Sigma Plus Tool Crack
Kum Verna
Is there plans for extending the ss+ algorithm designer to support sigma 300 chips?
I have a few custom algorithm add-in's that i was using with sigma studio 4.7, i want to migrate to sigma studio plus but unable to use the same dll's (of course). Is the a way to use my sigma studio plugin's in ss+ , or a wrapper maybe??
Welcome to the third installment of our series on Lean and Six Sigma. As we saw in the first post, "What Are Lean & Six Sigma Methodologies?", Lean and Six Sigma are complimentary continuous improvement methodologies that reduce the overall waste and variability in production processes respectively. The second post, "Lean Principles and Tools," went into some depth on a few of the key principles, tools and methodologies in Lean. Here we conclude our series with a high-level discussion of Six Sigma. There are many tools in the Six Sigma toolkit (Failure Mode Effects Analysis (FMEA), IPO Diagram, Confidence Intervals, Histograms, Pareto Charts, F-Tests, Design for Six Sigma (DFSS), and many more) that will not be discussed here. The focus here is to discuss the statistical realities that make Six Sigma effective.
Six Sigma aims to identify and eliminate the root cause(s) of defects and waste using statistical tools to identify the variations causing defects. In Six Sigma methodology, the only way to effectively solve a problem is to permanently eliminate its root cause.
It is a measurement-based strategy that focuses on process improvement striving to achieve not more than 3.4 defects per million opportunities. A Six Sigma defect is defined as anything outside of customer specifications. A Six Sigma opportunity is then the total quantity of chances for a defect to occur.
Once the problem, goal, or area of improvement is described, it is critical to attempt to identify the various input and output variables that are related to the behavior of the process. Often the output variables are the one(s) that are out of the specifications. It is important to identify which input variables can be causing the variation with the output variable(s).
Once the input variables that are causing the output behavior are identified, it is possible to develop a measurement plan that provide enough data to start the analysis. This phase is where data is collected on the key input and output variables. This is also the phase where performance baselines are developed for use in measuring the improvements made later. As a rule, at least 30 observations are required to provide enough data to represent the process behavior.
Once the data is collected, it is analyzed to determine the most likely three to five potential root causes. This is accomplished by continued data collection and review to understand the contribution of each potential root cause using statistical tools, plots and charts. The DMAIC process is iterative and repeats until all valid root causes are identified.
Based on the valid root causes identified in the Analyze phase, the process is adjusted until the excessive variation is eliminated. The Measure and Analyze phases are repeated until the desired outcome is achieved.
When the desired outcome is achieved, the improvements are institutionalized so that the source of the excessive variation is eliminated. This step should be accompanied by a control plan to ensure that the outputs continue to be at an acceptable quality level. The Control Plan includes implementing Statistical Process Control to monitor the process and ensure that it continues to function properly over time. This control plan should also include countermeasures if a problem occurs.
Statistical Process Control is a tool that measures whether or not a process is meeting product or process standards. If a process is capable and stable over time, the outcomes that the process was designed to produce will be achieved.
A process is transforming inputs into outputs. In this case, the ingredients are the inputs. It is known that the oven needs to reach a given temperature for a specific amount of time with the muffin batter inside to get the ideal muffins.
If all special causes of variation as above have been eliminated, then the process is deemed in control and all of the variations that are experienced are variations that are inherent to the process itself. These include small variations in measured ingredients and slight variations in oven temperature. But, the process is robust enough to produce the desired outcome even with these sources of (inherent) variation.
Dr. William Shewhart, the Father of Quality, began developing control charts in the early 1920s. He realized that if key process output variables were measured, and they created a distribution that would graph like the bell-shaped curve above, then the variation being displayed was random and, therefore, inherent to the process.
In other words, the process is behaving or operating in the manner it was designed to work. If the data is not random, then there must be a logic to explain that behavior. That is what a special cause of variation is.
