of the variability risks table. An assembly risk analysis will be performed during several of the case studies presented later. 2.6.5 Example ± Component Assembly Variability Risks Analysis Similar to the calculation of q m , it is possible to identify the variability risks associated with the assembly of components, q a . In the following example shown in Figure 2.29, a cover and housing (with a captive nut) are fastened by a ®xing bolt, which in turn is secured by a tab washer. For example, for assembly operation number 4 for the ®xing bolt we can determine the risk indices h p and f p . For the handling process, assuming automatic assembly, the Objectives, application and guidance for an analysis 81 Figure 2.28 Variability risks table for the cover support leg 82 Designing capable components and assemblies ®xing bolt is supplied in a feeder and does not have characteristics which complicate handling. Therefore, from the handling table in Figure 2.17, h p  1:0. Now assessing the ®tting to process risk, f p , from Figure 2.18: A (cannot be assembled the wrong way) A 1.0 B (no positioning reliance to process) B 1.0 C (automatic screwing) C 1.6 D (straight line assembly from above) D 1.2 E (single process ± one bolt in hole) E 1.1 F (no restricted access or vision) F 1.0 G (no alignment problems) G 1.0 H (no resistance to insertion) H 1.0 For the bolt ®tting operation: f p  A  B  C  D  E ÂF ÂG ÂH  2:11 The Component Assembly Variability Risk is given by: q a  h p  f p q a  1:0 Â2:11  2:11 Therefore, q a 4  2:11 However, once the cover, tab washer and bolt are in place an additional process is carried out on the washer to bend the tab. Thus from the additional assembly process Figure 2.29 Fixing bolt assembly and sequence of assembly Objectives, application and guidance for an analysis 83 Figure 2.30 Variability risks table for the ®xing bolt assembly 84 Designing capable components and assemblies [...]... tol2 and tol3 which may have been regarded as having acceptable Cpk values are shown to have costs of failure of greater than 10% and 0.2% respectively, due to the high Severity Rating …S† ˆ 8 for the potential failure modes in question Note that two additional failure modes are also illustrated 89 90 Designing capable components and assemblies Case studies Figure 2. 34 Hub analysis results 91 92 Designing. .. functional elements into a single piece and reduce assembly costs The design outline of the hub is shown in Figure 2. 34( a) together with an optical plate that is mounted on it Case studies Figure 2. 34( b) shows a line from the design FMEA related to the plastic moulded hub It gives the component function, the potential failure mode, the potential e€ects and potential causes of failure In addition,... companies, especially when the product has a high degree of interaction with the user 2.7 .4 Solenoid end assembly The following case study determines the manufacturing and assembly variability risks for a solenoid end assembly design, shown in Figure 2.39, and projects the potential 97 98 Designing capable components and assemblies Figure 2.39 Solenoid end assembly costs of failure associated with the... are analysed, they are not taken into account in the ®nal costs of failure In conclusion, the process capabilities Figure 2 .44 Solenoid end assembly redesign 103 1 04 Designing capable components and assemblies of several characteristics in this tolerance stack are inadequate and will not meet the customer's requirements consistently Solenoid end assembly redesign This is similar to the initial design,... Case studies Figure 2 .40 Solenoid end assembly initial design supplier) Also shown is a table describing the process used to manufacture each component and an assembly sequence diagram is given in Figure 2 .41 Referring back to Figure 2 .40 , the tolerance stack starts at face A on the fuel port and accumulates through the individual components to face B on the plunger seal 99 Figure 2 .41 Assembly sequence... ®xing bolt and bending of the tab washer operations will potentially be problematic on assembly, scoring assembly risk values greater than 2 The previous sections have illustrated the use of the various process risk charts and tables to obtain variability indices associated with the manufacture and assembly of products It is important to be systematic with the application of the methodology and the recording... Cpk values can also be written in the variability risks results table Objectives, application and guidance for an analysis Figure 2.33 Conformability matrix example 87 88 Designing capable components and assemblies Example ± determining the failure costs for product design We will now consider calculating the potential costs of failure in more detail for the cover support leg shown earlier The process... requirements and will inevitably present problems using Case studies Figure 2.35 Cover assembly design analysis 93 94 Designing capable components and assemblies either manual or automatic assembly operations Looking to the O-ring, a better design would be to eliminate it altogether and integrate the seal with the wire as shown in Figure 2.36 The wire is then positively located with the seal in the... Matrix, and represent the levels of design acceptability obtained with reference to the Conformability Map given in Figure 2.22 The link with FMEA brings into play the additional dimension of potential variability into the assessment of the failure modes and the e€ects on the customer The Conformability Matrix also highlights those `bought-in' components and/ or assemblies that have been analysed and found... to 4 Æ 0:08 mm (tol2 ), the dimensional tolerance on the faces to 1 Æ 0:07 mm (tol3 ) and the depth to 10 Æ 0:12 mm (tol4 ) Also, the thin sections of the hub gave two geometrical concerns as these vanes were on the limits of plastic ¯ow and distortion was likely on cooling The results of the analyses carried out by the business on the hub are given in the variability risks table shown in Figure 2. 34( c) . Normal distribution. C pk  j ÿL n j 3 2: 14 µ = 49 .575 mm = 49 .5 mm σ = 0.861 mm =41 Superimposed Normal distribution 47 47 .5 48 48 .5 49 49 .5 50 50.5 51 51.5 52 52.5 53 Frequency 12 10 8 6 4 2 0 Figure 2.27 Statistical. cover support leg 80 Designing capable components and assemblies where:   mean of distribution L n  nearest tolerance limit   standard deviation: Therefore: C pk  j49:575 49 :5j 3 Â0:861 . assembly and sequence of assembly Objectives, application and guidance for an analysis 83 Figure 2.30 Variability risks table for the ®xing bolt assembly 84 Designing capable components and assemblies table