পদ্ধতির তুলনা করুন

	সিমুলেশন-সহায়ক পরিসংখ্যানগত প্রক্রিয়া নিয়ন্ত্রণ	কন্ট্রোল চার্ট
ক্ষেত্র	পরীক্ষামূলক নকশা	পরীক্ষামূলক নকশা
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1980s–present	1924 (first use); 1931 (seminal book)
প্রবর্তক	Walter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onward	Walter A. Shewhart (Bell Labs)
ধরন	Hybrid quantitative method	Statistical monitoring and control technique
মৌলিক উৎস	Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand.
অপর নাম	Simulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPC	Shewhart chart, process-behavior chart, SPC chart, quality control chart
সম্পর্কিত	6	6
সারসংক্ষেপ	Simulation-assisted statistical process control (SA-SPC) combines computer simulation — typically Monte Carlo or discrete-event simulation — with classical SPC methods to design, test, and calibrate control charts and monitoring schemes before or alongside deployment on a real production process. Rather than relying solely on closed-form analytical assumptions, SA-SPC uses simulated data to evaluate chart performance under realistic, often non-normal process conditions.	A control chart is a time-series graph with statistically derived upper and lower control limits that separates the natural, random variation of a process (common cause) from unusual, assignable variation (special cause). Invented by Walter Shewhart at Bell Labs in 1924, control charts remain the foundational tool of Statistical Process Control and are used across manufacturing, healthcare, software, and service industries to monitor whether a process remains stable and predictable over time.