Shewhart also designed control charts (see below) that include control limits. Control limits are usually a distance of plus or minus three Standard Deviations from the mean. And, we know that if the data points are within the control limits, then our quality level is at least 99.7% good.
Please notice that there is no attention paid to the specifications or specification limits (tolerances). A process that is in control is producing what it was designed (not necessarily intended) to produce. Thus, it may actually be producing bad outputs.
By now we know if a process is capable and in control, it will, by definition, produce the outcome that the process was designed to produce. We discussed how to measure Process Control with SPC and the importance of keeping a process in control.
The Process Capability Index is used to determine how close the output is to the existing target and how consistent average performance is. Therefore, it can be used to predict future output performances and consistency.
The main issue in maintaining good process control is that, over time, any process will shift and drift, no matter how tight the initial settings were. When this occurs, the key point to remember is that as the process average moves, so does the entire variable range, while the specification limits stay stationary.
If the process moves beyond the specification limits, the process will be making defective products. You want to maintain index levels of 1.00 or better. This is achieved with good centering of the process average and minimizing variability.
In Summary: Using Six Sigma, it is possible to understand if a process is capable and to measure Process Control and Process Capability. As long as an "in control" process is capable of producing the desired outcome (Process Capability Cpk of at least 1.33), then it must perform properly as long as it is in control. For more information about Six Sigma, or Lean, please visit www.cmtc.com and select the "Services" option.
Issues are selected for special attention as six sigma plus projects. Projects with significant importance are assigned to Black Belts as six sigma projects. Thus each six sigma plus project is assigned a leader trained in six sigma and total quality management (tqm) tools. These Six Sigma Plus Black Belts' duties include teaching other members of the six sigma plus project team appropriate total quality management (tqm) philosophy, interfacing with management, coaching, leadership skills, teaching total quality management (tqm) tools and changing systems to sustain six sigma plus projects improvements.
Senior Leadership is responsible for the strategic plan, and selecting potential six sigma plus project areas. Once a six sigma plus project is understood using total quality management (tqm) tools, total quality management (tqm) techniques generate alternatives. Improvements are then implemented. Six sigma plus projects maintain improvements using control tools of total quality management (tqm). This is the define, measure, analyze, improve and control sequence (DMAIC) of six sigma. Six sigma training is recommended for the management and champions as well as for any six sigma black belt or green belt. /*Watermark Backgound Image Script- */if (document.all)document.body.style.cssText="background:white url(images/6back3.jpg) no-repeat fixed center" Click here six sigma project examples. Click here six sigma and tqm glossary of terms, including what is six sigma.
Six Sigma plus is a customer-centered approach that results in exemplary performance by business centers, all over the world. With strategy, people and processes as its basis this approach helps in streamlining and organizing various business processes to achieve optimum profitability and customer satisfaction.
Six Sigma is a methodology, which allows the process variations or deviations from the goal that may result in defects to be managed and eliminated, systematically. Multi-national corporations and business houses have implemented the Six Sigma process to improve their results and performances.
Six Sigma cannot be considered to be a quality standard and it is not a management system that allows people to measure the results. It is a way of thinking, which can be used in an organization to attain results that endure for a longer period of time. Six Sigma Plus is all about novel process thinking, customer-centric, data driven prioritizing and obvious and tangible results.
Six Sigma Plus allows organizations or major multi-national corporations, to integrate their tools into the learning cycles of Six Sigma and leading a change in their enterprises. It also helps them to implement a strategy effectively and efficiently use the feedback mechanisms to improve their organizational performance. The customer is the focal point in Six Sigma Plus.
Six Sigma works on two significant methodologies, namely, DMAIC and DFSS. DMAIC stands for Define, Measure, Analyze, Improve and Control and DFSS stands for Design for Six Sigma. DMAIC enables the business enterprises to improve the business process that are existent in their organizations. This methodology consists of five phases as mentioned in its expansion.
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