Statistical Process Analysis

Rating:
Summary: Unique approach to SPC
Review: This book is great! Through numerous real-world examples, it takes high-level ideas and makes them understandable. I highly recommend this book for anyone using SPC.

Rating:
Summary: Bit wordy but a must SPC reference
Review: With dozens of cookie cutter SPC books out there, I was skeptical that Alwan's book would be much different. I was pleasantly surprised. The author spends a great deal of time impressing upon the reader that control charts are potentially useless when processes don't behave like textbook examples. So, there is a data analysis approach taken with time spent on dealing with issues of nonormality and autocorrelation and time patterns. This is pretty different and not found in other SPC books that I have run across.

The time-series analysis is on the elementary level, e.g., using OLS regression to fit an AR(1). The book doesn't go deep into ARIMA models.

There is an interesting discussion on p charts and c charts. Basically, the author is dealing with the issue of overdispersion though he does not say the term. This is not to my knowledge covered in other SPC books but it is clearly an issue in reality.

The chapter on CUSUMs is particularly done well and is quite comprehensive.

If there is one negative point, the book is a bit too wordy to my liking. I think he could have shorten up his prose a bit. But, for folks that are leary of statistics, the extra text might help get the point across.

Most folks will recognize Montgomery's Intro. to Stat. Quality Control as the main player in the field. Given its longer history, I don't think that will change but Alwan's book is definitely an add-on to any decent SPC collection of reference books.

Rating:
Summary: Bit wordy but a must SPC reference
Review: With dozens of cookie cutter SPC books out there, I was skeptical that Alwan's book would be much different. I was pleasantly surprised. The author spends a great deal of time impressing upon the reader that control charts are potentially useless when processes don't behave like textbook examples. So, there is a data analysis approach taken with time spent on dealing with issues of nonormality and autocorrelation and time patterns. This is pretty different and not found in other SPC books that I have run across.

The time-series analysis is on the elementary level, e.g., using OLS regression to fit an AR(1). The book doesn't go deep into ARIMA models.

There is an interesting discussion on p charts and c charts. Basically, the author is dealing with the issue of overdispersion though he does not say the term. This is not to my knowledge covered in other SPC books but it is clearly an issue in reality.

The chapter on CUSUMs is particularly done well and is quite comprehensive.

If there is one negative point, the book is a bit too wordy to my liking. I think he could have shorten up his prose a bit. But, for folks that are leary of statistics, the extra text might help get the point across.

Most folks will recognize Montgomery's Intro. to Stat. Quality Control as the main player in the field. Given its longer history, I don't think that will change but Alwan's book is definitely an add-on to any decent SPC collection of reference books.