تخمین نقطه‌ی تغییر پله‌ای در پروفایل‌های خطی چندگانه با استفاده از شبکه‌ی عصبی احتمالی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی صنایع، دانشکده فنی و مهندسی، واحد تهران غرب، دانشگاه آزاد اسلامی، تهران، ایران

2 استادیار گروه مهندسی صنایع، واحد تهران غرب، دانشگاه آزاد اسلامی، تهران، ایران

3 استادیار گروه مهندسی صنایع، دانشکده فنی و مهندسی، واحد تهران غرب، دانشگاه آزاد اسلامی، تهران، ایران

چکیده

تخمین نقطه‌ی تغییر با کاهش مدت زمان لازم و هزینه‌ی تشخیص عامل اثرگذار، به مهندسین کیفیت در جستجوی مؤثر برای کشف انحرافات با دلیل و بهبود کیفیت یک محصول یا یک فرآیند کمک می‌کند. در این مقاله، از رویکرد شبکه‌ی عصبی مصنوعی احتمالی برای تخمین نقطه‌ی تغییر پله‌ای در فاز 2 پایش پروفایل‌های چندگانه استفاده می‌شود. عملکرد شبکه‌ی عصبی احتمالی پیشنهادی برای تخمین نقطه‌ی تغییر با استفاده از شبیه‌سازی مونت‌کارلو مورد سنجش قرار می‌گیرد. نتایج شبیه‌سازی‌ها بیانگر این است که شبکه‌ی پیشنهادی در تخمین نقطه‌ی تغییر، در تغییرات کوچک از رویکرد حداکثر درستنمایی بهتر عمل می‌کند. اما در تغییرات متوسط تا بزرگ رویکرد حداکثر درستنمایی بهتر عمل می‌کند. به علاوه، مزیت دیگر رویکرد پیشنهادی این است که بر خلاف رویکرد حداکثر درستنمایی نیازی به هیچ گونه پیش آگاهی از نوع تغییر ندارد و به خوبی قادر به تخمین انواع نقاط تغییر نیز هست.

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