How do you identify process defects?

The word (defect) means a deviation from a standard The word (standard) means the description of how you run a process to acheiv a CTQ so the CTQ is the out put of a standard (SOP) Any SOP has 3 living documents link to it (PFD. PFMEA , PCP) So we run the process according to the sequences that described throughly in the whole 3 living document Then we measure the result (CTQ) to insure its conformity to the requirements This measure should be done via Statistics , which determine both defects , its frequency and also many other usefull readings Also it determines whether this defect is common or assignable The assignable defects don't need extra solution , it treats by JDI While common cause needs the lean six sigma methodology

To define a process( using lean six sigma methodology), we can use different tools to make things clear. The SIPOC tool helps us by listing who gives inputs, what the process does, and who receives the outputs. The KANO model helps understand what features make customer happy or disappointed in a product ,process or service. It separates features into basic needs, performance needs & the RACI model helps to figure out who is responsible, accountable, needs to be consulted, or just needs to be informed in a project/process . By using these tools together, we can create a well-structured process that meets customer needs and expectations.

Swap analysis helps to understand the process defect: In the automotive industry the quick step to understand the process defect by doing Swap analysis..! It’s an very easy and give quick understanding of part and process defect.! Part swapping involves replacing a component with an identical part from defect-free vehicle and swapped with the potentially defective part in the vehicle . The two parts are essentially exchanged to determine whether the problem persists or is resolved. If the problem appears again with defect free vehicle components there may be problem with assembly process or if it’s resolved it’s May be with part.! It’s an initial test only.! From my experience 70 to 80% of time it works well.!

In Lean Six Sigma, identifying process defects is achieved through a systematic approach that involves defining the process, collecting customer feedback, using process mapping and data collection to visualize and quantify defects, implementing real-time process monitoring, prioritizing defects with Pareto analysis, and conducting root cause analysis through tools like the Fishbone Diagram and Failure Modes and Effects Analysis (FMEA). Additionally, assessing process capability, eliminating waste through Value Stream Mapping, and engaging in continuous improvement activities like Kaizen and Gemba walks play crucial roles in defect identification and, ultimately, the enhancement of process quality and customer satisfaction.

My approach is to first understand the process then identify failure points try an measure process at those points. The best to approach a process is to set it up right the first time

Using the process flow diagram, ask the people responsible at each step, “what goes wrong?” It helps to have team conversations because there may be lots of agreement or disagreement to fuel the fire. Take note of those pinch points because there may be multiple perspectives. Those can be very fruitful in next steps of Analyze and Improve.

In my experience not enough time is spent analyzing what the data is saying. Too many feel, if it is not outside the lines ( Upper and Lower control lines) every thing is fine! When there are times it is not, even though “the parts are good”. You can have an out of control system statistically while still being in-between the upper and lower limits. Out of control systems will fail and it is better to analyze them when parts are good rather than waiting for lots of bad parts.

Once you have defined the expected end result(s) and your process, metrics will be clearly defined. This helps to eliminate overly completed data collection strategies and focus your efforts on KEY metrics.

Begin by precisely outlining the procedure and determining key metrics. Gather relevant information and create a process map to visualize the workflow. Analyze the data using control charts and statistical methods to identify variations. Conduct a root cause analysis to pinpoint underlying problems and establish tolerance boundaries. Apply statistical process control for ongoing monitoring. Encourage a culture of continuous improvement by addressing the root causes of defects and preventing their recurrence.

In my opinion, measuring the performance and identifying the gap may to fully identify the the defects. It needs special efforts to identify and list the defects and group them into types. Then we need to relate them to the KPIs and performance index.

Ensure your measurement system includes elements for inputs, output, and efficiency. Root causes can often be identified by examining a combination of those metrics.

This step is often not executed to it's fullest causing critical root causes to be overlooked or even ignored in favor of the push for results. Management should understand that each and every RCCA investigation completion time varies along with he required resources.

By employing different mindsets, observing problem occurrences and non-occurrences, we can unlock deeper insights and arrive at more comprehensive solutions. By observing when and where the problem occurs (and equally important, where it does not), we can generate valuable hypotheses. To truly understand the root cause of a problem, we must approach it from different perspectives and examine the issue from many viewpoints, as follows: 1) customer, 2) process or system, 3) employee, 4) location-based, 5) time-based. Focus on analyzing underlying process steps, interactions, and dependencies. Consider the problem as part of a broader system. Explore how interconnected elements within the system might be contributing to the issue.

If the RCCA investigation is done thoroughly, then the solutions are easier to define and project timelines are more predictable. Project cost and delivery are easier to define with less scope creep and teams are able to meet target deadlines more consistently.

we can use basic 7 qc tools to find and fix problems. First, we use Check Sheets to keep track of how often defects happen. Then, we make Histograms to see how defects are spread out. With Pareto Analysis, we figure out which defects are causing most of the trouble. Cause-and-Effect Diagrams help us understand why defects happen. By using Scatter Diagrams, checking for correlations between factors and defects. Control Charts help us to monitor the variation over the time. Stratification tools, like flowcharts, help us see where defects are happening in the process. It's crucial to make sure all equipment collects data accurately. If we find defects, we take action to fix them and make plans to stop them from happening again in the future.

In reality, this step is less about control and more about monitoring the results. If the desired results are not being met, then the process definitions and solutions were not fully developed and tribal knowledge is driving many of the outputs. This data is vital for the next step of the full review of the project(s).

You have to live on the plant floor every day , every shift . Leadership must be on the floor , listening to the Voice of Process and Voice of People. Conversations and sitting behind a keyboard won’t work. See with your eyes , touch with your hands . Gemba is critical to achieving process excellence .

Another set of data is the engineering change orders from previous equipment and manufacturing processes-especially within families of products. Process defects can re-occur in various forms and with this knowledge gathered there is opportunity to learn how to eliminate and reduce future defects. Another way to gain a deeper understanding is to spend time reviewing with the assembly technicians what issues/problems they deal with. Statistics, KPIs and non-conformance data is useful but may not provide details of the organic nature of the defects.

The use of DOE / Taguchi Methods can help to identify and establish the ideal parameters of critical process variables. The use of SPC can help to control those variables. Regarding SPC; it is important to note that it is Statistical PROCESS Control not Statistical PARTS Control.

Conduct thorough process analysis. Implement quality control measures. Utilize data-driven monitoring for timely defect detection.

Map it out: Chart your process, step-by-step. Pinpoint potential hiccups: bottlenecks, rework loops, unclear tasks. Measure performance: Track key outputs - time, quality, cost. Look for deviations from expected values. Use tools like control charts to spot trends. Gather feedback: Talk to employees, customers. Listen for frustrations, inconsistencies, near misses. Their lived experience reveals pain points. Analyze data: Crunch the numbers! Combine metrics with feedback to identify patterns. Did a new supplier cause quality dips? Are late deliveries linked to inefficient scheduling? Embrace the unexpected: Be alert for anomalies. A sudden spike in scrap rates, a drop in customer satisfaction - these often signal hidden defects.