11 Statement of the problem

In order to improve business performance, manufacturing companies need to reduce the levels of non-conformance and attendant failure costs stemming from poor product design and development. Failure costs generally make up the largest cost category in a manufacturing business and include those attributable to rework, scrap, warranty claims, product recall and product liability claims. This represents lost profit to a business and, as a result, it is the area in which the greatest improvement in competitiveness can be made (Russell and Taylor, 1995).

The effect of failure cost or 'quality loss' on the profitability of a product development project is shown in Figure 1.1. High levels of failure cost would produce a loss on sales and would probably mean that the project fails to recover its initial level of investment.

In an attempt to combat high quality costs and improve product quality in general, companies usually opt for some kind of quality assurance registration, such as with BS EN ISO 9000. Quality assurance registration does not necessarily ensure product quality, but gives guidance on the implementation of the systems needed to trace and control quality problems, both within a business and with its suppliers. The adoption of quality standards is only the first step in the realization of quality products and also has an ambiguous contribution to the overall reduction in failure costs. A more proactive response by many businesses has been to implement and support long-term product design and development strategies focusing on the engineering of the product.

It has been realized for many years that waiting until the product is at the end of the production line to measure its quality is not good business practice (Crosby, 1969). This has led to an increased focus on the integration of quality into the early design stages of product development (Evbuomwan et al., 1996; Sanchez, 1993). Subsequently, there has been a gradual shift away from the traditional 'on-line' quality techniques, such as Statistical Process Control (SPC), which has been the main driver for quality improvement over the last 50 years, to an 'off-line' quality approach using design tools and techniques.

Figure 1.1 Effect of quality loss on the profitability of a product development project

The focus on quality improvement in design is not misplaced. Studies have estimated that the majority of all costs and problems of quality are created in product development. Focusing on the generation of product faults in product development, we find that typically 75% originate in the development and planning stages, but compounding the problem, around 80% of faults remain undetected until final test or when the product is in use (see Figure 1.2). The consequences of a design fault can be crippling: massive recalls, costly modifications, loss of reputation and sales, or even going out of business! Engineers and designers sometimes assume that someone else is causing product costs, but it is the details of how a product is designed that generates its costs in nearly every category (Foley and Bernardson, 1990).

The most significant cost savings can result from changes in product design rather than, say, from changes in production methods (Bralla, 1986). The costs 'fixed' at the planning and design stages in product development are typically between 60 and 85%, but the costs actually incurred may only be 5% of the total committed for the project. Therefore, the more problems prevented early on, through careful design, the fewer problems that have to be corrected later when they are difficult and expensive to change (Dertouzos et al., 1989). It is often the case that quality can be 'built in' to the product without necessarily increasing the overall cost (Soderberg, 1995). However, to achieve this we need to reduce the 'knowledge gap' between design and manufacture as illustrated in Figure 1.3.

Design is recognized as a major determinant of quality and therefore cost. It is also a driving factor in determining the 'time to market' of products (Welch and Dixon, 1992). Historically, designers have concerned themselves with product styling, function and structural integrity (Craig, 1992). Now the designer has the great responsibility of ensuring that the product will conform to customer requirements,

Figure 1.2 Origination and elimination of faults in product development (DTI, 1992)

comply to specification, meet cost targets and ensure quality and reliability in every aspect of the product's use, all within compressed time scales.

From the above, it is clear that the designer needs to be aware of the importance of the production phase of product development. As far as quality is concerned, the designer must aim to achieve the standards demanded by the specification, but at the same time should be within the capabilities of the production department. Many designers have practical experience of production and fully understand the limitations and capabilities that they must work within. Unfortunately, there are also many who do not (Oakley, 1993). From understanding the key design/manufacture interface issues, the designer can significantly reduce failure costs and improve business competitiveness. One of the most critical interface issues in product development is that concerning the allocation of process capable tolerances.

There is probably no other design improvement effort that can yield greater benefits for less cost than the careful analysis and assignment of tolerances (Chase and Parkinson, 1991). The effects of assigning tolerances on the design and manufacturing functions are far reaching, as shown in Figure 1.4. Product tolerances affect customer satisfaction, quality inspection, manufacturing and design, and are, therefore, a critical link between design, manufacture and the customer (Gerth, 1997; Soderberg, 1995). They need to be controlled and understood!

