What is the Cost of Poor Quality in Your Manufacturing Environment?

Written by: Julie Fraser

Read Time: 4 min

Calculating costs related to quality problems is not straightforward. Some of the expenses are apparent, but many are not. Quality is a top customer requirement, and lowering costs is key to a profitable business. So, truly understanding the cost of quality warrants the effort. Fortunately, advanced manufacturing technologies can help analyze and understand expenses plus quality problems and escapes.

Calculating poor quality costs in manufacturing

The cost of poor quality and the cost of good quality are the two components of the metric cost of quality (CoQ). The cost of good quality focuses on getting systems in place to ensure good quality. So, quality problems typically trigger creating a business case to invest in systems that boost good quality. 

There are many cost components of low quality. Here are a few cost areas that are typically easy to see:

  • Scrap
  • Rework
  • Capacity wasted on making scrap or rework
  • Time wasted making poor quality products
  • Direct and indirect materials used in scrap
  • Energy wasted producing unusable materials
  • Customer fines for delivering off-spec products
  • Warranty claims
  • Recall costs

Yet, these represent only a portion of the actual cost of poor quality. Consider what else may result:

  • Unused capacity, planning delays, and supply chain expediting when scrap and rework are taken out of their planned sequence
  • Overtime when employees need to rework or make replacements for scrap
  • Time and focus to identify root causes and create corrective and preventative action plans and possibly re-engineer the process, product, or supply requirements definitions to prevent future quality problems
  • Time, energy, and marketing to repair brand damage, address customer complaints, and restore trust
  • Coping with possible health and safety risks as well as fluctuations in demands on employees

Any subset of those costs can mount up to significant expense. Once you have identified the issues, quantifying them is another step. Often, operations and finance staff must work together to understand the true cost of poor quality.

Advanced Manufacturing Approaches to Minimize Quality Issues

Calculating the cost of poor quality provides clear ideas on how to improve. First, it identifies the top opportunities, both apparent and hidden. Second, it gives a guideline on how much to budget for projects aimed at lowering those costs. Advanced manufacturing approaches can aim to spot patterns and avoid problems.

Avoiding quality problems

Some quality problems arise because of poor communications. Most production processes are complicated, with many interdependent steps. So, improving communication between steps in the process and people can significantly lower the cost of poor quality.

One way to improve communication is with connected workcells. With this technology, each area can see what is happening in the previous or upstream steps in the production process and prepare appropriately. They can also let those in downstream process steps know if there have been anomalies such as out of spec materials, rework, or equipment repair.

Another critical handoff is between employees on different shifts. Today’s technologies allow a complete accounting of what has happened on a shift with minimal effort. Systems can highlight non-conformance issues so those following on the next shift can again see where problems occurred. In many cases, a meeting can focus on solving those before making more product.

Spotting quality patterns

Gathering data in manufacturing is easier and more cost-effective than ever. The Internet of Things (IoT) can add new data points to create a more comprehensive picture of the production process and quality issues. Using advanced analytics on the broad set of data from equipment, IoT, and other sources, companies can begin to detect patterns.

There is a pattern for on-track production. Departures from that pattern can predict quality issues. There may also be specific patterns that arise for various quality problems. Seeing how these patterns correlate with quality can dramatically improve a company’s ability to lower certain costs.

Using machine monitoring, a company can keep tabs on these patterns as they arise. Sometimes, the company can prevent the quality problem from happening with timely equipment repair or calibration, employee training, materials management, or other proactive steps.

Lowering the Cost of Poor Quality

Manufacturing in these turbulent times demands efficiency and high customer satisfaction. Thus, lowering costs related to quality problems becomes crucial. 

Ensuring that everyone on the production floor has good access to information about what’s happened to the products and equipment in prior steps or shifts helps. Fortunately, combining data gathering through IoT into an advanced analytics platform is available to support good quality and lower the cost of poor quality.

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Tags: Thingworx Connected Devices Industrial Internet of Things

About the Author

Julie Fraser

Julie Fraser is the Vice President of Research for Operations and Manufacturing for research firm Tech-Clarity. She covers Industry 4.0, Smart Manufacturing, MES/MOM, QMS, APS, APM/CMS, IIoT, AR/VR, other technologies and solutions for manufacturing.

Julie has over 25 years as an industry analyst in addition to experience in marketing and strategy (Berclain/Baan, now Infor) and editorial roles for computer and technology publications. She worked as an assembler over college summers and that got her hooked on manufacturing. She has a BA in German and French, Magna cum laude, Phi Beta Kappa, from Lawrence University in Wisconsin. She is also a certified business change agent and conscious business ambassador.

Julie’s current areas of research include the realities of moving Industry 4.0 from vision to reality; the role of MES/MOM in the new landscape; incremental vs. transformational change in manufacturing; approaches to empower plant workers and their leaders; IT/OT convergence; personalized and local manufacturing; and more. She is fascinated by the organizational, cultural and personal transformations required to drive success with new technology and approaches to manufacturing.

Julie is a certified yoga and meditation teacher. When she’s in love with life, good things like the opportunity to work for Tech-Clarity come at the right time.