PrashantKurse

Lead time : Calculation starts from when the customers request is received for a product or service until the product / service is delivered to customer . In other words Lead time = End date - creation date Cycle time : Calculation starts from when the actual work with respect to product / service starts. Until the delivery of product / service to customer Cycletime : Enddate - start time. The confusion is basically between the creation date and start date.

The Graham process mapping methods has been the Business Analytics choice for business process analytics since 1946.GPM is an affordable process mapping tool that makes it easy for you to understand.improve and manage business process .by using it it will tell the story of the process .Maps taht tell the reaader what is goi g on, what items are used, who is doing the work , where the work is being done and how long it takes. No other type of process charts supports decision making analysis, training and procedure writing as effectively as Graham process maps . The structure helps you to prepare process maps quickly and consistently.its helps in strong foundation for continuous improvement. It has eight basic symbols add as attachement . ...

Types of Data There are two types of data. Qualitative and Quantitative. Qualitative data cannotmbe measured objectively.it can be ranked or ordered. Quantitative data can be measured objectively. Qualitative data is further divided into nominal,ordial and binary. Quantitative data is divided into continous and discrete.. Most of thw cases when data is in % then the confusion starts. The golden rule states that 1) Discrete numerator, continuos denominator than data is continuous 2) Continuous numerator and continuos denominator than data is continuous. 3) Discrete numerator and discrete denominator than data is disxrete. 4) Continuous numerator and discrete denominator than data is continuos.

Correction action Action taken for detected non conformity owr any undesired event.by further analysis of rootcause and to see that it doesnot re occure again.its basically for past event . Preventive action Action taken for pontential cause that can happen in future . This event has not caused.its for preventing the issues that can raise in future. Eg My computer is dead .so i called the technician.he started to root cause the problem and found that its was due to the loose connection i.e some screws attached to the mother board is loosened so he fixed the issue by tighned the screws.this is a case of corrective action. He furthers checks all the remaning ten computers so that such problems must not raise in future.this is a case of preventive action where potential causes for occurence is taken care. He further check

Pull system Is a control oriented system that operates by receiving signals that more production is needed .(Make to order) In pull system the company doesnot stock any inventory in advance as the customers order is received the production process starts by purchasing the required parts. The challange is that if we are producing the products as per the customer orders .the parts is of any specific make or characteristics which is not easily available then we are unable to produce the finished product as per our commitment and the companies image is lost due to nonconfirmity of committed dates to deliver the product. In such cases push system is given byin instead of pull system.

Generally the good hypothesis decisions leads to new understandings and better alternatives to achieve the goals . Lets take an example as an organization we decide to spend on advertizing or what effect will result in price hike on customers. Its easy tobmake a wild assumptions. A business hypothesis always helps to solve the problems . In the start it takes support of some foundational information. Basically, hypothesis is theory. The theory details you generally expect from a certaion thought of enquiry. A hypothesis based on years of business research in a particular field hepls you to focus ,define and appropriately direct your research. You will not blindly or with a gut f÷ling chase to approve or disapprove it. The hypothesis predicts the relationship between two variables. Data collection establishes the foundation for appraising the quality of a product or service.but without correct data processing, it becomes challenging make an objective conclusion.it leads to wrong interpretation. Hypothesis testing is the process of using statistics to determine the probability that a specific hypothesis is true. Hypothesis test evaluates two mutually exclusive statements about a population to determine which statement is bestvsupported by sample data. Hypothesis testing is categorized as a parametric test and nonparametric test. The parametric includes z-test, t-test, and f-test. The nonparametric test includes sign test, Wilcoxon rank sum test, Kruskal Wallis test and permutation test. Its uses in analyze phase Examples: The statement of problem Suppose that the doctor claims those who are 17 yearscold have an average body temperature that is hogher than the commonly acepted human temperature of 98.6 degrees F .A simple random statistical samplevof 25 people ,each of age 17 is selected.The average temperature of the sample of the sample is found to be 98.9 degrees f .Further suppose that we know that the population standard deviation of every one who is 17 years old is 0.6 degress. The null hypothesis The claimbbeing investigated is that the average body temperature of everyone who is 17 yrs is greatervthan 98.6 degrees.This correspondes to the ststement x>98.6. The negation of this is that the population average is not greatervthan 98.6degress.In other words , the average temperature is les than or equal to 98.6 degrees. I.e x<=98.6. One of these statements must become the null hypothesis, and the other should be the altenative hypothesis. The null hypothesis contains equality. So for above, the null hypothesis Ho : x= 98.6. Its a common practise to only state the null hypothesis in terms of an equals sign and not a greater or equal or less thannequal to. The orther which does not contain equality is alternative hypothesis. One or two tails. The statement of our problem will determine which kind of test to use .if the alternative hypothesis contains a not equal to sign thenbwe use two tailed test. In other two cases whenbthebaltrnative hypothesisbcontains strict inequality webuse one tailes test. Choice ofba significance Here we choose the valuebof alpha , our significance level.It is typical to let alpha be 0.05 or 0.01.For this example we will use 5% level.i.e the alpha = 0.05. Choice of test statistic and distribution. Now we need to determine which distribution to use .the sample is from a population that is normally distributed as the bell curve, so we can use the standard normal distribution. A table of z scores will be necessary. The test statistic is found by the formulae for the mean of a sample, rather than thevstandard deviation we use standard error of the sample mean.Here n= 25 which hasba square root of 5. So the standard error is a 0.6/5 = 0.12.our test statistic is z = (98.9-98.6)/.12 = 2.5. Accepting and Rejecting At a 5% significance level, the critical value for a one tailed test is found from the table of z scores to be 1.645 Since the test statstic does not fall within the critical region we reject thevnull hypothesis. The pvalue method. There is a slight variation if we conduct our test using p values. Here we see that a zscore of 2.5 has a p value of 0.0062.Since this less than the significance level of 0.05 we reject null hypothesis. Conclusion We conclude by stating the results of our hypothesis test. The statistical evidence shows that eitherva rare event has occured or that the average temperature of thosevwho are 17yrs is greater than 98.6degrees.

Fault Tree Analysis.docx Fault Tree Analysis (FTA) FTA is a top down approach to problem solving.it means that you are taking a top level view of a process or a product , identifying a potential failure or undesired event .it uses deductive reasoning FTA is a methodology used to determine the probability that an unwanted event will occur . FTA consists of a Boolean logic gates such as AND,OR,NOR,XOR ETC. In FTA we build a visual failure analysis tree diagram .the top of the tree is undesired result below this are potential causes leading to the undesired result representing the gates. The technique starts with a failure and works backward toward s the root cause. USES – FTA To predict failure events and potential causes. To analyse a complete system containing numerous interconnected cause of failure To identify causes of a failure after it has happened. To identify causes of a potential system failure during the design process Best Used in Industry- Its best used in manufacturing ,electrical risk management ,Aerospace, Pharma projects and nowadays in software industries. Applicable to a system when undesired event is suspected of being caused by more than one pathway. Least used in industry FTA is least used where the number of effects are high. Not applicaple when undesired events can be causedonly by external events. Not applicable when undesired events cannot be stopped,slowec or mitigated

Please do find attached Kaizen,Kaikaku & kakushin reply. Lean concept.docx

Dear VK, I am using Sixsigma for Coconut farming. The data i have collected consists of BLOCK 1 DATE Trees Spathes No. of 120 days Nuts Emasc. Emasc. Buttons Count Harves. 6 7 8 9 10 11 12 TOTAL 0 0 0 0 0 The data has many zero values and the data is non normal so how to go about it and which tests to conduct .