1<br />King Saud University<br />College of Engineering<br />Industrial Engineering Department<br />Control Phase <br />By: WadeaAmeen 431106471<br />
What is DMAIC ?<br />•A structured approach to problem solving and process improvement <br />
DMAIC Process<br />PHASE 0: Definition.<br /> These processes consist of identification of product or process that need improvement and also benchmarking product characteristic from other company.<br />PHASE 1: Measurement.<br /> This phase consist of selecting characteristic (dependent variable, independent variable, process mapping). The major tool is Quality Functional Deployment (QFD).<br />PHASE 2: Analysis.<br />This process analyze and benchmark the key product or performance metrics. This phase determine which factor that influence more and which level of factor is the best for the process. Common tool is using Design of Experiment (DOE).<br />
DMAIC Process cont.<br />PHASE 3: Improvement.<br /> After knowing which characteristic level is the best, we must improve that process factor and characteristic. DOE and Taguchi Method are common tools used to make improvement.<br />PHASE 4: Control.<br /> This process need to monitor new process conditions via Statistical Process Control (SPC). After steady period, the process capability is assessed.<br />control:process performance and ensure that defects do not recur.<br />
Control Activities& Tools<br />Control Activities<br />- Determine Needed Controls (measurement, design, etc.)- Implement and Validate Controls- Develop Transfer Plan- Realize Benefits of Implementing Solution- Close Project and Communicate Results<br />Control Quality Tools<br /> - Statistical Process Control- Out of Control Action Plan (OCAP)- Design Changes to eliminate<br />
Objective Control<br />Prevent the problem and its root cause from recurring.<br />Document project<br />Implement results <br />Implement controls<br />
“Control” Flow<br />Select SPC controls where appropriate<br />Based on Solution, Brainstorm appropriate controls to sustain the gains<br />Implement and validate controls<br />Review and approve control plan with Management<br />Realize savings and determine final financial benefits and ROI<br />Determine long term owner and close the project<br />
<ul><li>The affinity diagram is a business tool used to organize ideas and data. It is one of the Seven Management and Planning Tools.</li></ul>The tool is commonly used within project management and allows large numbers of ideas stemming from brainstorming to be sorted into groups for review and analysis<br /><ul><li>The affinity diagram was devised by JiroKawakita in the 1960s and is sometimes referred to as the KJ Method.
Sort cards into groups until all cards have been used.</li></ul>Once the cards have been sorted into groups the team may sort large clusters into subgroups for easier management and analysis. Once completed, the affinity diagram may be used to create acause and effect diagram<br />
The process decision program chart <br />The process decision program chart systematically identifies what might go wrong in a plan under development. Countermeasures(اجراء مضاد) are developed to prevent or offset those problems. By using PDPC, you can either revise the plan to avoid the problems or be ready with the best response when a problem occurs.<br />How do we develop a Process Decision Program Chart?<br /><ul><li>Break down the task into a tree diagram. The bottom 'leaves' on the tree will now indicate the actual tasks to be carried out. For each bottom-level task 'leaf', brainstorm or otherwise identify a list of possible problems that could occur.</li></ul>Select one or a few of the risks identified in step 2 to put on the diagram, based on a combination of probability of the risk occurring and the potential impact, should the risk materialize.<br />For each risk selected in step 2, brainstorm or otherwise identify possible countermeasures(prevent ) that you could take to minimize the effect of the risk.<br />Select a practical subset of countermeasures identified in step 4 to put in the chart.<br />Continue building the chart as above finding risks and countermeasures for each task. If there are a large number of tasks, you can simplify the task by only doing this for tasks that are considered to be at risk or where the impact of their failure would be large.<br />
Matrix Diagram<br />Purpose: Compare two or more groups of ideas, determine relationships among the elements, and make decisions.<br />Process<br /><ul><li>Generate two or more sets of characteristics to be compared. Use tree diagrams or brainstorming.
Choose the proper matrix to represent the interactions (L, T, X, Y).
Put the characteristics on the axes of the matrix.</li></ul>Rank the interactions from 1 (low) to 5 (high)<br />
Control:<br />12. Implement process control system and bring the project to a close<br />Three primary approaches may be used at this stage:<br />Risk Management: <br />This is similar to FMEA but now focus is trained on x, rather than y.<br />Risk Management Score = RMS = (Impact)*(Probability)<br />RM identifies and quantifies risks, establishes a risk abatement plan, <br />and monitorsthe progress of the plan.<br />Mistake Proofing:<br />This is a technique for eliminating errors by making it impossible to make them in<br />the process. To quote: “It is good to do it right the first time. It is even better<br />to make it impossible to do it wrong.”<br />Statistical Process Control (Charts): <br />This is a feedback system with sequential data and ongoing process data collection.<br />
Statistical Process Control<br />Statistical process control (SPC) is the application of statistical methods to the monitoring and control of a process to ensure that it operates at its full potential to produce conforming product<br />Statistical Process Control may be broadly broken down into three sets of activities: <br />understanding the process, <br />understanding the causes of variation, <br />and elimination of the sources of special cause variation<br />
Control Chart<br /><ul><li>Why Use a Control Chart?
To monitor, control, and improve process performance over time by studying variation and its source.
There are many types of control charts. The control charts that you or your team decides to use should be determined by the type of data that you have.
Use the following tree diagram to determine which chart will best fit your situation. Only the most common types of charts are addressed.</li></li></ul><li>Control Chart Selection: Variable Data<br />n is ‘large’<br /> n > 10<br />n is ‘small’<br /> 3 < n < 5<br />2 < n < 9<br /> median<br />n = 1<br />X & Rm<br />X & R<br />X & R<br /> X & S<br />
Control Chart Selection: Attribute Data<br />Defective Data<br />Defect or<br />Nonconformity Data<br /> Constant Variable Constant Variable<br />sample size sample size n > 50 n > 50<br /> c chart u chart p or np chart p chart<br />
PRE-Control<br />PRE-Control technique helps shop operators to control the process so that defective parts are not <br /> produced. Although simple to understand for even the shop operators, PRE-Control is statistically robust<br /><ul><li>In PRE-Control, the drawing tolerance is divided in three zones as shown in the figure. These three zones are Green, Yellow, and Red.</li></li></ul><li>
PRE-Control Rules: <br /><ul><li>If five consecutive pieces are in Green </li></ul>zone, set-up is ok to run <br /><ul><li> If one yellow, restart counting
If two consecutive yellows, adjust the </li></ul>process <br /><ul><li> If one reading is red, adjust the process </li></li></ul><li>