QCC (Quality Control Circle) Practical Case: From the Shop Floor to Continuous Improvement

In June 2024, the manufacturing director of a certain automotive parts company presented a set of data at the monthly quality conference: over the past 12 months, 23 improvement projects initiated by frontline employees through QCCs had generated a direct economic benefit of approximately 4.2 million yuan, while the total gains from six Six Sigma projects led by engineers during the same period were 3.8 million yuan. More intriguingly, the average implementation cycle for the 23 QCC projects was only 47 days, far shorter than the 112 days for Six Sigma projects.

This set of data reveals a fact often overlooked by many companies: QCC (Quality Control Circle) as a bottom-up improvement activity involving all employees often has a comparable return on investment and efficiency to systematic Six Sigma projects, and it plays an irreplaceable role in enhancing the quality awareness and improvement culture of frontline employees.

However, the effectiveness of QCC implementation in domestic companies is highly polarized. Some companies have active QCC groups with abundant results, while others fall into the trap of formalism: "QCC groups are formed, activities are initiated, results are compiled, and the process is just a formality," leading to the groups becoming defunct after three months. What is the root cause of this disparity? How should QCC be effectively implemented? This article will systematically break down the complete path from the formation of QCCs to the publication of their results through two real cases.

1. Core Framework of QCC Methodology

Before delving into the cases, it is necessary to clarify the basic operational logic of QCC. QCC is not a casual "group discussion," but a structured improvement method with a complete process, tools, and review mechanism.

1.1 Ten Steps of QCC Activities

Standard QCC activities typically follow the ten steps below, which are highly consistent with DMAIC in logic but place more emphasis on the operability for frontline employees:

1.2 Complementary Relationship Between QCC and DMAIC

Many quality professionals ask: with Six Sigma DMAIC already in place, why do we need QCC? The answer lies in the different positioning of the two methods.

DMAIC is suitable for solving cross-departmental, data-intensive, and complex problems that require advanced statistical analysis, typically led by Black Belts or Green Belts with a cycle of 3 to 6 months. In contrast, QCC is suitable for solving local problems at the workshop or team level, led by frontline employees with a cycle of 1 to 2 months, requiring less statistical tools and emphasizing "80% of problems can be solved using the seven QC tools."

QCC addresses "small improvements in daily work," while DMAIC addresses "systemic major issues." The coexistence and complementarity of both methods are the hallmarks of a mature improvement system.

2. Case One: "Tongxin Circle" of a Certain Automotive Parts Company Reduces Welding Spatter Defect Rate

2.1 Background and Circle Formation

In March 2024, the second welding workshop of a certain automotive parts company (hereinafter referred to as Company A) faced a persistent issue: the welding spatter defect rate for the rear subframe assembly was consistently between 5.8% and 7.2%, far exceeding the company's target of 3.0%. Spatter not only affects the appearance of the product but can also lead to insufficient weld point strength in extreme cases, posing a quality risk.

The peculiarity of this issue was that the welding process parameters had been optimized multiple times by process engineers, and the test piece inspection data was all within specifications. However, once mass production began, the spatter problem reappeared. Despite multiple meetings between the quality department and the process department, a stable solution was never found.

Against this backdrop, the team leader, Mr. Li, took the initiative to apply for the formation of a QCC to address this problem. The circle was named "Tongxin Circle," symbolizing "united efforts to overcome difficulties." The circle consisted of 7 members: 1 team leader (circle leader), 4 frontline welding operators, 1 equipment maintenance technician, and 1 quality inspector. The workshop director served as the mentor, and a quality engineer from the quality department served as the external technical advisor.

2.2 Step 1: Theme Selection

At the first circle meeting, the group used brainstorming to propose 9 potential topics, including "reducing electrode replacement frequency," "reducing welding tongs cable wear," and "improving changeover efficiency." After quantifying the scores using an evaluation matrix (scoring dimensions included: problem severity, improvement potential, technical difficulty, urgency), "reducing the welding spatter defect rate" emerged as the top choice with a score of 92, and was selected as the theme for this activity.

After the theme was selected, the circle developed a simple activity plan, clearly defining the time nodes and responsible persons for each stage, with a total planned cycle of 8 weeks.

2.3 Steps 2-4: Current Status Investigation and Goal Setting

The circle first collected spatter defect data from January to March 2024. The quality inspector exported daily spatter defect records from the MES system, and the circle leader organized the team to use stratification to analyze the data by shift, workstation, and product model.

The stratification analysis revealed three key facts:

1. The spatter defect rate showed a significant shift difference: 5.2% for the day shift, 6.8% for the afternoon shift, and 7.9% for the night shift. The night shift defect rate was more than 50% higher than the day shift.
2. Among the four welding stations on the production line, the spatter defect rates for stations 2 and 4 were 8.5% and 7.8%, respectively, much higher than the 4.1% and 4.5% for stations 1 and 3.
3. The spatter defect rates for different product models did not show significant differences, indicating that the problem was more related to the workstation and operation level rather than the product design.

