Dear friends,
I have a customer which has a specific tool for SPC.
This tool has few different applications.
Two of this is:
1. Binominal law of distribution
2. Poisson law

Can somebody give some informations about two of this ?
I want very simple information to understand
• What really means these laws
• What’s the specific of them?
• Where(when) should I have to applied them

I have to submit some parts for approval and I don’t really know what’s about all of this.
Thank you very much and God bless you.

Dear friends,
I have a customer which has a specific tool for SPC.
This tool has few different applications.
Two of this is:
1. Binominal law of distribution
2. Poisson law

Can somebody give some informations about two of this ?
I want very simple information to understand
• What really means these laws
• What’s the specific of them?
• Where(when) should I have to applied them

I have to submit some parts for approval and I don’t really know what’s about all of this.
Thank you very much and God bless you.

The binomial distribution is for when you have data on something that may have one of two outcomes: heads/tails, go/no go, good/bad, accept/reject, on time/late. Each result must be independent of any other result. That is, if I flip a coin and get heads, that coin flip result does not affect the next result. One uses a "p-chart" control chart for these data. See http://www.hanford.gov/rl/uploadfiles/VPP_pchart.pdf for an example.

The poisson distribution is used for counting independent arrival events. Such as the number of people arriving in one minute increments at a bank teller. It also is useful for counting independent events such as numbers of injuries. We utilize a c-chart here, http://www.hanford.gov/rl/uploadfiles/VPP_cchart.pdf.

There is a variation on the c-chart, the u-chart which also uses the Poisson distribution. In this case we count defects or events per some area of opportunity. Injuries per 200,000 hours worked is a common example. See http://www.hanford.gov/rl/uploadfiles/VPP_uchart.pdf.

The binomial distribution is for when you have data on something that may have one of two outcomes: heads/tails, go/no go, good/bad, accept/reject, on time/late. Each result must be independent of any other result. That is, if I flip a coin and get heads, that coin flip result does not affect the next result. One uses a "p-chart" control chart for these data. See http://www.hanford.gov/rl/uploadfiles/VPP_pchart.pdf for an example.

"The poisson distribution is used for counting independent arrival events. Such as the number of people arriving in one minute increments at a bank teller. It also is useful for counting independent events such as numbers of injuries. We utilize a c-chart here, http://www.hanford.gov/rl/uploadfiles/VPP_cchart.pdf."

Can I use this for one side evaluation? For "minimum force" for example? Or for torque?

There is a variation on the c-chart, the u-chart which also uses the Poisson distribution. In this case we count defects or events per some area of opportunity. Injuries per 200,000 hours worked is a common example. See http://www.hanford.gov/rl/uploadfiles/VPP_uchart.pdf.

Unfortunately I can’t open the link to read your matherial.
Thank you very much for your answer.