Each product is derived from individual pieces of material, individual components and individual assembly processes. The properties of these individual elements have a probability of deviating from the ideal or target value. In turn, the designer defines allowable tolerances on component characteristics in anticipation of the manufacturing variations, but more often than not, with limited knowledge of the cost

Figure 1.3 Commitment and incursion of costs during product development and the 'knowledge gap' principle (adapted from Fabrycky, 1994)

implication or manufacturing capability in order to meet the specification (Craig, 1992; Korde, 1997). When these variations are too large or off target, the usability of the product for its purpose will be impaired (Henzold, 1995). It therefore becomes important to determine if a characteristic is within specification, and, if so, how far it is from the target value (Vasseur et al., 1992).

Improperly set tolerances and uncontrolled variation are one of the greatest causes of defects, scrap, rework, warranty returns, increased product development cycle time, work flow disruption and the need for inspection (Gerth and Hancock, 1995). If manufacturing processes did not exhibit variation, quality problems would not arise, therefore reducing the effects of variability at the design stage, in a cost-effective way, improves product quality (Bergman, 1992; Kehoe, 1996).

A significant proportion of the problems of product quality can directly result from variability in manufacturing and assembly (Craig, 1992). However, the difficulties associated with identifying variability at the design stage mean that these problems are detected too late in many cases, as indicated by a recent study of engineering change in nine major businesses from the aerospace, industrial and automotive sectors (Swift et al., 1997). On average, almost 70% of product engineering rework was due to quality problems, that is failure to satisfy customer expectations and to

Figure 1.4 Tolerances - the critical link between design and manufacture (Chase and Parkinson, 1991)

anticipate production variability on the shop floor. The need for more than 40% of the rework was not identified until production commenced.

The reasons for the rework, described in Figure 1.5, can be classified into four groups:

• Customer driven changes (including technical quality)

• Engineering science problems (stress analysis errors, etc.)

• Manufacturing/assembly feasibility and cost problems

• Production variability problems.

This indicates that customer related changes occurred throughout concept design, detailing, prototyping and testing with some amendments still being required after production had began. Engineering science problems, which represented less than 10% of the changes on average, were mostly cleared before production commenced. The most disturbing aspect is the acceptance by the businesses that most of the manufacturing changes, and more so manufacturing variability changes, were taking place during production, product testing and after release to the customer. Because the cost of change increases rapidly as production is approached and passed, the expenditure on manufacturing quality related rework is extremely high. More than 50% of all rework occurred in the costly elements of design for manufacture and production variability.

Further evidence of the problems associated with manufacturing variability and design can be found in published literature (Lewis and Samuel, 1991). Here, an investigation in the automotive industry showed that of the 26 quality problems stated, 12 resulted from process integrity and the integrity of assembly. Process integrity was defined as the correct matching of the component or assembly design to either the current manufacturing process or subsequent processes. Integrity of assembly was defined as the correct matching of dimensions, spatial configuration of adjacent or interconnecting components and subassemblies.

Variability associated with manufacturing and assembly has historically been considered a problem of the manufacturing department of a company (Craig,

Figure 1.5 Disposition of rework in product development (Swift etal., 1997)

Concept Detail Production

Figure 1.5 Disposition of rework in product development (Swift etal., 1997)

1992). It is now being recognized that there is a need to reduce such variations at the design stage, where its understanding and control may lead to (Leaney, 1996a):

• Easier manufacture

• Improved fit and finish

• Less work in progress

• Reduced cycle time

• Fewer design changes

• Increased consistency and improved reliability

• Better maintainability and repairability.

Variation is an obvious measure for quality of conformance, but it must be associated with the requirements set by the specification to be of value at the design stage. Unfortunately, difficulty exists in finding the exact relationship between product tolerance and variability. Approximate relationships can be found by using process capability indices, quality metrics which are interrelated with manufacturing cost and tolerance (Lin et al, 1997)*.

The first concern in designing process capable products is to guarantee the proper functioning of the product, and therefore to satisfy technical constraints. Dimensional

• It is recommended at this stage of the text that the reader unfamiliar with the basic concepts of variation and process capability refer to Appendix I for an introductory treatise on statistics, and Appendix II for a discussion of process capability studies.

characteristics reflect the spatial configuration of the product and the interaction with other components or assemblies. Tolerances should be allocated to reflect the true requirements of the product in terms of form, fit and function in order to limit the degradation of the performance in service (Kotz and Lovelace, 1998). Ideally, designers like tight tolerances to assure fit and function of their designs. All manufacturers prefer loose tolerances which make parts easier and less expensive to make (Chase and Parkinson, 1991).

