بهینه‌سازی ترکیبی موجودی قطعات یدکی و فعالیت‌های نگهداری و تعمیرات

نویسندگان

دانشگاه جامع امام حسین(ع)

چکیده

امروزه با توجه به شرایط رقابتی موجود، شرکت­ها تلاش می­ کنند به­ منظور کاهش هزینه­ های خود، سطح موجودی خود را کاهش دهند. در مدیریت و کنترل موجودی در سازمان‌ها، باید یک توازن بین سطح موجودی قطعات یدکی و هزینه و ریسک ناشی از عدم وجود قطعه به هنگام نیاز برقرار نمود. واضح است که این سطح از موجودی قطعات یدکی متأثر از خصوصیات دستگاه‌ها و قابلیت اطمینان آنها است. به‌ طور­ کلی در صنایع مختلف،سیاست‌های نگهداری و تعمیرات و تعیین میزان موجودی قطعات یدکی به­ صورت جداگانه انجام می‌شوند. در این مقاله، از شبیه­ سازی مونت­ کارلو به منظور بهینه­ سازی ترکیبی فعالیت­ های نگهداری و تعمیرات مبتنی بر وضعیت و موجودی قطعات یدکی استفاده شده است. از الگوریتم ژنتیک باینری به­ منظور پیدا کردن مقادیر بهینه متغیرهای تصمیم استفاده گردیده است. در این سیاست؛ فواصل بازرسیT))، حداکثر موجودی قطعات یدکی(S)، نقطه سفارش مجدد موجودی قطعات یدکی(s)، سرحد فرسایش به­ منظور انجام تعویض پیشگیرانهLp)) و نیروی انسانی مورد نیاز برای انجام تعویض‌های اصلاحی و پیشگیرانه (labor)بهینه می‌شود. در مطالعه موردی برای شبیه‌سازی رویدادهای مختلف تعمیراتی، از بانک اطلاعاتی آنالیز روغن یک شرکت عمرانی شامل 8000 داده آنالیز روغن استفاده شده است. شبیه­ سازی مونت­ کارلو مورد نظر و همچنین الگوریتم ژنتیک در نرم افزار Matlabکد نویسی شده است و در پایان نتایج حاصل از شبیه­ سازی مطالعه موردی آورده شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Joint Optimization of Spare Parts and Condition Based Maintenance Using Monte Carlo Approach

چکیده [English]

Today according to the competitive conditions, companies try to reduce their inventory level to diminish the costs. In companies inventory management and control should establish a balance between inventory level of spare parts, cost and the risk that arising from absence of part when is needed. It is clear that this level of spare parts inventory affected by facility characteristics and its reliabilities. As a whole in the various industries, maintenance policies and determination of spare parts inventory level individually performed. In this paper is used Monte Carlo simulation to combinatorial optimize the condition based maintenance activities and spare parts inventory. Used binary genetic algorithm to find the optimal values of decision variables. In this optimize policy inspection intervals (T), maximum of spare parts inventory(S), spare parts renewed order point(s), frontier erosion to perform preventive replacement(LP) and human resource required to performing corrective and preventive replacements(labor). In the case study for maintenance events simulation used the oil analysis database of a construction company that included about 8000 data of oil analysis. Intended Monte Carlo simulation and also genetic algorithm coded in Matlab Software and finally the result of simulation is brought.

کلیدواژه‌ها [English]

  • Spare Parts
  • Condition Based Maintenance
  • Monte Carlo
  • Joint Optimization
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