The Cost of Poor Quality (COPQ) refers to the total expenses incurred due to manufacturing defects, inefficiencies or error during the processes. Typical categorizations of COPQ are divided into four main areas: Prevention costs, appraisal costs, internal failure cost and external failure cost.

Understanding COPQ is beneficial for organizations as it highlights the areas where quality improvements can lead to significant cost savings. (AIAG, 2012).

Internal failure costs arise from defects identified before the product reaches the customer and include activities such as rework, where faulty products are corrected and scrap. (Chopra & Garg, 2011).

Quality Management in production

Quality Management in production is fundamental aspect of any manufacturing process which determines that the product meets its design specifications and customer expectations. High production quality is essential for ensuring customer satisfaction, operational efficiency, and overall business success. (Schroeder et al., 2005).

Barrie G. Dale and Mark Smith (1997) developed a Spectrum of quality management grid where a manager can look at the problems, issues, and behaviour in their business, and then decide what steps to take to help things improve and move forward. (Dale & Smith, 1997).

The Automotive Industry Action Group (AIAG) published the 1^st handbook version of The Cost of Poor Quality Guide (2012), where the spectrum was graphically explained that for every action in an organization there is an impact on the company´s future. (AIAG, 2012).

In the picture below, is the Quality Spectrum with subsequent steps. Based on: (AIAG. 2012).

Development work and research methods

The thesis was done as development work for the company, with different research methods with the goal to be able to calculate the cost of poor quality directly and use it to develop an indicator.

Data of the repairs was collected form ERP system after the path was created. From the ERP system we were able to identify that the repairs can be divided into two phases: During and post production repairs. The indicator and in cost of poor quality challenges has been considered by interviewing another factory where the COPQ indicator has been created earlier.

For the interviews, semi-structured as qualitative research method was chosen. There was a set of open-ended questions in advance prepared, but I also allowed room for the conversation to flow naturally and for new topics to come up based on the interviewee’s responses and during COPQ indicator illustration.

I found the conversational style helpful in building trust and encouraging participants to share their experiences more openly. Although the interviews took time to conduct and analyze, they provided rich, detailed information that supported the objectives of my thesis.

Results

The results based on data in this work can be considered successful, even though an example value was used as the coefficient in the calculation formula. The intention is to use the actual value once it becomes available, as it will be obtained later when all costs have been considered.

The average cost per one repair case during production was calculated to be 6,617 € and for post production repair the calculation was 1,480 € per case.

The most valuable and the most effective findings were the interviews in another factory regarding COPQ. The two performed interviews gave the knowledge and understanding on COPQ indicator but also beneficial information on what to exclude from the indicator due to its complexity.

Conclusions

The biggest development opportunity is to collect the repair hours into indicator and visually present to the stakeholder. When quality costs are defined and categorized in the future, this will give different thought on where to focus and how.

The calculation examples are cost calculations directly on the amount of repair time, therefore in future it can be used to compare on potential saving cost when actions need to be taken.

Based on the interviews performed in another company about COPQ indicator, this development project will not adopt a similar indicator for its analysis. Instead, alternative approaches better suited to ensuring data reliability, strategic relevance, and actionable outcomes will be pursued.

Thesis in Theseus: https://urn.fi/URN:NBN:fi:amk-2025060520683

References

AIAG. (2012). Cost of Poor Quality Guide (1st ed., Vol. 1). Automotive Industry Action Group.

Chopra, A., & Garg, D. (2011). Behavior patterns of quality cost categories. The TQM Journal, 23(5), 510–515. https://doi.org/10.1108/17542731111157617

Dale, B. G., & Smith, M. (1997). Spectrum of quality management implementation grid: Development and use. Managing Service Quality: An International Journal, 7(6), 307–311. https://doi.org/10.1108/09604529710186651

Schroeder, R. G., Linderman, K., & Zhang, D. (2005). Evolution of Quality: First Fifty Issues of Production and Operations Management. Production and Operations Management, 14(4), 468–481. https://doi.org/10.1111/j.1937-5956.2005.tb002