Swapnil Srivastava

Check sheet is a basic tool of six sigma which is structured way of recording and analysing data for accessing a process or input to other analysis. It is a simple tool used by people on shop floor for data collection. A check sheet consists of information of who has filled the check sheet, what was collected, where was data collected i.e. facility, when collection took place and why was data collected When should Check Sheet be used: 1) when data is observed repeatedly by same person or at same location 2) when data is recorded on basis of frequency or patterns of problems, defects , events etc. 3) when collecting data from production process Have Check Sheets become Obsolete ? The check sheets which were once among the 7 basic tools of six sigma have now become obsolete since it was difficult to deal with complex data . They have been replaced by Business Management softwares which can collect data automatically making assessment of processes independent of human intelligence and reliability of check sheet . Through these softwares we can study the data in any format (Tabular of graphical) in just few clicks. hence the day is not far when it will be completely removed as a topic in QC.

There is always some degree of variation in measuring data. Variation gives us an idea on how data is distributed about the the expected mean. Following are the 2 types of variation found in any data. COMMON CAUSE VARIANCE SPECIAL CAUSE VARIANCE Also known as Natural Problems, Noise , Random Cause Assignable Cause Found By Harry Alpert W Edwards Deming Definition Common causes of variance are the usual quantifiable and historical variations in a system that are natural. Special Cause of Variance refers to unexpected glitches that affect a process. Characteristic These variations are ongoing, consistent, and predictable.They are an inherent part of a process These are variations that were not observed previously and are unusual, non-quantifiable variations. It is not usually part of your normal process and occurs out of the blue Variation in Control chart On a control chart, they are indicated by a few random points that are within the control limit. On a control chart, the points lie beyond the preferred control limit or even as random points within the control limit. Solution These kinds of variations will require management action since there can be no immediate process to rectify it. You will have to make a fundamental change to reduce the number of common causes of variation. This type of problem needs to be found and addressed immediately so as to prevent recurrence of it in the project. Why is the differentiation important and misjudging one of these can create problem in real world The differentiation is important because if common cause of variation stays in a process then process doesn't become unstable i.e. the data is in control limits . The presence of common cause of variation is common and it is not actionable . I. But the presence of special cause makes data unstable i.e. that data lies out of control limits and it immediately requires rectification.

Jidoka term is ued in Toyota ProductionSystem which means intelligent automation or automation with human touch. Its an Quality check method which ensures all quality checks and balances are carried out. Jidoka enables machinery to b eenough to 1) Identify process malfunction/ Product defect 2) Stop itself 3) Fix and correct 4) Investigate a rootcause and install a counter measure The term Jidoka(autonomation) is applied to a machine with a built in device to make judgement whereas regular Japanese term Jido(Automation) is applied to a mchine which moves on its own. Jidoka refers to a machine which moves wih a human touch. Since it has an inbult intelligence hence one operator is sufficient to oversee several machineries. Whereas Automation that is Jido refers to a machinery which is under monitoring of a operator . There are several opertors for all the machineries.

Any process along the value stream that sets the pace of entire stream. The pacemaker is most of the time near the customer end of value stream i.e. the final assembly cell, but in a FIFO flow of product from upstream to downstream the pacemaker process is at the upstream . On future state mapping pacemaker is the production process that is controlled by outside customers order

Mistake Proofing is a Japanese technique that makes it impossible to make an error or makes the error obvious once it has occurred. Here all the interpretations are correct. 1) there are some prevention techniques like shutdown prevention and control prevention through which error may not happen at all. Ex. These days furniture parts which has to be assembled are easy to do since there is only one way to assemble as per fitting and shape of joints. 4) some techniques are also such that error might happen but defect will happen and get corrected. Ex. Autocorrect option in text messages . We may write incorrect spelling but it will get corrected automatically. 3) human error may happen but defect is less likely. Ex. Warning prevention techniques like red light in traffic signal. Though when it's red light, it means one had to stop but still some people might commit mistake if they were absent minded but chances are less of this case. 2) human error may continue to happen but error won't happen in cases of shutdown detection. Example.: When washing machine gets overheated there is auto cut takes place which doesn't let washing machine to fail.

When our toast burns and or there is smoke from a burnt food in oven and smoke alarm fails then it's type 1 error or false alarm. When there is a fire in house and smoke alarm fails then it's type 2 error or missed alarm. Though type 2 error is very rare assume the functioning proper functioning of smoke alarm but it comes at cost of too many type 1 error

False alarm is more preferred over missed alert because false alarm is a detection technique where defect has already happened whereas missed alert is a prevention technique where we have missed some steps in process of preparing end product which is a warning which might lead to defect but defect hasn't happened

The Central limit theorem states that when sample size tends to infinity, the sample mean will be normally distributed Law of large numbers states that when sample size tends to infinity , sample mean equals the population mean The difference between central limit theorem and Law of large numbers: The Central limit theorem tells us that when sample size tends to infinity, the distribution of sample mean approaches normal distribution . It implies that shape of sample distribution approaches bell curve which is shape of normal distribution. Whereas Law of large numbers tell us where the centre ( maximum point ) of bell curve is located . As the sample size approaches infinity , centre of distribution of sample means becomes equal to centre of distribution of population mean.