After clarifying the current status, the circle set the goal: to reduce the welding spatter defect rate from the current 6.5% (three-month average) to below 3.0%. The basis for setting this goal was the company's quality target and industry benchmark data, while also considering the circle's improvement capabilities within the planned cycle.

2.4 Steps 3-4: Cause Analysis and Key Factor Confirmation

This is the most critical phase of the QCC activity, testing the circle's analytical capabilities. The circle held three consecutive meetings for cause analysis.

At the first meeting, the group used a fishbone diagram (cause-and-effect diagram) to list 26 potential causes of spatter defects from five dimensions: people, machines, materials, methods, and environment. These included: abnormal opening of the welding tongs, insufficient cooling water flow, oil contamination on the sheet metal, differences in employee operation techniques, and deviations in wire feeding speed.

At the second meeting, the group used the 5Why analysis method to deeply explore the top five potential causes. Taking the "high defect rate during the night shift" as an example, the chain of questions was as follows:

Why1: Why is the spatter defect rate higher during the night shift? → Because the electrodes of the welding tongs wear out faster during the night shift. Why2: Why do the electrodes wear out faster during the night shift? → Because the night shift produces a thicker reinforced plate product. Why3: Why does a thicker product lead to faster electrode wear? → Because welding a thicker plate requires a higher welding current and a longer welding time. Why4: Why does the problem still occur after parameter adjustments? → Because the operators do not adjust the welding parameters in a timely manner when switching products. Why5: Why are the parameters not adjusted in a timely manner? → Because there is no clear "product switch-parameter reference table" on-site, and the operators rely on experience, with fewer experienced employees during the night shift.

This 5Why analysis revealed the deep-rooted cause: it was not a problem with the equipment or the employees' efforts, but rather the lack of standardized and visual parameter switching guidance.

At the third meeting, the circle verified all potential causes one by one, confirming three main factors through on-site measurements, data comparisons, and simple experiments:

1. Welding parameters not standardized by product type (Key Factor A)
2. Insufficient electrode grinding frequency at station 2 (Key Factor B)
3. Lower operational proficiency of night shift employees for special products (Key Factor C)

2.5 Steps 5-6: Countermeasure Formulation and Implementation

For the three key factors, the circle formulated corresponding improvement countermeasures and assigned them to specific responsible persons and time nodes:

Countermeasure for Key Factor A: Led by the circle leader, Mr. Li, in collaboration with process engineers, the circle developed a "Welding Parameters-Product Model Reference Table," standardizing 7 key parameters (welding current, welding time, electrode pressure, wire feeding speed, etc.) for 12 common products. This table was posted above the operation panel of each welding station. Additionally, a parameter switching reminder function was set up in the MES system—when a product switch is scanned, the system automatically displays the corresponding parameter settings.

Countermeasure for Key Factor B: The electrode grinding frequency at stations 2 and 4 was adjusted from once every 100 cycles to once every 60 cycles. The equipment maintenance technician was responsible for setting the counter alarm value and confirming the grinding quality during the daily pre-shift inspection.

Countermeasure for Key Factor C: Special training sessions were conducted for night shift operators, led by experienced operators from the day shift. The training lasted for two consecutive weeks. A "Employee Skill Matrix" was also established to specify the qualification requirements for each workstation, ensuring that at least one skilled operator is present at each night shift workstation.

The above countermeasures were implemented simultaneously in the first week of May 2024. The circle held a progress meeting every week during the implementation process to record issues and deviations and make timely adjustments.

2.6 Steps 7-9: Effect Verification and Standardization

One month after the implementation of the countermeasures (early June 2024), the circle verified the improvement effects. The results were as follows:

• The spatter defect rate for the entire production line decreased from 6.5% to 2.1%, below the target of 3.0%.
• The defect rate for the day shift decreased from 5.2% to 1.8%, and for the night shift from 7.9% to 2.6%, significantly narrowing the shift difference.
• The defect rate at station 2 decreased from 8.5% to 2.3%, showing the most significant improvement.
• The electrode consumption increased by about 15% due to the higher grinding frequency, but the savings from reduced defects far outweighed the increased grinding costs.

In terms of intangible effects, the circle members wrote in their activity summary: "Previously, spatter was seen as an unsolvable old problem, but now we know it's not unsolvable, just that the right methods were not used." The activity enthusiasm of the circle members significantly increased, with several members volunteering to participate in the next QCC activity.

The circle solidified the improvement results into three standard documents: the "Welding Parameters-Product Model Reference Table" was incorporated into the process document management, the "Electrode Grinding Standard Work Instruction" was updated, and the "New Employee On-line Training Standard Process" was integrated into the workshop training system.

