12 The costs of quality

The costs of quality are often reported to be between 5 and 30% of a company's turnover, with some engineering businesses reporting quality costs as high as 36%

Unsure 17%

Failure costs

Prevention costs 18%

Unsure 17%

Prevention costs 18%

Failure costs

Appraisal costs 25%

Appraisal costs 25%

Figure 1.6 The costs of quality in UK industry (Booker, 1994)

(Dale, 1994; Kehoe, 1996; Maylor, 1996). This figure can be as high as 40% in the service industry! (Bendell et al., 1993). In general, the overall cost of quality in a business can be divided into the following four categories:

• Prevention costs - These are costs we expect to incur to get things right first time, for example quality planning and assurance, design reviews, tools and techniques, and training.

• Appraisal costs - Costs which include inspection and the checking of goods and materials on arrival. Whilst an element of inspection and testing is necessary and justified, it should be kept to a minimum as it does not add any value to the project.

• Failure costs - Internal failure costs are essentially the cost of failures identified and rectified before the final product gets to the external customer, such as rework, scrap, design changes. External failure costs include product recall, warranty and product liability claims.

• Lost opportunities - This category of quality cost is impossible to quantify accurately. It refers to the rejection of a company product due to a history of poor quality and service, hence the company is not invited to bid for future contracts because of a damaged reputation.

Up to 90% of the total quality cost is due to failure, both internal and external, with around 50% being the average (Crosby, 1969; Russell and Taylor, 1995; Smith, 1993). A survey of UK manufacturing companies in 1994 found that failure under the various categories was responsible for 40% of the total cost of quality, followed by appraisal at 25%, and then prevention costs at 18%. This is shown in Figure 1.6. Of the companies surveyed, 17% were unsure where their quality costs originated, but indicated that these costs could be attributable to failure, either internally or externally.

Many organizations fail to appreciate the scale of their quality failures and employ financial systems which neglect to quantify and record the true costs. In many cases, the failures are often costs that are logged as 'overheads'. Quality failure costs represent a direct loss of profit! Organizations may have financial systems to recognize scrap, inspection, repair and test, but these only represent the 'tip of the iceberg' as illustrated in Figure 1.7.

A company should minimize the failure costs, minimize appraisal costs, but be prepared increase investment on prevention. Some quality gurus promote the philosophy of zero defects. Whilst this is obviously the ultimate goal, the prevention costs can become prohibitive. It is possible to determine the optimum from a cost point of view. This value may not be constant across the different business sectors, for instance a machine shop may be prepared to accept a 1% scrap rate, but it is doubtful that the public would accept that failure rate from a commercial aircraft! Each must set its own objectives, although 4% has been stated in terms of a general target as a percentage of total sales for manufacturing companies (Crosby, 1969). A simple quality-cost model that a business can develop to define an optimum between quality of conformance and cost is illustrated in Figure 1.8.

1.2.1 Cases studies in failure costs

External failure costs and lost opportunities are potentially the most damaging costs to a business. Several examples commonly quoted in the literature are given below.

This first example applies to UK industry in general. The turnover for UK manufacturing industry was in the order of £150 billion in 1990 (Smith, 1990). If the total quality cost for a business was likely to be somewhere in the region of 20%, with failure costs at approximately 50% of the total, it is likely that about £15 billion was wasted in defects and failures. A 10% improvement in failure costs would have released an estimated £1.5 billion into the economy. IBM, the computer manufacturer, estimated that they were losing about $5.6 billion in 1986 owing to costs of non-conformance and its failure to meet quality standards set for its products and

Figure 1.8 The optimization of quality costs

services. A further $2 billion was estimated as being lost as a result of having poor working processes. IBM proceeded on the basis that the company had $7.6 billion of potential savings to be obtained getting things 'right first time' (Kruger, 1996).

In the US over the last 30 years, there has been an increasing trend in product liability claims and associated punitive damages. For example, after a legal battle, General Motors had to pay a plaintiff's family $105 million, when the plaintiff was killed when a poorly positioned petrol tank in a truck exploded during an accident (Olson, 1993). The UK motorcycle industry in the 1970s suffered greatly due to their Japanese counterparts not only producing more cost-effective bikes, but also of higher quality. The successful resurgence of Triumph only recently was based on matching and even bettering the Japanese on the quality of it products.

