Statistical quality control (SQC) is a method of using statistical tools and techniques to monitor and improve the quality of products and processes. SQC can help you reduce defects, increase customer satisfaction, and save costs. But how can you ensure that your SQC is reliable and effective? Here are some tips to follow.
There are different types of SQC methods, such as control charts, sampling plans, process capability analysis, and design of experiments. Each method has its own advantages, limitations, and assumptions. You need to choose the methods that suit your quality objectives, data characteristics, and process conditions. For example, if you want to detect changes in the mean or variation of a process, you can use control charts. If you want to test the conformity of a product to specifications, you can use sampling plans.
To ensure statistical quality control is reliable, the following steps can be taken: 1. Collect accurate and representative data. 2. Use appropriate statistical methods: Use statistical methods that are appropriate for the type of data being analyzed. This includes selecting the correct control chart, choosing the appropriate statistical tests, and ensuring that the data is normally distributed. 3. Monitor and maintain equipment. 4. Train personnel. 5. Continuously monitor and improve: Continuously monitor the process to identify areas of improvement and implement corrective actions when necessary. This includes reviewing control charts, analyzing data trends, and identifying root causes of issues.
Selecting the right tool, knowing when and how to use it makes the key difference., Old 7 QC tools mainly focuses on analytic techniques whereas the New tools focuses on logical and rational thinking. A combination of these tools can help you arrive at the conclusion
A Real-time Statistical Process Control System is useful in gathering data. This data can be used to detect variability. While sampling can answer conformity issues, algorithms can be developed to answer both variations and conformity issues in Real-time. To achieve this, machine vision (such as Laser & Camera technology) and machine intelligence (computerized algorithms) are essential. A graphic user interface can then be used to display charts and analytical algorithms can make inferences to answer any question as required
Firstly understand the Problem statement and Data you are collecting. Picking the right tool will help you to solve problems easily and driving conclusions, inferences from it. Start with Basic Charts which will Make sense based on Data you are collecting.
Think about the expected value. Expected value is the value x its probability to happen. If the value is small then even if the probabily is high, it matter less. If the value( of the event that we monitor statistically) is high. Then even at law probability to happen, it is an important statistical problem.
SQC relies on data to measure and improve quality. You need to collect data that are relevant, accurate, and representative of your process or product. You also need to follow proper sampling procedures, such as randomization, stratification, and replication. You need to analyze the data using appropriate statistical techniques, such as hypothesis testing, confidence intervals, and regression. You need to interpret the results correctly and avoid common errors, such as overfitting, confounding, and bias.
Clearly one thing is to proceed for any improvement, 1st step you have to get the accurate data and analysis of the data. Because with the good analysis you get the right information and on right information you can make right action plan, which will be results in achieving the better numbers.
The devil lives in the details - Always validate your equipment, data, and collection methods before embarking on a major collection campaign and always test control or calibration data over the course of the study. Data collected well becomes insight, data collected poorly becomes an expensive lesson.
Define quality goals Choose the right SQC tools Collect and analyze data correctly SQC methods are used to make decisions on whether to accept or reject a group of parts or items based on the quality found in a sample. They are also used to determine whether a process should be continued or adjusted to achieve the desired quality.
As fases de coleta e análise de dados s?o fundamentais na avalia??o e otimiza??o de processos, em que se estabelece parametros de controle, identifica características de qualidade críticas e adota métodos de amostragem representativos. A calibra??o rigorosa de instrumentos de medi??o e o treinamento adequado dos operadores garantem consistência na coleta de dados. Na análise, ferramentas estatísticas avan?adas, como gráficos de controle e análises de capacidade do processo, monitoram desvios e avaliam a conformidade. A documenta??o meticulosa permite revis?es críticas e orienta a implementa??o de a??es corretivas e preventivas, o que sustenta a integridade do sistema e uma cultura de melhoria contínua.
SQC is not a one-time activity, but a continuous cycle of improvement. You need to implement the changes or solutions that you identified from your data analysis. You also need to monitor the effects of the changes on your quality performance. You need to use feedback mechanisms, such as control charts, to track the progress and detect any deviations or problems. You need to adjust your methods or actions accordingly and keep improving your quality.
Monitoring Improvements are always important as you will see if your changes in process are impacting positively. Control Charts are good way too see if your in spec and how off you are from desired standards.
When you develop a continuous improvement project, you do so based on some data analysis previously carried out on some KPI or process indicator. After implementing improvements, you must follow that same indicator and observe the impacts of those improvements. In general, time-based data is best for doing that, and control charts are a useful tool. But, before diving into deeper analysis, you should pay attention to the process, not just observe the data. It is very common for some practical aspects to occur after the modification that must be corrected.
I'll give an example of an induction sub motor of a diameter of 5.5" water cooled 25Hp. It has bronze bush mechanism with stainless steel thrust controllers underneath the rotor. With the experience you could tell by analysis that once electrical and mechanical problems occur it could either be both or one of the two. Data analysis and monitoring effects
SQC is not only a technical process, but also a human one. You need to train and involve your staff in your SQC activities. You need to explain the benefits and principles of SQC to your staff and encourage their participation and feedback. You need to provide them with the necessary tools and resources to perform SQC tasks. You need to reward and recognize their contributions and achievements. You need to create a culture of quality in your organization.
Train the staff Monitor frequently Check targets achievements Establish a quality dashboard or wall with all charts and graphs Explain problems to the involved technicians to avoid the reoccurrence in the future and prevent customer complaint and penalties.
This is very true, training is essential to get employee buy-in. Quality Control is a culture more than it is a job for one or more assigned expert(s).
Explicar los beneficios que puede traer en cada eslabón del proceso es fundamental. Para lograr integrar a los equipos de trabajo y hacerlos participar y sobre todo que crean en “algo nuevo” propicia un ambiente de producción sostenible y mejora continua.
Staff is your assett and they need to be looked after by training them to the best level ensuing results for the process as well giving them a lead edge to be more confident
SQC is not a static system, but a dynamic one. You need to review and update your SQC system periodically. You need to evaluate the effectiveness and efficiency of your SQC methods and procedures. You need to identify the strengths and weaknesses of your SQC system and look for opportunities for improvement. You need to consider the changes in your internal and external environment, such as customer needs, market trends, and technological innovations. You need to adapt your SQC system to meet the changing demands and expectations of quality.
1. Review Methods: Evaluate current SQC methods and gather feedback. 2. Adapt to Changes: Consider environmental and technological shifts. 3. Update Procedures: Revise procedures, provide training, and monitor continuously. 4. Document and Review: Document changes, encourage improvement, and schedule regular reviews. This ensures ongoing effectiveness and alignment with evolving quality standards.
It will depend upon the failure rate of a particular component and root cause analysis. Based on that the SQC will change. It is desirable to study FAT and SAT of a particular component to arrive at a mean SQC.
Ensure that updated software programs are implemented to have on line analysis which may relive you of manual work as sometimes due to the production work pressure shortcuts are used which eventually spoils the product quality
In my experience, the validation of tools utilized during this process is significant. One good technique would be the usage of the PDCA cycle and monitoring consistently your results.
Always Start with MSA.. or bluntly stating, check for the measurement systems and quality of data. The nature and type of data and the tools used for plotting makes a great differ