The Case for Quality

ISO 9001 section 0.1 states: “The adoption of a quality management system should be a strategic decision of an organization.”  While ISO 9001 is the most widely adopted quality management system (QMS) standard in the world, many companies attach little or no importance to a well-designed QMS.

A recent article: Stauffer, R, Owens, D. “Lasting Impression: Quality management’s positive impact on the economy” Quality Progress, November 2012 makes the economic case for a QMS implementation, asking the question: “Does quality have a payoff?”

The authors reference the study “The Contribution of Quality Management to the UK Economy”, jointly commissioned by the Chartered Management Institute (CMI) and the Chartered Quality Institute (CQI). 

The study, researched and written by the Center for Economic and Business Research (CEBR), conducted a review of relevant business and economic literature, developed 18 case studies from various business and public service sectors, and surveyed 120 organizations.  From the literature research it concluded that an effective QMS resulted in:

·         Upward pressure on stock prices while unsuccessful quality management systems had the opposite effect.

·         Enhanced customer and employee satisfaction and retention.

·         Reduced costs.

·         Improvement in key financial performance metrics.

·         Greater focus on customer satisfaction.

From the organizations surveyed the CEBR found:

·         On average costs were reduced by 4.8%.

·         More than 93% agreed that the QMS was a significant contributor to success.

·         95% agreed that the QMS contributes to customer retention and satisfaction.

·         83% thought that the QMS provides consistent improvement and therefore higher productivity

·         83% agreed that without an effective QMS they could not justify pricing to customers.

The study examined key economic indicators in the UK for 2011.  The study determined that an effective QMS:

·         Contributed ₤86 billion ($135 billion) to GDP.

·         Contributed ₤8.4 billion ($13.1 billion) in corporate tax receipts.

·         Caused employment to be 1.43 million higher (4.94%) than it would otherwise have been.

The article makes a strong case for a well-designed QMS.  The results are likely transferrable to the US economy with similar results.

The benefits of an effective QMS take time to appear.  They do not happen overnight.  Commitment, involvement, and leadership from senior management are keys to success.

For assistance with ISO 9001 implementation see www.rosehillsystems.com

 

Acceptance Sampling

ISO 9001 section 8.2.4 says that the organization must monitor and measure the characteristics of the product in order to verify that the product meets requirements, but is silent on the methods to be applied to monitor and measure product characteristics.  The choice of inspection methods is left to the organization. 

Acceptance sampling is one such method.  Since it is not practical to inspect every item in a large batch, acceptance sampling allows you to infer batch quality by examining a random sample from the batch.  Statistically designed acceptance sampling plans, as a method of measuring product conformity, have been around since at least World War II.  Sampling plans like MIL-STD-105, authored by Harold F Dodge and others, have been in use for over 60 years.

Because not all items in the batch are examined, there are risks associated with statistical acceptance sampling.  Two risks are typically calculated:

·         The Acceptable Quality Level (AQL), also known as producer’s risk, is the percent defective that is likely to be accepted 95 % of the time.  There is a 5% chance that product of higher quality than the AQL will be rejected by the sampling plan.

·         The Lot Tolerance Percent Defective (LTPD), also known as consumer’s risk, is the percent defective that is likely to be accepted 10% of the time.  There is a 10% chance product as defective as the LTPD will be accepted by the sampling plan.

Each sampling plan has an associated operating characteristic curve (OC) which describes the probability of lot acceptance as a function of the lot’s percent defective.  The AQL and LTPD represent two points on the OC curve.  As the lot percent defective increases, the probability of accepting the lot based on the sampling plan that the OC curve represents decreases. 
In addition to the risks associated with acceptance sampling plans, there are some practical disadvantages:

·         While acceptance sampling greatly reduces the number of items inspected, other sampling methods such as statistical process control reduce inspection even further and provide process control feedback.

·         When a lot is rejected, we will know why the lot is rejected, but we will not know the root cause of the defect.  We will only know that the product is defective.  There is no control mechanism that will help us control the process the product comes from.

·         Acceptance sampling assumes random sampling, but in most cases the sample is stratified because the product is normally stored in boxes.  As such, it is possible that some product will never have a chance of being sampled and the sample will not be random.

·         Sampling plans based on AQL, LTPD, or AOQL (Average Outgoing Quality Limit) assume that a certain amount of defective material is acceptable.  This sends a message to employees and suppliers that some level of defectiveness is acceptable.  This is not the best message to send if the organization is trying to be a best in class producer.

Sampling plans can be designed by users, or selected from standards such as MIL-STD-105, now obsolete, or ANSI Z1.4 which implements the same plans.  A common pitfall suffered by users not familiar with sampling plan design is to design constant percentage sampling plans.  Avoid constant percentage sampling plans (a fixed percentage of the lot is sampled regardless of lot size).  For small lots, constant percentage sampling plans may not afford enough protection.  For large lots, an excessive amount of inspection will usually result, and the sampling plan will be over critical.

Consider a sampling plan that samples 10% of a lot.  For a 50 piece lot, a 5 piece sample will result in approximately a 1% AQL, but a 46% LTPD (a very weak sampling plan).  For a 5000 piece lot, a 500 piece sample will result in an AQL of .001% and the LTPD will be .46% - a plan unlikely to accept any lot.

While there are better ways to control production processes than acceptance sampling, acceptance sampling can be an effective method for a customer to protect itself from accepting defective purchased product.  Since the customer has no control over the manufacturing process, it is not important for it to understand what process variable caused defective material.  It need only know that the product is defective.  The customer is susceptible to stratified sampling, but accepts this disadvantage in favor of inspecting a small percentage of the entire batch.

For more information see www.rosehillsystems.com