Quality control Tools Implementation.pptx

Good for the quality management students

1. Metrology and quality coNtrol (IM-213 ) IMPLEMENTATION OF QC TOOLS : PRESENTED BY: ANUSHA AHMED (IM- 020 ) FAIZA MASHKOOR (IM- 010 ) IFRAH TANVIR(IM- 014 ) MAHNOOR AHMED (IM- 015 )

2. INTRODUCTION: 2 QC tools are a set of techniques used for quality control. They help identify and solve quality-related issues in a project or process. QC tools are important in ensuring that a product or service meets a certain level of quality. The 7 QC tools are used for different purposes, such as collecting and organizing data, monitoring variations, analyzing data distribution, identifying significant problems, identifying relationships between variables, identifying root causes of problems, and visualizing processes. By using these tools, businesses can improve their processes and products, reduce waste, and increase customer satisfaction.

3. 3 INDUSTRY 4.0: Industry 4.0 implementations integrate people, machines, data, technology, and processes and allow organizations to connect through digitization and cloud-based systems. Defining and implementing advancements in quality are always challenging and daunting. The definition of quality evolved from fitness for use and customer satisfaction to invariability. Acceptable input to the system and output from the system laid the basis for quality control (QC) including seven QC tools that were later revamped as quality assurance (QA) that used seven management tools.

4. PDCA CYCLE: The PDCA cycle, also known as the Deming Cycle or the She whart Cycle, is a four-step process for continuous improvement. The PDCA cycle can be used to improve any aspect of a business, including manufacturing processes, customer service , and product development . It has 4 basic steps Plan Do Check Act 4

5. USES OF PDCA CYCLE: Improve the efficiency of manufacturing processes. Reduce the number of defects. Increase customer satisfaction. Improve the safety of the workplace. 5

6. OTHER METHODOLOGIES: Some methodologies to implement in industry 4.0 for quality improvement are : Lean Manufacturing. Six sigma Overall equipment effectiveness Agile Manufacturing 6

7. Now goal is to identify the main factors which are improving with higher frequency and needs consideration to implement an Industrial 4.0 environment. Define objectives how industry 4.0 can improve production, efficiency and quality of products . Cloud data 7. Smart factory Cyber physical system 8. Virtual engineering Data mining 9. Augmented reality ERP 10. AI and Robotics Lot 11. Projects Smart factory CASE STUDY:

8. 8 FLOWCHART: Industry 4.0, flowcharts can be used for a wide variety of processes, including manufacturing, logistics, and supply chain management. Specifically, flowcharts can be used to visualize the flow of data and information across different systems and processes, such as the integration of sensors, machine learning algorithms, and cloud computing resources. The flow chart made is a general flow chart for the quality improvement of industry 4.0. Any product line can be defined and improved by this framework and methodology in industry 4.0 by smart factories and cyber physical systems. IMPLEMENTATION OF QC TOOLS ON INDUSTRY 4.0:

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10. 10 CHECKSHEET: Check sheets are simple and effective tools that have been used in various industries for quality control and data collection. In the context of Industry 4.0

11. 11 HISTOGRAM : Histograms are a powerful tool in Industry 4.0 because they allow companies to analyze large amounts of data quickly and easily. The histogram showed that the most common defects were related to data security, interoperability, cloud computing, cyber threats, need of skilled trainee. This data is helpful to prioritize these defects so that action can be taken for improvement of quality.

12. 12 PARETO CHART: In Industry 4.0, there is a massive amount of data and factors that can influence processes and outcomes. Pareto analysis helps identify the vital few factors that contribute the most to a problem or outcome.

13. 13 SCATTER DIAGRAM: In Industry 4.0, where large amounts of data can be collected from sensors and machines, scatter diagrams can be used to explore the correlation between different process parameters, machine performance indicators, or quality metrics. In Industry 4.0, where machines and equipment are equipped with sensors, scatter diagrams can be used to analyze the relationship between sensor readings and equipment performance.

14. 14 CONTROL CHART: In Industry 4.0, control charts can be integrated with advanced analytics and machine learning algorithms to analyze process data and identify patterns or anomalies. By leveraging historical data and statistical methods, control charts can provide insights into process capability, process stability, and potential areas for improvement.

15. RESULT: 15 We can analyze our outcomes based on the aforementioned charts. The flow chart is general for industry 4.0 framework, by defining the object we can implement industry 4.0 for quality improvement, productivity, etc. this flowchart provides a roadmap to all the framework required in any particular process of a industry or a smart factory. The PARETO CHART shows that there are 6 vital few, in case of industry 4.0 these are the main factors which needs constant improvement. The histogram shows that it is a symmetric histogram, which produces the best results. The SCATTER DIAGRAM displays non linear exponentially decreasing correlation As one variable increases, the other variable decreases at an accelerating rate. Since we don't have any special circumstances, CONTROL CHART(I and MR) indicates that all values fall between the UCL and LCL.

16. 16 MAIN FACTORS : Big data analytics Cyber-physical systems The Internet of things (IOT ) Robotics Virtual engineering The Smart Factory

17. THANK YOU!