Tolerances alone simply do not contain enough information for the efficient manufacture of a design concept and the designer must use process capability data when allocating tolerances to component characteristics (Harry and Stewart, 1988; Vasseur et al., 1992). Process capability analysis has proven to be a valuable tool in this respect, and is most useful when used from the very beginning of the product development process (Kotz and Lovelace, 1998).

If the product is not capable, the only options available are to either: manufacture some bad product, and sort it out by inspection; rework at the end of the production line; narrow the natural variation in the process; or widen the specification to improve the capability. Post-production inspection is expensive and widening the specification is not necessarily desirable in some applications as this may have an impact on the functional characteristics of the product. However, in many cases the tolerance specification may have been set somewhat arbitrarily, implying that it may not be necessary to have such tight tolerances in the first place (Kotz and Lovelace, 1998; Vasseur et al., 1992). Making the product robust to variation is the driving force behind designing capable and reliable products, lessens the need for inspection and can reduce the costs associated with product failure.

Variability must become the responsibility of the designer in order to achieve these goals (Bjorke, 1989). An important aspect of the designer's work is to understand the tolerances set on the design characteristics, and, more importantly, to assess the likely capability of the characteristics due to the design decisions.

Industry is far from understanding the true capability of their designs. Some comments from senior managers and engineers in the industry give an indication of the cultural problems faced and the education needed to improve design processes in this respect.

We will have difficulty meeting those tolerances - it is 'bought-in' so we'll get the supplier to do the inspection.

Cpk = 1.33! We do much better than that in the factory. We're down to Cpk = 0.8!

I don't see how we make this design characteristic at Cpk = 1.5. Let's kill it with 100% inspection.

The components are not going to be process capable, but we can easily set the tolerance stack at ±0.1 mm when we build the assembly machine. Our assembly machine supplier uses robots.

I can see that this design is not likely to be capable, but my new director has said we are to use this design solution because it has the lowest part count. I can't spend any more time on design. I see the problems, but it will cost the department too much if I have to modify the design.

I have been told that we must not use any secondary machining operations to meet the tolerance requirements. It just costs too much!

Good design practice does not simply mean trying to design the product so that it will not fail, but also identifying how it might fail and with what consequences (Wright, 1989). To effectively understand the quality of conformance associated with design decisions requires undertaking a number of engineering activities in the early stages of product development. In addition to understanding the capability of the design, the designer must consider the severity of potential failures and make sure the design is sufficiently robust to effectively eliminate or accommodate defects. Effective failure analysis is an essential part of quality and reliability work, and a technique useful in this capacity is Failure Mode and Effects Analysis (FMEA). (See Appendix III for a discussion of FMEA, together with several key tools and techniques regarded as being beneficial in new product development.)

FMEA is a systematic element by element assessment to highlight the effects of a component, product, process or system failure to meet all the requirements of a customer specification, including safety. FMEA can be used to provide a quantitative measure of the risk for a design. Because FMEA can be applied hierarchically, through subassembly and component levels down to individual dimensions and characteristics, it follows the progress of the design into detail listing the potential failure modes of the product, as well as the safety aspects in service with regard to the user or environment. Therefore, FMEA provides a possible means for linking potential variability with consequent design acceptability and associated failure costs. The application of a technique that relates design capability to potential failure costs incurred during production and service would be highly beneficial to manufacturing industry.

Conceivably, a number of new issues in product design and development have been discussed in this opening section, but in summary:

• Understanding and controlling the variability associated with design characteristics is a key element of developing a capable and reliable product

• Variability can have severe repercussions in terms of failure costs

• Designers need to be aware of potential problems and shortfalls in the capability of their designs

• There is a need for techniques which estimate process capability, quantify design risks and estimate failure costs.

Next, we review the costs of quality that typically exist in a manufacturing business, and how these are related to the way products fail in service. The remainder of the chapter discusses the important elements of risk assessment as a basis for design. This puts in context the work on designing for quality and reliability, which are the main topics of the book.

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