2.7 Result Calculation and Presentation

The total input for the "Tongxin Circle" QCC activity was 8 weeks × 7 people × 2 hours/week = 112 person-hours, plus the cost of experimental materials and training, totaling about 18,000 yuan. After the improvements, the average number of defective products per month decreased by about 420 pieces, with a repair cost of 35 yuan per piece, saving 14,700 yuan per month. Combined with the reduction in scrap and inspection time, the annual economic benefit was approximately 180,000 yuan. This case won the first prize at Company A's 2024 QCC result presentation conference.

3. Case Two: "Feiyi Circle" of a Certain Electronics Manufacturing Company Improves SMT First Pass Yield

3.1 Background and Problem

In March 2025, a certain electronics manufacturing company (hereinafter referred to as Company B) encountered a challenging issue on one of its SMT (Surface Mount Technology) production lines. This line produces power management modules for a well-known smartphone brand, with a production capacity requirement of 1,800 units per day. However, the first pass yield (First Pass Yield, FPY) after SMT was only 87.3%, meaning that more than 200 units per day required manual rework. Rework not only increased labor costs but also posed a long-term reliability risk for PCB boards due to the double reflow soldering process.

Company B had previously tried various improvement methods: adjusting the reflow soldering temperature curve, changing the solder paste brand, and increasing the SPI (Solder Paste Inspection) frequency. These measures had some effect, but the FPY remained between 85% and 89%, failing to break the 90% threshold.

3.2 Circle Formation and Current Status Analysis

The process technician, Mr. Wang, from the SMT workshop led the formation of the "Feiyi Circle." The circle members included 2 SMT operators, 2 quality inspectors, 1 equipment maintenance technician, and 1 process engineer. The circle determined the activity theme as "improving the SMT first pass yield to over 95%."

During the current status investigation phase, the circle exported defect data from the SPI and AOI systems for the past two months, totaling 3,287 records. The quality inspector used a Pareto chart to analyze the data and found:

• The top defect type was "insufficient solder," accounting for 38.6%.
• The second most common defect type was "misalignment," accounting for 24.3%.
• The third most common defect type was "bridging," accounting for 17.8%.
• The cumulative percentage of the top three defect types was 80.7%, consistent with the Pareto principle (80/20 rule).

The circle decided to focus on these three types of defects, setting the goal to increase the FPY from 87.3% to over 95%.

3.3 Cause Analysis and Countermeasures

Root Cause Analysis for Insufficient Solder: The circle checked the parameter settings and historical alarm records of the solder paste printer and found a key pattern—insufficient solder defects were concentrated between 9:00 AM and 10:30 AM and between 2:00 PM and 3:30 PM. Further investigation revealed that these times coincided with the shift change and the restart of the line after lunch breaks. Each time the line was restarted, the solder paste stayed on the stencil for a longer period, changing its viscosity and leading to unstable printing. The root cause was identified as lack of solder paste viscosity management.

Countermeasure: Develop a "Solder Paste Usage Management Standard," stipulating that the solder paste must be stirred again if it stays on the stencil for more than 30 minutes, and replaced if it stays for more than 1 hour. Additionally, a real-time solder paste viscosity monitoring function was added to the SPI equipment, which automatically alarms when an anomaly is detected.

Root Cause Analysis for Misalignment: Misalignment defects were mainly concentrated at the edges and corners of the PCB board. The circle measured the placement accuracy data of the pick-and-place machine and found that the positioning deviation in the X-axis direction at the end of the travel reached ±0.08mm, close to the specification limit of ±0.10mm. Further inspection revealed that the lubrication cycle of the pick-and-place machine's guide rails had exceeded the two-week limit, increasing the guide rail resistance and reducing placement accuracy.

Countermeasure: Adjust the guide rail lubrication from once a month to once a week, and establish a guide rail cleaning and lubrication inspection card. Additionally, add a placement accuracy verification step during the daily pre-shift inspection, using a standard calibration board for three tests. If the deviation in any direction exceeds ±0.06mm, the calibration process is triggered.

Root Cause Analysis for Bridging: The circle found that bridging defects were mainly concentrated on QFP (Quad Flat Package) and BGA (Ball Grid Array) components. Cross-analysis revealed that when the PCB board stayed for more than 20 minutes before reflow soldering, the bridging rate increased from the normal 2.1% to 5.6%. The reason was that the solder paste was exposed to the air for too long, causing the solvent to evaporate and increasing the viscosity, which prevented the solder paste from fully merging during reflow.

Countermeasure: Optimize the production rhythm management of the PCB board, specifying that the time window from solder paste printing to reflow soldering should not exceed 15 minutes. Add a "work-in-progress time limit" monitoring module to the production line control system, automatically diverting PCB boards that exceed the time limit for re-printing before re-entering the line.