Most producers believe in the adage 'quality pays' in terms of better reputation and sales, customer loyalty, lower reject rates, service and warranty costs. They should also realize that 'safety pays' in terms of reducing the legal exposure and the tremendous costs that this can incur, both directly and indirectly, for example from compensation, legal fees, time and effort, increased insurance premiums, recalls and publicity (Wright, 1989). Few manufacturers understand all the cost factors involved, and many take a shortsighted view of the actual situation with regard to the costs of safety.

Measures to minimize safety problems must be initiated at the start of the life cycle of any product, but too often determinations of criticality are left to production or quality control personnel who may have an incomplete knowledge of which items are safety critical (Hammer, 1980). Any potential non-conformity that occurs with a severity sufficient to cause a product or service not to satisfy intended normal or reasonably foreseeable usage requirements is termed a 'defect' (Kutz, 1986). The optimum defect level will vary according to the application, where the more severe the consequences of failure the higher the quality of conformance needs to be.

The losses that companies can face are influenced by many factors including market sector, sales turnover and product liability history. It is not easy to make a satisfactory estimate of the product liability costs associated with quality of non-conformance, and

Figure 1.9 US tort cost escalation compared with GNP growth (Sturgis, 1992)

losses due to safety critical failures in particular are subject to wide variation (Abbot, 1993).

It is known that product liability costs in the US have risen rapidly in recent years and this trend is set to continue. It has been predicted that US tort costs would reach $300 billion by the year 2000, which would then represent 3.5% of US economic output (Sturgis, 1992). Tort is a term used in common law for a civil wrong and for the branch of law dealing with the liability for these wrongs. It is an alleged wrongful act for which the victim can bring a civil action to seek redress. Examples of individual torts are negligence, nuisance, and strict liability. Tort cost growth far outstripped Gross National Product (GNP) growth since 1930, increasing 300 times over this period, as shown in Figure 1.9, compared with a 50-fold increase for GNP.

The way in which tort costs are moving provides valuable evidence of the costs of 'getting it wrong' (Sturgis, 1992). Product liability experts believe that while the US system has its differences, as lawyers in the UK become more attuned to the US system, a similar situation may occur here also. Some background to the situation in the UK is shown in Figure 1.10, indicating that product liability costs could reach £5 billion annually. A further escalation in product liability claims could result in higher insurance premiums and the involvement of insurance companies in actually defining quality and reliability standards and procedures (Smith, 1993).

Insurance appears to be the safest solution for companies to defend themselves against costly mistakes, but there are problems, notably the cost of the premiums and the extent of the cover provided (Wright, 1989). The insurance sector must address some of the above issues in assessing their exposure (Abbot, 1993). Case histories provide some insight into the costs that can accrue though.

For a catastrophic failure in the aerospace industry with a high probability of loss of life, which relates to an FMEA Severity Rating (S) = 10, a business could quite possibly need insurance cover well in excess of £100 million. This will allow for costs due to failure investigations, legal actions, product recall and possible loss of

business. High failure costs are not only associated with the aerospace industry. Discussions relating to the automotive sector suggest that for a failure severity of S = 9, complete failure with probable severe injury and/or loss of life, a business could well face the need for cover in excess of £10 million. Less safety critical business sectors and lower severity ratings reduce the exposure considerably, but losses beyond £1 million have still been recorded (Abbot, 1993). The relationship between safety critical failures and potential cost is summarized in Figure 1.11. It is evident that as failures become more severe, they cost more, so the only approach available to the designer is to reduce the probability of occurrence.

Little progress towards reducing product liability exposure can be made by individuals within a business unless top management are committed to marketing safe products. Safety is one aspect of the overall quality of a product. While most producers and suppliers realize the importance of quality in terms of sales and reputation, there is sometimes less thought given to the importance of safety in terms of legal liabilities. Where 'quality' is mentioned it should be associated with 'safety'. Management strategy should be based on recognizing the importance of marketing a safe product, and the potential costs of failing to do so, and that failures will occur and plans must be made for mitigating their effect (Wright, 1989).

