Six Sigma | Arrelic Insights
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Six Sigma is a rigorous methodology that uses data analysis to identify and eliminate defects in manufacturing and business processes. It aims for near perfect production processes with only 3.4 defects per million opportunities. DMADDD is a digital process used to drive costs out of processes by automating non-value tasks. Critical to Quality factors (CTQs) are key process outputs that are important to measure. Potential causes of defects are identified and the most influential ones are targeted for improvement through tools like a cause-and-effect chart.
Six Sigma | Arrelic Insights
- 2. Introduction The term itself (six sigma) comes from manufacturing jargon and without going into specifics and technical talk you should just remember that it refers to a process that has only 3.4 defects in a million output units – be it physical products or other particular tasks that can be measured in units. It is a rigorous and disciplined methodology that uses data and statistical analysis to measure and improve a company's operational performance by identifying and eliminating "defects" in manufacturing and service- related processes. We help organizations to implement Six Sigma by identifying the right projects, help them execute the project most cost-effective way. DMADDD (DEFINE, MEASURE, ANALYZE, DESIGN, DIGITIZE, DRAW-DOWN) Part of Motorola’s Digitization effort, DMADDD is used to drive the cost out of a process by incorporating Digital improvements. These modifications can drive dramatic improvements in efficiency by identifying non-value tasks and using simple web-enabled tools to automate certain tasks. In doing so, employees can be freed up to work on more important duties. Define: Where must we be leaner? Measure: What’s our baseline? Analyze: Where can we free capacity and improve yields? Design: How should we implement? Digitize: How do we execute?
- 3. Critical to quality(CTQ) The CTQ is critical to quality to reduce the defective rate and we wanted to maintain worker safety and maintain in Weld strength okay so some of you out there undoubtedly are welders I am not so I made this up and you can probably improve on it but it's a teaching example okay over on this side we list our key process output variables these are the meters that we would like to watch to see how each of our process steps has gone over here are the key process and input variables these are the knobs we would like to be able to adjust or that we can adjust to make the process come out like we want it so then that's the whole point is to get these CTQ's SOME EXAMPLES The knobs we can adjust so I go through and for example down here in the performing the weld things that I know a little bit about is the wire feed rate. The type of the wire and if you've got some shielding gas that you're flowing over it why how much of that and one thing that might be important sometimes is the time. since the surface prep was done got a surface prep step back here and if some processes if you allow too long to elapse then you will have difficulty getting a good weld so having collected that the next issue is which of all of these input variables is most important now we could go through it. In fact I'm going to shrink that down a little bit we could go through if we wanted to and we could analyse each of those input variables but that would be very costly and there's no reason to do it. There's a really well-established rule not law but pretty good rule that most of the problems come from a few variables all right so what we need is some simple tool for assessing which ones of these we might spend most of our time on and that would be the cause and effect chart.
- 5. How to deploy CTQs ? Here are my CTQ's these are automatically carried forward for me here are all of the KPIVs that I collected those are automatically carried forward for me I assign weights to each of these CTQ's okay and then I fill out this matrix I can put in 0 1 3 or 9 depending on how much this input variable influences this CTQ okay and then I just hit calculate and it does a little bit of arithmetic and arranges these in descending order of importance ,so it's just a rough quick and dirty selection of what's most important now instead of having to do a few dozen variables. A few variables okay makes life a lot simpler so I want to study these in detail and so I might logically carry those through to my FMEA well as long as I'm here I might as well check off the process map and I might as well check off the C and E matrix and the Pareto chart is done we've got some more stuff to do so I'm going to later with this so I'm going to leave that unchecked okay now if you notice here the heavy variables our cleaning procedure time sense surface prep the material physical properties and a couple of other things. 2018
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- 7. 37 M 5 M ©2018 Arrelic Reliability Private Limited ·All rights reserved . Arrelic, Arlytic, PdMAAS, are trademarks of Arrelic . No part of this document may be distributed, reproduced or posted without the express written permission of Arrelic. DesignedinIndia|Arrelic www.arrelic.com [email protected] Disclaimer The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavour to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation. In this regard, Arrelic has no responsibility for the consequences hereof and no liability. About Arrelic Arrelic is a fast-growing deep-tech firm aiming to bring the next level of IoT based sensor technology to transform the mode of manufacturing operation and maintenance practice of various industries with extensive expertise in Reliability Engineering, Predictive Maintenance, Industrial Internet of Things (IIoT) Sensors, Machine Learning and Artificial Intelligence. We provide a single ecosystem for catering all industry needs from Consulting to IoT and Analytics as well as providing Training and Development courses for different stakeholders. We aim to help manufacturing industries to improve their overall plant productivity, reliability and minimize total production cost by 25-30% by eliminating machine downtime, lightening management decisions by analysing the machine data with right mind and expertise; for a worry free operation. For more queries