24 Component Assembly Variability Risks Analysis

In the development of the assembly variability risks analysis, expert knowledge, data found in many engineering references and information drawn from the CSC DFA/MA practitioner's manual (CSC Manufacturing, 1995) were collated and issues related to variability converged on. Much of the knowledge for the additional assembly variability risks analysis was reviewed from the fabrication and joining data sheets called PRocess Information MAps (PRIMAs) as given in Swift and Booker (1997).

Product assembly is such a large area that focusing on the key operational issues, such as handling, fitting and joining, is justified at the design stage. Although much has been written about DFA, it was not appropriate to use the DFA indices directly for these assembly operations because they are based on relative cost, not potential variability. Where the knowledge and data cannot help, and where some of the more qualitative aspects of design commence, as well as expert knowledge, some Poka Yoke ideas were used, particularly for the component fitting chart. Poka Yoke is used to prevent an error being converted into a defect (Shingo, 1986). It is heavily involved in the development of any DFA process. Poka Yoke has two main steps: preventing the occurrence of a defect, and detecting a defect (Dale and McQuater, 1998). Some of the assembly variability risks charts reflect these Poka Yoke philosophies.

The measure of assembly variability, qa, derived from the analysis should be used as a relative performance indicator for each design evaluated. The design with the least potential variability problems or least failure cost should be chosen for further development. The indices should not be taken as absolutes as assembly variability is difficult to measure and validate.

The component assembly variability risk, qa, as determined by CA, attempts to better understand the affects of the assembly situation on variability by quantifying the risks that various operations inherently exhibit. A component's assembly situation typically involves the following process issues:

• Handling characteristics, hp

• Fitting (placing and insertion) characteristics, fp

• Additional assembly considerations (welding, soldering, etc.), ap

• Whether the process is performed manually or automatically.

At the current stage of development, the risk index associated with component assembly variability is the product of the component's handling and fitting risks:

The additional assembly process risk, ap, is considered in isolation after the handling and fitting operations, questioning the assembly situation of a component after initial placing, and which requires further processing, for example welding or adhesive bonding. Therefore, because additional assembly processes are performed after initial part placement, qa simply defaults to ap when it is considered in the assembly sequence:

The additional assembly processes covered in the analysis are provided in Appendix VI, and are listed below:

• Miscellaneous operations (testing, reorientation, heating, cooling)

• Later mechanical deformation (riveting)

• Adhesive bonding

• Brazing and soldering

• Resistance welding

A systematic assessment is made of every handling and fitting process involved in the product construction (manual or automated), including the effects of alignment, placement and fastening, through the assembly sequence diagram for the design. A number of charts are used for each aspect of the assembly analysis. Using the handling process risk chart (see Figure 2.17), the fitting process risk (Figure 2.18) and the additional process risk charts, the assembly situation for most components can be analysed, accruing penalties if the design has increased potential for variability. The measure of variability returned is the component assembly variability risk, qa. Guidance notes accompany each chart for the designer.

The assembly indices are bounded in the same way as the component manufacturing variability risk indices, qm. Starting with the notion that an ideal component assembly situation exists, this risk index is given a value of unity. The indices are then scaled within the same conditions described for tp (used in the manufacturing variability risks analysis). For example, 1.7 < hp < 2.2 indicates that the handling process is within special control. High values of qa indicate high-risk design to process solutions. The estimated values of qa tend to be within the range 1 to 5, with only those components where the risk is exceptionally high coming out beyond 5. Where detailed knowledge and experience of a particular assembly situation is available,

_EJ SENSITIVITY

TECHNOLOGY ^^

DELICATE lit

SENSITIVE TO TEMPERATURE CHANGE

SENSITIVE TO CONTAMINATION

NOT APPLICABLE

O)

Chemical (2)

Mechanical

MANUAL HANDLING i. «HIPPING

Nal thin/ small (4)

1 3

1.2

1.5

1.1

1.0

Thiiiysmall

1.7

1.3

2.0

f.2

1.0

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No-g ripping

1.2

1.1

1.2

1,1

1.0

II

No! thin

14

1.1

1 2

1.3

1.0

Thin

1.6

1.3

1.2

1.4

1.0

Vacuum/ Magnetic contad

1 2

1.3

1.2

13

"O

as

No gripping

1 5

1.1

1.2

1.5

1.0

Gripping

Si? s «

Not Ihin

1.9

1.2

1.3

1.7

1 .0

w ■ 1

Thin

2.2

1.3

1.3

1.«

Z> <

Vacuum/ magnetic contad

1.6

1 3

1.3

1.8

1.0

O

No gripping

1.2

1.1

1.2

1.2

1.0

Sä a 5 u

Not Ihin

1.5

1 2

1.5

1.7

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2.2 j 1.3

1.5

1.8

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Vacuum/ magnelic contact

1 .3

1.3

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® Also includes high finish.

® Chemical contamination to operator/machine or product. ® If component is not sensitive to the characteristics listed, hp = 1.0. ® A component is said to be thin if one of its major dimensions is <0.25 mm thick. © Includes mechanical and air assisted mechanisms.

Notes

® Also includes high finish.

® Chemical contamination to operator/machine or product. ® If component is not sensitive to the characteristics listed, hp = 1.0. ® A component is said to be thin if one of its major dimensions is <0.25 mm thick. © Includes mechanical and air assisted mechanisms.

Figure 2.17 Handling process risk, hp this expertise should be used to augment the analysis. Because the assembly variability knowledge collated is a mixture of quantitative and qualitative data, validation of the indices used in the charts is more difficult than the manufacturing variability risks analysis. Experts from the assembly industry were therefore used in their final assessment and allocation. However, despite the fact that the validation of the assembly capability measures are difficult to determine empirically, they are found to be of great benefit when comparing and evaluating a number of design principles.

Designing capable components and assemblies I START I

Key to values: AUTOMATED (MANUAL)

Can it be assembled the wrong way round? (1)

No vT

D Is there reliance on the process to achieve accurate positioning? (2)

Operator control Positional tolerance 0.1mm using automation

Part placing process (3)

Self- Requires holding to maintain sustained correct orientation orientation

Parts fastening process (4)

QUT7

Easy

Difficult

Self-securing

Screwing

Blind riveting

Plastic bending

Process direction?

Straight line Straight line Not straight from above (5) not from line (7) above (6) q

Single

Multiple process

Simultaneous process (8)

"0" ^^ j^j 1.0(1.0) 1.1(1.0) 1.3(1.1) 1.7(1.9) 1.2(1.1)

Is the component difficult to align during assembly? (9)

0 0

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