1.2.2 Quality-cost estimating methods

Quality-cost models can help a business understand the influence of defect levels on cost during product development. More importantly, designers should use models to predict costs at the various stages. These results make the decisionmaking process more effective, particularly at the design stage (Hundal, 1997). The estimation of quality costs in the literature is commonly quoted at three quite different levels:

1000

1000

FMEA Severity (S)

Figure 1.11 The potential cost of safety critical failures

• Economic quality-cost models which are 'global' or 'macro-scaling' top down methods, show general trends in quality costs which are predicted based on varying some notion of time or quality improvement. The model in the latest standard BS6143, as shown in Figure 1.12, is such a model. It is perhaps closest to the view of some quality experts, but surprisingly infers that prevention costs reduce substantially with increased quality improvement. A model published recently also combines failure and appraisal costs, two distinct categories (Cather and Nandasa, 1995). Quality managers believe that many of the widely publicised quality-cost models are inaccurate and may even be of the wrong form (Plunkett and Dale, 1988). A valid model that could be used to audit business performance and predict the effects of change would be most helpful. However, since the modelling of quality costs range from inaccurate to questionable, they are unlikely to provide a rigorous basis for product engineering to connect design decisions to the costs of poor quality.

• 'Micro-scaling' or bottom up approach to quality costs, where it is possible to calculate the cost of losses involved in manufacture and due to returns and/or claims. This method requires a great deal of experience and relies on the availability of detailed cost data throughout a product's life-cycle. While this is a crucial activity for a business, it is also not a practical approach for estimating the quality cost for product in the early stages of product development.

• The Conformability Analysis (CA) method presented in this book and Taguchi's Quality Loss Function (Taguchi et al., 1989) are what might be called 'meso-scaling' or quality-cost scaling. Here past failure costs are scaled to new requirements allowing for changes in design capability. It gives more precision than the global approach, but would clearly lack the accuracy of the bottom up approach possible

Quality related costs

Figure 1.12 Global quality-cost model (BS 6143, 1990)

once a product is in production. However, these methods are more useful at the design stage.

We have already seen elements of the CA approach when considering the costs due to safety critical failures. A further insight into the way that failure costs can be estimated for non-safety critical failures is also used to support the CA methodology. Estimates for the costs of failure in this category are based on the experiences of a sample of industrial businesses and published material as follows.

Consider a product whose product cost is Pc. The costs due to failure at the various stages of the product's life cycle have been investigated, and in terms of Pc, they have been found to be (Braunsperger, 1996; DTI, 1992):

0.1 Pc - internal failure cost due to rework at the end of the production line

Pc - external failure cost for return from customer inspection 10 Pc - external failure cost for warranty return due to failure with customer in use.

The relationship is commonly known as the '10x rule' and is shown in Figure 1.13. The 10 x rule demonstrates how a fault, if not discovered, will give rise to ten times the original elimination costs in a later phase of the life-cycle. In other words, products must be designed in such a way that scarcely any defects develop or if they do, they can be identified as early as possible in the product development process and rectified (Braunsperger, 1996). Other surveys have found that these costs could be even higher as shown in Figure 1.14.

Suppose a particular fault in a product is not detected through internal tests and inevitably results in a failure severity S = 5. If around 80% of failures are found by customer testing and 20% are warranty returns, then the expected cost on average for one fault will be 2.8Pc, from Figure 1.13. If the product has been designed such that Cpk = 1.33, or in other words, approximately 30 parts-per-million (ppm) failures are expected for the characteristic which may be faulty, then for a product costing £100 the probable cost of failure per million products produced would be £8400.

Relative company cost to rectify error

w la

0 rn oe

Stage where error is discovered

Figure 1.14 Cost escalation of rectifying errors at down stream stages (Ostrowski, 1992)

At Cpk = 1, or approximately 1300 ppm failures expected, the probable cost of failure per million products would be £364 000. At Cpk = 0.8 (or 8000 ppm) the probable cost of failure would increase by an order of magnitude to over £2.2 million. These failure costs do not take into account the costs associated with damaged company reputation and lost opportunities which are difficult to assess, but do indicate that failure cost estimates associated with product designs are possible. This aspect of the CA methodology is further developed in Chapter 2.

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