3.4 Effect Verification

Two weeks after the implementation of the countermeasures, the circle conducted the first verification of the improvement effects. The SMT first pass yield increased from 87.3% to 94.8%, just 0.2 percentage points short of the 95% target. The circle did not settle for this result and continued to analyze the remaining 1.2% of defects, finding that about 0.5% were due to new employees' operational errors. The circle then increased online training and poka-yoke prompts, and after two weeks, the FPY stabilized at 95.6%.

The total duration of the "Feiyi Circle" QCC activity was 6 weeks, with a total cost of about 25,000 yuan (including the cost of the solder paste management system upgrade). After the improvements, the number of rework boards decreased by about 150 per month, saving 45,000 yuan in rework costs per month. Combined with the reduction in scrap and material savings, the annual economic benefit was approximately 580,000 yuan.

4. Key Elements for Successful QCC Implementation

Through the above two cases, several common elements for the successful implementation of QCC can be summarized:

First, the topic should be "accurate and not too broad." QCC is a tool for frontline employees, not for Black Belts. The topic should be a problem that the team can solve independently at the workshop or team level, and the scope should not be too large. "Tongxin Circle" chose welding spatter, and "Feiyi Circle" chose SMT defects—both are specific problems faced by operators every day. If the topic becomes something like "reducing the entire factory's manufacturing costs" or "optimizing the supply chain delivery cycle," the circle will be at a loss.

Second, the tools should be "sufficient and practical." QCC does not require complex statistical tools. In the two cases, the main tools used did not exceed eight: brainstorming, evaluation matrix, stratification, Pareto chart, fishbone diagram, 5Why analysis, run chart, and radar chart. These tools, known as the "seven QC tools," are sufficient to solve more than 80% of the problems on the shop floor.

Third, the data should be "visible." The information sources in the two cases were completely different: Company A used data exported from the MES system for stratification analysis, while Company B used quality data from the SPI and AOI systems for Pareto chart analysis. Regardless of the data volume, the key is to make the current status visible and understandable to frontline employees. Many QCC activities fail because they lack data support, and discussions remain at the level of feelings and experience.

Fourth, the mentor should not be "absent." The main participants in QCC activities are frontline employees, but without a mentor who understands the methods (usually the workshop director or quality engineer), the circle can easily fall into the trap of "idle talk" or "brute force." In the analysis phase, the mentor of Company A guided the circle to use the fishbone diagram and 5Why analysis, while the mentor of Company B helped the circle coordinate process resources during the implementation phase. Correct method guidance is the "invisible pillar" of QCC success.

5. QCC and DMAIC: The Dual Engines of the Corporate Improvement System

Returning to the question posed at the beginning of the article: what is the relationship between QCC and Six Sigma DMAIC?

From the intrinsic logic of the methodology, the ten steps of QCC correspond clearly to the five stages of DMAIC: topic selection corresponds to Define, current status investigation to Measure, cause analysis to Analyze, countermeasure formulation and implementation to Improve, and effect verification and standardization to Control. QCC is essentially a "lightweight, practical" version of DMAIC.

However, from a practical perspective in companies, the two methods should not replace each other but should be deployed in layers:

• Major issues (cross-departmental, high complexity, requiring statistical modeling) → Six Sigma DMAIC → led by Black Belts or Green Belts
• Medium issues (workshop-level, moderate complexity, requiring tool assistance) → QCC Quality Control Circle → led by frontline team leaders
• Minor issues (position-level, simple, easily solvable) → Rationalization Suggestions → daily improvement by all employees

Once the roles and responsibilities at each level are clearly defined, improvement activities will not fall into the chaotic state of "one-size-fits-all." Six Sigma delves deep, QCC covers a wide range, and rationalization suggestions are practical, forming a three-tier system that supports each other and collectively drives the internal improvement momentum of the company.

6. Conclusion

QCC is not a new concept and can even be considered a "dated" tool. However, it is precisely this "old tool" that is severely underestimated in many companies pursuing "high-end" methodologies. The two cases presented here showcase the most basic and solid strength of QCC: enabling the people who understand the problem the most to use the simplest methods to solve the most practical problems.

When a company can achieve "everyone participating in improvements and every circle producing results," the company's quality culture and improvement capabilities have been internalized into the organization's bones—this is the greatest value of QCC and the fundamental reason why it has been promoted by the global quality community for half a century.

QCC is not about making employees smarter, but about making smart methods a habit for employees.

Knowledge code: 5.1.2

Version: v20260724

Author: Quality Think Tank Quality Think Tank is dedicated to providing systematic professional knowledge, methodologies, and practical tools for quality management practitioners, helping companies continuously improve their quality capabilities.