Fault tree analysis introduced by Bell Laboratories is a deductive failure analysis where we try to find the cause of any undesirable state of the system using Boolean logic. It is mainly used in Safety and Reliability engineering to identify the reasons causing a system to fail, Risk analysis of the system, and finding event rate of the system. FTA is used in complex and hazardous processes of Aerospace sector, Pharma sector, chemical engineering, nuclear power sector and software engineering for debugging Where do you think it is more effective It is more effective for analysing faults of complex / Hazardous systems using boolean logic Where do you think its least useful Its least useful when you have to analyse the effect of a single component, equipment and subsystem. It is good at showing how a system is resistant to single/ multiple initiating faults but it cannot help in the exhausting analysis that is in analysing all the faults.

Fault tree analysis introduced by Bell Laboratories is a deductive failure analysis where we try to find the cause of any undesirable state of the system using Boolean logic. It is mainly used in Safety and Reliability engineering to identify the reasons causing a system to fail, Risk analysis of system, and finding event rate of the system. FTA is used in complex and hazardous processes of Aerospace sector, Pharma sector, chemical engineering, nuclear power sector and software engineering for debugging

5S was developed in Japan by Toyota for work place organization. It is one of the first tool that can be applied by a company to fit into lean culture. It's right that 5S makes sense in workplace even in service sector but it doesn't really help us save money in service sector since it's a lean tool and if we try to see financial impact of lean tool the return is very poor but one can't really drive continuous improvement with this approach . But if we try to see the financial impact of the system as a whole the return is priceless. It's less like maths and more like chemistry where 1 bowl NaCl + 1 beaker H2SO4 is not equal to 1 bowl NaCl and 1 beaker H2SO4. It's all together a new product. Similar way the return / Saving of 5S is not cost saving in service industry but will lead to qualitative work, increased productivity, reduction in time, elimination of Muda and a Kaizen culture which will not further effect our bottom line in long run.

For any organization to stay competitive and survive long, these 3 Ks are very necessary which are Kaizen ( change for better), kaikaku ( revolutionary change) and Kakushin ( innovation) . Kaizen means elimination of non value added work ( muda, 7+1 type of waste) in work processes to bring continuous improvement. It was started by Toyota around 40 years back and was later adopted rapidly by most of the industries so a need of more rapid and agile practice was felt. So Kaikaku came into picture. Kaikaku is a more radical change which indicates big/ revolutionary improvements. It allows organization to implement fundamental changes in their production system mostly performed by executives and top management and involves large investment. Many times, breakthrough inventions are required more than any improvements in current processes. Such kind of innovation and renewal is called Kakushin. Difference: kaizen is small change to make process better and involves little/ no investment. It can be done by anybody on shop floor. Kaikaku is revolutionary change .I.e. a bigger change which involves fundamental changes in processes to get a more accurate result. It involves lot of investment and is implemented by executives/ management. Kakushin is Innovation or breakthrough in products/ services which has more to do with mindset of people. It involves huge investment and risks and is implemented only by senior management/ MD / CEOs of organization How they complement each other ? For any company to succeed they first need to bring Kaizen ( small changes) in processes to bridge gap between actual and target. Once they are able to achieve the target to change their standards they need to implement Kaikaku so as to embrace with the rapid improvements and bring revolution in processes. Once they have achieved everything thing with their current processes, then there's a need to innovate in products/ services to differentiate themselves from other companies for which Kakushin is required. What would a company loose if one of them is not implemented? Kaizen is most basic step for continuous improvement, without which a company won't survive. Kaikaku is next step to be no. 1 organization in the industry for which revolution is required in processes and without you one can't be first choice for its customers. Kakushin is further next step so that your competitors can't even think of competing with you. It's innovating such that you have monopoly in your field and to differentiate oneself from others so that customers have no choice.

Today we mostly say that what is not measurable can't be managed. But a lot of things are present in management like compliance, branding, technology, staff motivation, customer feedback etc which needs to be managed and improved but which can't be measured. There's also another side to this please..we can also say that numbers are only indicators and tell us where to look and what to look for but we can't rely on it completely to know the status of concerned parameter. This is what Deming wants to tell.he is not asking us to abandon all performance metrics. But he wants us to tell that there are also few parameters which we can't measure but we need to look into it.